Artificial Intelligence - Science topic

Ablation of the cerebellum does not abolish locomotion in mammals (Ioffe 2013); it merely induces atonia: body movements become clumsy with postural and vestibular deficits, which is related to the negation of both proprioceptive and vestibular input to the cerebellum, which encodes where the body is with respect to itself and the outside world, i.e., with respect to the gravitational axis (Carriot et al. 2021; Demontis et al. 2017; Fuchs and Kornhuber 1969; Lawson et al. 2016; Miles and Lisberger 1981). Animals have difficulty crossing a balance beam following complete cerebellar damage and the righting reflex is interrupted. Consciousness, which is a declarative attribute, is not affected following cerebellar damage. As with cerebellar impairment, following neocortical ablation, locomotion is not eliminated but the sequencing of movement is severely affected (Vanderwolf 2007; Vanderwolf et al. 1978). Stepping responses can be evoked in spinal animals, but with a total loss of balance and muscular coordination since both cerebellar and neocortical support is now absent (Audet et al. 2022; Grillner 2003; Sherrington 1910).

Following a stroke that affected the left mediolateral and posterior lobes of the cerebellar cortex (including the left dentate nucleus), it was found that the subject (aged 72), a (right handed) war correspondent who had been versed in seven languages, could no longer communicate in his non-primary languages (see Fig. 1, Mariën et al. 2017): French, German, Slovenian, Serbo-Croatian, Hebrew, and Dutch (in the order of having learned the languages before the age of 40). Before the stroke, the subject used Dutch, French, and English regularly. After the stroke his primary language, English, remained intact. Most significantly, the day of the stroke, all thinking in the second languages was abolished (see Footnote 1). One day following the stroke, however, the French language returned. Nevertheless, the remaining secondary languages were abnormal. Reading was better preserved than oral and written language, likely because reading is dependent mainly on scanning a page with the eyes and having an intact neocortex for word comprehension (fMRI revealed language activations in neocortex and in the intact right cerebellar hemisphere, Mariën et al. 2017). Speaking and writing, on the other hand, are more dependent on the sequencing of multiple muscle groups, a task of the cerebellum (Heck and Sultan 2002; Sultan and Heck 2003; Thatch et al. 1992). When speaking or writing in a non-primary language, English words would intrude. The naming of objects and actions verbally was impaired, and writing was severely disrupted. When high-frequency visual stimuli (objects, animals, etc.) were presented visually (1 month after the stroke), identifying an object with the correct word surpassed 80% correctness for English, French, and Dutch, whereas it remained at under 20% correctness for German, Slovenian, Serbo-Croatian, and Hebrew. Since the execution of behavior depends on loop integrity between the neocortex and cerebellum (Hasanbegović 2024), it is highly likely that damage to the cerebellum undermined this integrity such that the least overlearned routines—German, Slovenian, Serbo-Croatian, and Hebrew—were disturbed. Note that a functional left neocortex (of the right-handed subject) with a preserved right cerebellum was sufficient to execute the overlearned languages—English, French, and Dutch.

Based on our understanding of cerebellar function, if the entire cerebellum (including the subjacent nuclei) were damaged in the subject, we would expect that even English, the primary language, would be compromised, and most importantly, the learning of a new language would be rendered impossible, given the dependence of behavioral executions (and learning) on intact neocortical-cerebellar loops (Hasanbegović 2024; also see: Sendhilnathan and Goldberg 2000b; Thach et al. 1992). Thus, thinking is affected by damage to neocortical-cerebellar loops, which concurs with the behavioral findings of Hasanbegović (2024).

Footnote 1: Self-report by the patient about the day of the cerebellar stroke: “I was watching television at my apartment in Antwerp when suddenly the room seemed to spin around violently. I tried to stand but was unable to do so. I felt a need to vomit and managed to crawl to the bathroom to take a plastic bowl. My next instinct was to call the emergency service, but the leaflet I have outlining the services was in Dutch and for some reason, I was unable to think (or speak) in any language other than my native English. I have lived in Antwerp for many years and use Dutch (Flemish) on a day-to-day basis. I called my son-in-law, who speaks fluent English and he drove me to Middelheim Hospital. We normally speak English when together. I understood none of the questions asked to me in Dutch by hospital staff and they had to be translated back to me in English. My speech was slurred. I had lost some words, I was aware of that, but I cannot recall which words. I made no attempt to speak any of the other languages I know, and in the first hours of my mishap happening, I do not think I realized that I had other languages.” (Mariën et al. 2017, p. 19)

Figure 1. Human cerebellar cortex. The mediolateral and posterior lobes are indicated. The mediolateral lobe of the cerebellum (right and left) is part of the cortico-frontal-cerebellar language loop (Stoodley and Schmahmann 2009), and cerebellar grey matter density in bilingual speakers is correlated with language proficiency (Pliatsikas et al. 2014). Typically, the innervation of the left neocortical language areas is strongest to the right cerebellum in right-handed subjects (Van Overwalle et al. 2023). Illustration from figure 8 of Tehovnik, Patel, Tolias et al. (2021).

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“Intelligent machines” have long been the subject of science fiction. However, we now live in an era in which artificial intelligence (Al) is a reality, and it is having very real and deep impacts on our daily lives. From phones to cars to finances and medical care, AI is shifting the way we live.

AI applications can be found in many aspects of our lives, from agriculture to industry, communications, education, finance, government, service, manufacturing, medicine, and transportation. Even public safety and criminal justice are benefiting from AI. For example, traffic safety systems identify violations and enforce the rules of the road, and crime forecasts allow for more efficient allocation of policing resources. AI is also helping to identify the potential for an individual under criminal justice supervision to reoffend.[1]

Research supported by NIJ is helping to lead the way in applying AI to address criminal justice needs, such as identifying individuals and their actions in videos relating to criminal activity or public safety, DNA analysis, gunshot detection, and crime forecasting.

source: https://nij.ojp.gov/topics/articles/using-artificial-intelligence-address-criminal-justice-needs

Software-defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller that can be programmed and used as the brain of the network. Recently, the research community has shown an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN.

source: Review Article

Free Access

Artificial intelligence enabled software-defined networking: a comprehensive overview

Majd Latah, Levent Toker

First published: 01 March 2019

Artificial intelligence enabled software‐defined networking: a comprehensive overview - Latah - 2019 - IET Networks - Wiley Online Library

Looking for Health care professionals interested in the mental health research study.

Looking for Health care professionals interested in the mental health research study. Empathetic AI Systems for Mental Health Support: Bridging the Human-AI Interaction Gap Greetings, We are currently seeking individuals to participate in an interview focusing on user experiences and empathy dimensions within AI mental health systems. The interview is expected to last approximately 60 minutes. We are specifically targeting participants who are 18 years old and above, including users of existing mental health support apps, healthcare professionals engaged in mental health care, as well as designers and developers working on healthcare and mental health apps or software. By including these diverse groups, we aim to gain comprehensive insights into the effectiveness, empathy, and design challenges of AI-driven mental health systems. As a token of appreciation for your time, each participant will receive a $10 (USD) Amazon gift card. Participation in this study is entirely voluntary, and all responses provided during the interview will be kept strictly confidential and anonymous. The results of this study will be thoroughly analyzed and subsequently published. This study has received the necessary approval from the King Khalid Research Ethics Committee, as indicated by the Ethical Clearance Certificate (ECM#2024-1109). If you meet the aforementioned criteria and are interested in contributing to our research, we cordially invite you to participate. WHO CAN I TALK TO? If you have any questions or concerns about the research, please feel free to contact Dr. Asma Aldrees ([email protected]) , Dr. Karthik Meduri ([email protected]), Durga chavali ([email protected])

Greetings,

I invite you to participate in a research study aimed at exploring the impact of Artificial Intelligence (AI) on education, focusing specifically on its effects on staff roles, skill requirements, and time management. Your insights are crucial for understanding the broader implications of AI adoption in Education

Research Objective

The objective of this qualitative research is to explore the perceptions and experiences of educational staff regarding the adoption of AI in education. Specifically, it aims to understand how AI technologies influence staff roles, skills development, training needs, and time management, and how these changes affect the overall quality of education.

Privacy Statement

We are committed to protecting your privacy and confidentiality. All information shared during the interview will be anonymized, and any identifiable information will be kept strictly confidential. Participation is voluntary, and you may withdraw at any time without consequence.

Meeting

Please book your slot for an online meeting.

Best Regards,

Tarek ElMourad

As we look to the future of scientific research and communication, it's clear that advances in AI will have a major impact. AI-powered tools are already augmenting many aspects of the research workflow, from literature synthesis to data analysis.

The aim of this study is to publish in a top-quality journal.

As the computing power of processors and the ability to process large and increasingly large data sets and information grows rapidly year on year thanks to technological advances, so also the sets of data and information, so also the possibilities for multi-criteria, automated analysis of large data sets on Big Data Analytics platforms, including the use of Industry 4.0 technologies, including machine learning, deep learning and artificial intelligence are also growing rapidly. Therefore, through the use of the aforementioned technologies, including artificial intelligence and Big Data Analytics, it is also possible to improve the processes of analysing the sentiment of large collections of publications and conducting semi-automated bibliometric research on large collections of publications, including scientific publications collected in online indexing databases of scientific publications. In view of the above, the application of new Industry 4.0 technologies, including new generations of artificial intelligence and computerised analytical Big Data Analytics platforms, may increase the scale of automation of the processes of conducting sentiment analysis on large sets of data and information contained in publications included in online indexing databases of scientific and/or professional publications and in the framework of bibliometric research carried out. The key determinants limiting the possibility of conducting multi-criteria analyses, including sentiment analyses of the content of multiple online publications, professional and/or scientific journals, in addition to technological limitations, include the issue of IT compatibility of Big Data Analytics platforms and the structural and technical conditions of online journal portals and online indexing databases of specific publications, including scientific publications.

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What is your opinion on this topic?

What is your opinion on this subject?

Please respond,

I invite you all to discuss,

Thank you very much,

Warm regards,

Dariusz Prokopowicz

On the one hand, the development of modern and safe nuclear power technology is needed especially in the situation of creating an important source of electricity as an intermediate step in the green transformation of the energy sector, which consists of shifting power generation based mainly on emission-intensive fossil fuel combustion to clean power generation based on emission-free, fully renewable energy sources. The application of new Industry 4.0/5.0 technologies, including but not limited to machine learning, deep learning, generative artificial intelligence, Big Data Analytics, multi-criteria simulation models, Internet of Things, Blockchain, digital twins, cloud computing, autonomous robots, etc., enables the generation of new innovative solutions, improvement of applications and safety systems of energy technologies, including nuclear energy technologies. Besides, thanks to the application of the above-mentioned technologies, there are new opportunities for optimization both in the design and implementation of investment projects for the construction of new power plants and optimization in the processes of managing energy production from various energy sources within the applied mix of energy sources, taking into account the changing conditions of energy consumption, forecasting changes in energy demand in the future, changes in the economic environment, climatic conditions and other factors modeling changes in energy production from various energy sources, including those that depend on specific atmospheric and climatic conditions such as wind and solar power.

However, on the other hand, the application of Industry 4.0/5.0 technologies, including primarily generative artificial intelligence in improving technology development processes, supporting research processes, supporting management processes, etc. concerning nuclear technology, including nuclear technology applied in fields other than energy, i.e., e.g., medicine, geology, construction analytics, etc., and in the military field, may generate various kinds of very serious risks.

A cinematic vision of the kind of risks that can result from the application of artificial intelligence technology in the military sphere, including in terms of supporting the management processes of military systems taking into account ballistic missiles equipped with nuclear payloads, i.e. carried by transcontinental missiles and/or launched from submarines and strategic bombers was presented many years ago in films of the drama, thriller and at the same time science fiction genre, such as the 1983 film titled “War Games”, directed by John Badham, and the continuation of this theme in a similar film titled “War Games: The Code of Death”. “War Games: Code of Death” from 2008, directed by Stuart Gillard.

In view of the above, for at least 4 decades now, there have been considerations about the serious risks arising from the application of artificial intelligence technology in the field of computerized weapons management systems, in the field of military defense of the country, including with regard to nuclear weapons.

In view of the above, in view of the fact that the application of Industry 4.0/5.0 technologies, including, first of all, generative artificial intelligence in the military field can generate various kinds of very serious risks so it is still topical to consider the validity and scope of optimal, safe application of AI technologies in this field.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:

APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

I described the key issues concerning the problem of green transformation of the economy in the following article:

IMPLEMENTATION OF THE PRINCIPLES OF SUSTAINABLE ECONOMY DEVELOPMENT AS A KEY ELEMENT OF THE PRO-ECOLOGICAL TRANSFORMATION OF THE ECONOMY TOWARDS GREEN ECONOMY AND CIRCULAR ECONOMY

I invite you to discuss this important topic for the future of the planet's biosphere and climate.

The key issues of the problematic sources of Poland's exceptionally deep energy cross in 2022 are described in my co-authored article below:

POLAND'S 2022 ENERGY CRISIS AS A RESULT OF THE WAR IN UKRAINE AND YEARS OF NEGLECT TO CARRY OUT A GREEN TRANSFORMATION OF THE ENERGY SECTOR

In view of the above, I address the following question to the esteemed community of scientists and researchers:

Is it safe to apply generative artificial intelligence technology in conjunction with Big Data and other Industry 4.0/5.0 technologies to support the development of nuclear technology?

Is it safe to apply generative artificial intelligence technology in the development of nuclear technology?

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

How do teachers / lecturers around the globe use AI tools in language courses?

My goal is to consider the possible risks of using AI and the possibility of solving some of these problems using classical ethics. Ethics in relation to AI is usually considered either through human actions: how should we program AI to be ethical. But how can we apply classical ethical approaches to the artificial agent itself if we cannot be completely sure that it will follow the established norms?

Who knows?

This would be interesting as a pure question. This question will shed the lights to many related areas of technical worlds and non-technical ones. However I think that AI would aquire the legal personality in the near future. Then the arguments on this question and problems involved are inevitable. In a sense, of course, this question includes the eternal question: what is love?

I am writing articles on Electrical and Protection Automation, IoT and Artificial Intelligence, I am looking like minded people who can be a co-author with me.

Thanks and Regards,

Madhu

Hi Dears,

I would like to know if it is possible to access the site's content via an API. This would make the job of implementing AI much easier. I'm new in this group, so I'm asking for your guidance and support on this matter.

Sincerely, Antonio

Artificial Intelligence

Greetings,

I invite you to participate in a research study aimed at exploring the impact of Artificial Intelligence (AI) on education, focusing specifically on its effects on staff roles, skill requirements, and time management. Your insights are crucial for understanding the broader implications of AI adoption in Education

Research Objective

The objective of this qualitative research is to explore the perceptions and experiences of educational staff regarding the adoption of AI in education. Specifically, it aims to understand how AI technologies influence staff roles, skills development, training needs, and time management, and how these changes affect the overall quality of education.

Privacy Statement

We are committed to protecting your privacy and confidentiality. All information shared during the interview will be anonymized, and any identifiable information will be kept strictly confidential. Participation is voluntary, and you may withdraw at any time without consequence.

Meeting

Please book your slot for an online meeting.

Best Regards,

Tarek ElMourad

I am researching the topic of AI transformation in Education and other organization. If you have like 15 to 20 min to have an interview, book your time slot on:

Interview Questions will be mainly on:

Will the rise of artificial intelligence (AI) revolutionize research development, or will it have a negative impact on the research process? On one hand, AI could streamline research, accelerate discovery, and enhance the quality of research outputs. On the other hand, widespread reliance on AI could lead to a decrease in critical thinking skills, originality, and the value of hard work. What are the potential benefits and drawbacks of integrating AI in research, and how can we ensure that AI is used in a way that complements human creativity and innovation?

Which artificial intelligences can be useful in finding scientific papers related to a topic to prepare a literature review of the research (methodology, case study location, variables used)? Please guide me with the link of each one? Thank You

Hey everyone,

I'm writing my master thesis on the impact of artificial intelligence on business productivity.

This study is mainly aimed at those of you who develop AI or use these technologies in your professional environment.

This questionnaire will take no more than 5 minutes to complete, and your participation is confidential!

Thank you in advance for your time and contribution!

To take part, please click on the link below: https://forms.gle/fzzHq4iNqGUiidTWA

Assuming an AI system is provided with the required data and computing resources to achieve a complex task. This task would not be achieved unless the machine is powered with a well written algorithm. Since an algorithm is a program or set of instructions that a machine executes, therefore, applying it defies the concept of machine intelligence. Do you agree?

In the Netherlands, there is much concern about the distance between citizens and government and the lack of mutual trust in each other. Some say this is a result of technology - algorithms and automation of many activities are making the relationship between government and citizen (national but also local) increasingly businesslike and formal. AI could further increase this distance. There are also those who believe that AI can actually help make government more human and improve government-citizen contact. What do you guys think about this and are there people here who know of concrete examples or studies where AI is helping to make government more trusting and human?

What is the role of artificial intelligence in business management?

Conducting a SWOT analysis of the applications of artificial intelligence technology in business, in the business activities of companies and enterprises, shows that there are both many already and developing many more business applications of the said technology, i.e., many potential development opportunities are recognized in this field of using the achievements of the current fourth and/or fifth technological revolution in various spheres of business activity, as well as there are many risks arising from inappropriate, incompatible with the prevailing social norms, standards of reliable business activity, incompatible with business ethics use of new technologies. Among some of the most recognized negative aspects of improper use of generative artificial intelligence technology is the use of AI-equipped graphic applications available on the Internet that allow for the simple and easy generation of photos, graphics, images, videos and animations that, in the form of very realistically presented images, photos, videos, etc., depict something that never happened in reality, i.e., they graphically present images or videos presenting what could be described as “fictitious facts” in a very professional manner. In this way, Internet users can become disinformation generators in online social media, where they can post the said generated images, photos, videos, etc. with added descriptions, posts, comments, in which the said “fictitious facts” presented in the photos or videos will also be described in an editorially correct manner. Besides, the mentioned descriptions, posts, entries, comments, etc. can also be edited with the help of intelligent chatbots available on the Internet like Chat GPT, Copilot, Gemini, etc. However, misinformation is not the only serious problem as it has significantly intensified after OpenAI released the first versions of ChatGPT chatbot online in November 2021. A new category of technical operational risk associated with the new AI technology applied has emerged in companies and enterprises that implement generative artificial intelligence technology into various spheres of business. In addition, there is a growing scale of risks arising from conflicts of interest between business entities related to not fully regulated copyright issues of works created using applications and information systems equipped with generative artificial intelligence technology. Accordingly, there is a demand for the development of a standard of a kind of digital signature with the help of which works created with the help of AI technology will be electronically signed, so that each such work will be unique, unrepeatable and whose counterfeiting will thus be seriously hampered. However, these are only some of the negative aspects of the developing applications of AI technologies, for which there are no functioning legal norms. In the middle of 2023 and then in the spring of 2024, European Union bodies made public the preliminary versions of the developed legal norms on the proper, business-ethical use of technology in business, which were given the name AI Act. The legal normatives, referred to as the AIAct, contain a number of specific, defined types of AI technology applications deemed inappropriate, unethical, i.e. those that should not be used. The AIAct contains classified according to different levels of negative impact on society various types and specific examples of inappropriate and unethical use of AI technologies in the context of various aspects of business as well as non-business activities. An important issue to consider is the scale of the commitment of technology companies developing AI technologies to respect such regulations so that issues of ethical use of this technology are also defined as much as possible in technological aspects in companies that create, develop and implement these technologies. Besides, in order for AIACT's legal norms, when they come into force, not to be dead, it is necessary to introduce both sanction instruments in the form of specific penalties for business entities that use artificial intelligence technologies unethically, antisocially, contrary to AIAct. On the other hand, it would also be a good solution to introduce a system of rewarding those companies and businesses that make the most proper, pro-social, in accordance with the provisions of the AIAct, fully ethical use of AI technologies. In view of the fact that AIACT is to come into force only in more than 2 years so it is necessary to constantly monitor the development of AI technology, verify the validity of the provisions of AIAct in the face of dynamically developing AI technology, successively amend the provisions of the said legal norms, so that when they come into force they do not turn out to be outdated. In view of the above, it is to be hoped that, despite the rapid technological progress, the provisions on the ethical applications of artificial intelligence technology will be constantly updated and the legal normatives shaping the development of AI technology will be amended accordingly. If AIAct achieves the above-mentioned goals to a significant extent, ethical applications of AI technology should be implemented in the future, and the technology can be referred to as ethical generative artificial intelligence, which is finding new applications.

The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

We submitted a paper Large Language Models: Assessment for Singularity.

We investigated whether modern LLM technology can create the conditions for the singularity of AI, which has been discussed mainly in the field of philosophy, and modeled and discussed what kind of design is possible at the implementation level, as well as the conditions for an intelligence explosion and accelerated AI population growth.

If an autonomous AI can be created in a safe manner, the benefits to mankind are likely to be enormous, so we have begun research on prototypes of the RSI_RPF and other products proposed in this study with great care.

We are open to a wide range of opinions, including interest and discussion, and hope you will feel free to contact us to discuss about this theme.

Hey everyone,

I'm currently writing my thesis on The Role of AI in Recruitment and I'm looking for professional participants for my survey. Would you mind taking a few minutes to fill it out? Your insights would be incredibly valuable to my research.

Here's the link to the survey: https://forms.gle/85wjLYqaCMnCUHwd7

As a token of appreciation, there's also a chance to win an Amazon Voucher!

Thank you so much for your time and support! 💙

2024 4th International Conference on Computer, Remote Sensing and Aerospace (CRSA 2024) will be held at Osaka, Japan on July 5-7, 2024.

The topics of interest for submission include, but are not limited to:

1. Algorithms

Image Processing

Data processing

Data Mining

Computer Vision

Computer Aided Design

......

2. Remote Sensing

Optical Remote Sensing

Microwave Remote Sensing

Remote Sensing Information Engineering

Geographic Information System

Global Navigation Satellite System

......

3. Aeroacoustics

Aeroelasticity and structural dynamics

Aerothermodynamics

Airworthiness

Autonomy

Mechanisms

......

All accepted papers will be published in the Conference Proceedings, and submitted to EI Compendex, Scopus for indexing.

Full Paper Submission Date: May 31, 2024

Registration Deadline: May 31, 2024

Conference Date: July 5-7, 2024

Invitation code: AISCONF

*Using the invitation code on submission system/registration can get priority review and feedback

Guest Editors: Abdulqadir Nashwan, MSc, RN, Hamad Medical Corporation, Qatar Kathrin Seibert, DPH, MSc, RN, University of Bremen, Germany Submission Status: Open  |  Submission Deadline: 27 January 2025 BMC Nursing is calling for submissions to our Collection, Artificial intelligence and nursing practice. This collection explores the diverse applications of AI in nursing; ranging from innovative clinical interventions to ethical considerations and implications for healthcare delivery. for more details ⬇

Dear Colleagues,

Ready to showcase your research on cutting-edge crop yield predictions?

We are thrilled to announce a special issue dedicated to the intersection of artificial intelligence and remote sensing in predicting crop yields.

This special issue focuses on AI and remote sensing technologies to provide early and precise yield estimations, thereby revolutionizing farming practices.

Researchers are invited to submit their innovative solutions and research findings on a wide array of topics, including:

🚜 IAI and LiDAR precision agriculture.

📡 satellite imagery for crop monitoring and yield estimation.

🌿 multispectral and hyperspectral imaging in horticulture.

🌦️ Machine learning models for weather impact on crop yields.

🦠 AI-driven pest and disease detection .

💧 Optimization of irrigation systems using remote sensing.

🤖 Deep learning for crop classification.

🌱 Predictive analytics for soil health impact on crop yields.

🔢 Automated crop counting and size estimation.

🌍 Impact of climate change on crop yields.

Don't miss the chance to contribute to this exciting field! Submit your research now: mdpi.com/si/199287

Hey everyone,

I'm currently writing my thesis on The Role of AI in Recruitment and I'm looking for professional participants for my survey. Would you mind taking a few minutes to fill it out? Your insights would be incredibly valuable to my research.

Here's the link to the survey: https://forms.gle/85wjLYqaCMnCUHwd7

As a token of appreciation, there's also a chance to win an Amazon Voucher!

Thank you so much for your time and support! 💙

CMC-Computers, Materials & Continua new special issue“Emerging Trends and Applications of Deep Learning for Biomedical Signal and Image Processing”is open for submission now.

Submission Deadline: 31 March 2025

In this special issue, we delve into the cutting-edge advancements and transformative applications of deep learning techniques within the realms of biomedical engineering and healthcare. Deep learning, a subset of artificial intelligence, has emerged as a groundbreaking tool, offering unparalleled capabilities in interpreting complex biomedical signals and images. This issue brings together a collection of research articles, reviews, and case studies that highlight the innovative integration of deep learning methodologies for analyzing physiological signals (such as EEG, ECG, and EMG) and medical images (including MRI, CT scans, X-rays, and etc.).

The content spans a broad spectrum, from theoretical frameworks and algorithm development to practical applications and case studies, providing insights into the current state-of-the-art and future directions in this rapidly evolving field. Key themes include, but are not limited to, the development of novel deep learning models for disease diagnosis and prognosis, enhancement of image quality and interpretation, real-time monitoring and analysis of biomedical signals, and personalized healthcare solutions.

Contributors to this issue showcase the significant impact of deep learning on improving diagnostic accuracy, enabling early detection of abnormalities, and facilitating personalized treatment plans. Furthermore, discussions extend to ethical considerations, data privacy, and the challenges of implementing AI technologies in clinical settings, offering a comprehensive overview of the landscape of deep learning applications in biomedical signal and image processing.

Through a blend of technical depth and accessibility, this special issue aims to inform and inspire researchers, clinicians, and industry professionals about the potential of deep learning to revolutionize healthcare, paving the way for more innovative, efficient, and personalized medical care.

For submission guidelines and details, visit: https://www.techscience.com/.../special.../biomedical-signal

Advanced analytical systems, including complex forecasting models that enable multi-criteria, highly sophisticated, big data and information processing-based forecasts of the development of multi-faceted climatic, natural, social, economic and other processes are increasingly based on new Industry 4.0/5.0 technologies, including Big Data Analytics and machine learning, deep learning and generative artificial intelligence. The use of generative artificial intelligence technologies enables the application of complex data processing algorithms according to precisely defined assumptions and human-defined factors. The use of computerized, integrated business intelligence information systems allows real-time analysis on the basis of continuously updated data provided and the generation of reports, reports, expert opinions in accordance with the defined formulas for such studies. The use of digital twin technology allows computers to build simulations of complex, multi-faceted, prognosticated processes in accordance with defined scenarios of the potential possibility of these processes occurring in the future. In this regard, it is also important to determine the probability of occurrence in the future of several different defined and characterized scenarios of developments, specific processes, phenomena, etc. In this regard, Business Intelligence analytics should also make it possible to precisely determine the level of probability of the occurrence of a certain phenomenon, the operation of a process, the appearance of described effects, including those classified as opportunities and threats to the future development of the situation. Besides, Business Intelligence analytics should enable precise quantitative estimation of the scale of influence of positive and negative effects of the operation of certain processes, as well as factors acting on these processes and determinants conditioning the realization of certain scenarios of situation development. Cloud computing makes it possible, on the one hand, to update the database with new data and information from various institutions, think tanks, research institutes, companies and enterprises operating within a selected sector or industry of the economy, and, on the other hand, to enable simultaneous use of a database updated in this way by many beneficiaries, many business entities and/or, for example, also by many Internet users in a situation where the said database would be made available on the Internet. In a situation where Internet of Things technology is applied, it would be possible to access the said database from the level of various types of devices equipped with Internet access. The application of Blockchain technology makes it possible to increase the scale of cybersecurity of the transfer of data sent to the database and Big Data information as part of the updating of the collected data and as part of the use of the analytical system thus built by external entities. The use of machine learning and/or deep learning technologies in conjunction with artificial neural networks makes it possible to train an AI-based system to perform multi-criteria analysis, build multi-criteria simulation models, etc. in the way a human would. In order for such complex analytical systems that process large amounts of data and information to work efficiently it is a good solution to use state-of-the-art super quantum computers characterized by high computing power to process huge amounts of data in a short time. A center for multi-criteria analysis of large data sets built in this way can occupy quite a large floor space equipped with many servers. Due to the necessary cooling and ventilation system and security considerations, this kind of server room can be built underground. while due to the large amounts of electricity absorbed by this kind of big data analytics center, it is a good solution to build a power plant nearby to supply power to the said data center. If this kind of data analytics center is to be described as sustainable, in line with the trends of sustainable development and green transformation of the economy, so the power plant powering the data analytics center should generate electricity from renewable energy sources, e.g. from photovoltaic panels, windmills and/or other renewable and emission-free energy sources of such a situation, i.e., when a data analytics center that processes multi-criteria Big Data and Big Data Analytics information is powered by renewable and emission-free energy sources then it can be described as sustainable, pro-climate, pro-environment, green, etc. Besides, when the Big Data Analytics analytics center is equipped with advanced generative artificial intelligence technology and is powered by renewable and emission-free energy sources then the AI technology used can also be described as sustainable, pro-climate, pro-environment, green, etc. On the other hand, the Big Data Analytics center can be used to conduct multi-criteria analysis and build multi-faceted simulations of complex climatic, natural, economic, social processes, etc. with the aim of, for example. to develop scenarios of future development of processes observed up to now, to create simulations of continuation in the future of diagnosed historical trends, to develop different variants of scenarios of situation development according to the occurrence of certain determinants, to determine the probability of occurrence of said determinants, to estimate the scale of influence of external factors, the scale of potential materialization of certain categories of risk, the possibility of the occurrence of certain opportunities and threats, estimation of the level of probability of materialization of the various variants of scenarios, in which the potential continuation of the diagnosed trends was characterized for the processes under study, including the processes of sustainable development, green transformation of the economy, implementation of sustainable development goals, etc. Accordingly, the data analytical center built in this way can, on the one hand, be described as sustainable, since it is powered by renewable and emission-free energy sources. In addition to this, the data analytical center can also be helpful in building simulations of complex multi-criteria processes, including the continuation of certain trends of determinants influencing the said processes and the factors co-creating them, which concern the potential development of sustainable processes, e.g. economic, i.e. concerning sustainable economic development. Therefore, the data analytical center built in this way can be helpful, for example, in developing a complex, multifactor simulation of the progressive global warming process in subsequent years, the occurrence in the future of the negative effects of the deepening scale of climate change, the negative impact of these processes on the economy, but also to forecast and develop simulations of the future process of carrying out a pro-environmental and pro-climate transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon zero-growth and closed-loop economy. So, the sustainable data analytical center built in this way will be able to be defined as sustainable due to the supply of renewable and zero-carbon energy sources, but will also be helpful in developing simulations of future processes of green transformation of the economy carried out according to certain assumptions, defined determinants, estimated probability of occurrence of certain impact factors and conditions, etc. orz estimating costs, gains and losses, opportunities and threats, identifying risk factors, particular categories of risks and estimating the feasibility of the defined scenarios of the green transformation of the economy planned to be implemented. In this way, a sustainable data analytical center can also be of great help in the smooth and rapid implementation of the green transformation of the economy.

Kluczowe kwestie dotyczące problematyki zielonej transformacji gospodarki opisałem w poniższym artykule:

IMPLEMENTATION OF THE PRINCIPLES OF SUSTAINABLE ECONOMY DEVELOPMENT AS A KEY ELEMENT OF THE PRO-ECOLOGICAL TRANSFORMATION OF THE ECONOMY TOWARDS GREEN ECONOMY AND CIRCULAR ECONOMY

Zastosowania technologii Big Data w analizie sentymentu, analityce biznesowej i zarządzaniu ryzykiem opisałem w artykule mego współautorstwa:

APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

Topic is ''The most effective AI tool for university students among Chatgpt VS Gemini ai'' and our aim is to find out what is the most effective AI tool for university students.

There are many indications that artificial intelligence technology can be of great help in terms of discovering and creating new drugs. Artificial intelligence can help reduce the cost of developing new drugs, can significantly reduce the time it takes to design and create new drug formulations, the time it takes to conduct research and testing, and can thus provide patients with new therapies for treating various diseases and saving lives faster. Thanks to the use of new technologies and analytical methods, the way healthcare professionals treat patients has been changing rapidly in recent times. As scientists manage to overcome the complex problems associated with lengthy research processes, and the pharmaceutical industry seeks to reduce the time it takes to develop life-saving drugs, so-called precision medicine is coming to the rescue. It takes a lot of time to develop, analyze, test and bring a new drug to market. Artificial intelligence technology is particularly helpful in this regard, including reducing the aforementioned time to create a new drug. When creating most drugs, the first step is to synthesize a compound that can bind to a target molecule associated with the disease. The molecule in question is usually a protein, which is then tested for various influencing factors. In order to find the right compound, researchers analyze thousands of potential candidates of different molecules. When a compound that meets certain characteristics is successfully identified, then researchers search through huge libraries of similar compounds to find the optimal interaction with the protein responsible for the specific disease. In contrast, many years of time and many millions of dollars of funding are required to complete this labor-intensive process today. In a situation where artificial intelligence, machine learning and deep learning are involved in this process, then the entire process can be significantly reduced in time, costs can be significantly reduced and the new drug can be brought to the pharmaceutical market faster by pharmaceutical companies. However, can an artificial intelligence equipped with artificial neural networks that has been taught through deep learning to carry out the above-mentioned processes get it wrong when creating a new drug? What if the drug that was supposed to cure a person of a particular disease produces a number of new side effects that prove even more problematic for the patient than the original disease from which it was supposed to be cured? What if the patient dies due to previously unforeseen side effects? Will insurance companies recognize the artificial intelligence's mistake and compensate the family of the deceased patient? Who will bear the legal, financial, ethical, etc. responsibility for such a situation?

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

Since the release of an intelligent chatbot built on the ChatGPT language model on the Internet in November 2021, the scale of ongoing discussions on the topic of the impact of the development of artificial intelligence technology on labor markets has increased again. Each successive technological revolution has largely generated changes in labor markets. The increase in the scale of automation of manufacturing processes carried out as part of business operations was motivated by the reduction of operational personnel costs resulting from hired personnel. Automation of manufacturing processes, including processes of production and offering services, may also have reduced the level of personnel operational risk. As a result, companies, firms and, in recent years, financial institutions and public entities, through the implementation of ICT, Internet and Industry 4.0/5.0 technologies in various business processes, are improving the efficiency of business processes and increasing the economic profitability of these processes. In each of the previous four technological revolutions, in spite of changing technical solutions and emerging new technologies, analogous processes of using these new technological advances to increase the scale of automation of economic processes worked. In the era of the current fourth or fifth technological revolution, in which a special role is played by the development of generative artificial intelligence technology, applications of this technology in the development of robotics, building autonomous robots, increasing the scale of cooperation between humans and highly intelligent androids is also making a new appearance and another stage of increasing the scale of automation of manufacturing processes. However, what from the point of view of entrepreneurs thanks to the applied new technologies, the achieved automation of production processes is an increase in the efficiency of manufacturing processes, increasing the scale of economic profitability, etc., is, on the other hand, generating serious effects on labor markets, including, among other things, a reduction in employment in certain jobs. The largest scale of applied automation of economic processes and, at the same time, the largest scale of employment reduction was and is generated for those jobs that are characterized by a high level of repetition of certain activities. The activities carried out by employees that are characterized by a high level of repetitiveness were usually the first ones that could be and have been replaced by technology in a relatively simple way. this is also the case today in the era of the fifth technological revolution, in which highly advanced intelligent information systems and autonomous androids equipped with generative artificial intelligence technologies contribute to the reduction of employment in companies and enterprises where humans are replaced by such technology. A particular manifestation of these trends are the group layoffs announced starting in 2022 of employees, including IT specialists in technology companies that the aforementioned advanced technologies of Industry 4.0/5.0 are also creating, developing and implementing into their economic processes carried out in the aforementioned technology companies. Recently, there have been a lot of different kinds of predictive analysis results in the media suggesting which occupations and professions previously performed by people are most at risk of increasing unemployment in the future due to the development of business applications of generative artificial intelligence technologies. In the first months of ChatGPT's release, the Internet was dominated by a number of publications suggesting that a significant portion of jobs in many industries will be replaced by AI technology over the next few decades. Then, after another few months of the development of applications of intelligent chatbots, but also the revelation of many controversies and risks associated with it such as the development of cybercrime and disinformation on the Internet, this dominant opinion began to change in the direction of slightly less pessimistic. these less pessimistic opinions suggest that the technology of generative artificial intelligence does not necessarily deprive the majority of employees in companies and enterprises of their jobs only the majority of employees will be forced to use these new tools, applications, information systems equipped with AI technology as part of their work. Besides, the scale of the impact of new technologies on labor markets will probably not be the same across industries and sectors of the economy.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

I ask this question from the perspective that AI algorithms can automate tasks, analyze vast amounts of data, and suggest new research avenues. It can also improve research efficiency and speed up scientific progress, in addition to analysing massive datasets, it could identify patterns, and accelerate scientific discovery. These no doubt are advantageous benefits, but AI algorithms can also inherit biases from the data they're trained on, leading to discriminatory or misleading results, which directly affect research in terms of the quality of output. Additionally, the "black box" nature of some AI systems makes it difficult to understand how they reach conclusions, raising concerns about transparency and accountability.

Do artificial intelligence applications have a role in developing all types of sports media, audio-visual media, journalism, and digital multimedia?

..

What does LLM and generative AI tell us about language acquisition and language use?

What does LLM and generative AI mean for linguistic theories? For generative grammar or for cognitive construction grammar? For diachronic linguistics and philology?

CMC-Computers, Materials & Continua new special issue“Practical Application and Services in Fog/Edge Computing System”is open for submission now.

📆 Submission Deadline:  31 December 2024

👨‍🎓 Guest Editors

Prof. Hwa-Young Jeong, Kyung Hee University, South Korea

Prof. Neil Y. Yen, University of Aizu, Japan

Prof. Jason C. Hung, Taichung University of Science and Technology, Taiwan

📝 The main topics of this special issue are state-of-the-art technologies and research for practical use or application in the field of fog/edge computing with IoT. Real cases and technical studies in various fields are recruited with fog/edge computing technology, and research cases applied to fog/edge computing with artificial intelligence/deep learning are recruited.

📚 For submission guidelines and details, visit:  https://www.techscience.com/cmc/special_detail/fog_edge-computing

As AI technology, such as ChatGPT, continues to advance, I'm curious about its impact on academic research. How do researchers view the integration of AI tools in their work? Are these tools seen as beneficial for enhancing research productivity and quality, or are there concerns about their influence on the integrity and originality of research? I would appreciate any insights or experiences you could share.

Why all the buzz about AI-assisted writing? Think about it—haven’t we already embraced tools like Grammarly and Quillbot and other AI-assisted and Computer Assisted Writing to help us write better(Wang, 2022)? And remember when we switched from digging through library cards to hopping onto research databases? Evidently, each has advantages and disadvantages (Falagas, 2008). Sure, there was a time when many educators were wary about students using computers for writing, worried it might spoil their writing skills (Billings, 1986) or second language acquisition (Lai, 2006; Gündüz, 2005). But look how that turned out: we adapted and learned to see the value in the technology. So, what's the big deal now? AI writing tools are just the next step. Instead of pushing back, why not dive in, learn how it works, and show others how to use it? Let's make the most of what tech can offer and keep up with the times!

Billings, D. M. (1986). Advantages and disadvantages of computer-assisted instruction. Dimensions of Critical Care Nursing, 5(6), 356-362.

Falagas, M. E., Pitsouni, E. I., Malietzis, G. A., & Pappas, G. (2008). Comparison of PubMed, Scopus, web of science, and Google scholar: strengths and weaknesses. The FASEB journal, 22(2), 338-342.

Gündüz, N. (2005). Computer-assisted language learning. Journal of language and linguistic studies, 1(2), 193-214.

Lai, C. C., & Kritsonis, W. A. (2006). The advantages and disadvantages of computer technology in second language acquisition. Online Submission, 3(1).

Wang, Z. (2022). Computer-assisted EFL writing and evaluations based on artificial intelligence: a case from a college reading and writing course. Library Hi Tech, 40(1), 80-97.

how to establish this idea in to the research?

Dear all,

I would like to publish my papers in a journal. Since it is strongly required to publish the paper in an international journal indexed by Scopus, I face some difficulties due to some fees that must be paid (which is very high) by the author.

My research areas are computer science, artificial intelligence, machine learning, Pattern recognition, natural language processing and Social Media Analytics.

Are there any Scopus-indexed journals without without any article processing charge or other hidden charges for publication and suitable for my research areas?

I would like to thanks for your kind help.

With best regards,

Amit

good greetings

I need references such as books and papers about artificial intelligence in international law.

How far back can we go in history to understanding productivity using AI? Is use of embedded MS Excel functions/formulae or even use of spelling checker in Word.doc a good example of describing the time-frame in terms of early AI? I think AI has just advanced in progression but has been in use for 50 years or more, agree?

Is our productivity really simplified and made economically affordable or we tend to desire learning more and more and getting entangled in even more complications but in a simplified manner? I mean to argue that instead of reducing complications, science prompts us to simplify complications?

Many research institutions have included among the main types of threats and risks developing globally in 2023 the question of the increase in the scale of organized disinformation operating in online social media. The diagnosed increase in the scale of disinformation generated in online social media is related to the use of applications available on the Internet based on generative artificial intelligence technology. With the help of applications available on the Internet, it is possible without being a computer graphic designer and even without artistic skills to simply and easily create graphics, drawings, photos, images, videos, animations, etc., which can represent graphically professionally created “works” that can depict fictional events. Then, with the help of other applications equipped with generative artificial intelligence technology and advanced language models, i.e. with the help of intelligent chatbots, text can be created to describe specific “fictional events” depicted in the generated images. Accordingly, since the end of 2022, i.e. since the first such intelligent chatbot, i.e. the first versions of ChatGPT, were made available on the Internet, the number of memes, photos, comments, videos, posts, banners, etc. generated with the help of applications equipped with tools based on artificial intelligence technology has been growing rapidly, including the rapid increase in the scale of disinformation generated in this way. In order to limit the scale of the aforementioned disinformation developing in online media, on the one hand, technology companies running social media portals and other online information services are perfecting tools for identifying posts, entries, comments, banners, photos, videos, animations, etc. that contain specific, usually thematic types of disinformation. However, these solutions are not perfect, and the scales of disinformation operating in internecine social media are still high. On the other hand, specific institutions for combating disinformation are being established, NGOs and schools are conducting educational campaigns to make citizens aware of the high scale of disinformation developing on the Internet. In addition, proposed regulations such as the AIAct, which as a set of regulations on the proper use of tools equipped with artificial intelligence technology is expected to come into force in the next 2 years in the European Union may play an important role in reducing the scale of disinformation developing on the Internet.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

I was recently asked by LinkedIn to respond to and elaborate on this question, given a post of mine on this subject there. Before I provide my response here on researchgate.net, I wish to ask this question within this forum's context.

There are numerous angles one can take in approaching this critical question which is likely to affect not only Colleges and Universities' built infrastructure, but also their basic functions: teaching and research.

Obviously, there are currently expected future effects in both the short as well as the longer term of Artificial Intelligence upon Higher Education. Hence, the informed and educated views from the academic community are solicited here with this generic type of question. Thank you for your attention.

I would like to start a research from this question

As part of a capstone project, we are a group of graduate students researching innovations (technological or otherwise) that have the potential to transform the business model in American journalism. Our challenge is to propose ideas that make it more financially sustainable without sacrificing public trust. Much of our focus has been on advertising as the adjacent business and we also have been exploring different applications of AI, blockchain, etc., but are hoping to gain more insights generated by "out-of-the-box" thinking.

What innovations have you encountered that you think could help support a unique business like news? We will credit you for any new paths you might set us on!

Thank you.

Among the areas in which applications based on generative artificial intelligence are now rapidly finding application are marketing communication processes realized within the framework of Internet marketing, within the framework of social media advertising campaigns. More and more advertising agencies are using generative artificial intelligence technology to create images, graphics, animations and videos that are used in advertising campaigns. Thanks to the use of generative artificial intelligence technology, the creation of such key elements of marketing communication materials has become much simpler and cheaper and their creation time has been significantly reduced. On the other hand, thanks to the applications already available on the Internet based on generative artificial intelligence technology that enable the creation of photos, graphics, animations and videos, it is no longer only advertising agencies employing professional cartoonists, graphic designers, screenwriters and filmmakers that can create professional marketing materials and advertising campaigns. Thanks to the aforementioned applications available on the Internet, graphic design platforms, including free smartphone apps offered by technology companies, advertising spots and entire advertising campaigns can be designed, created and executed by Internet users, including online social media users, who have not previously been involved in the creation of graphics, banners, posters, animations and advertising videos. Thus, opportunities are already emerging for Internet users who maintain their social media profiles to professionally create promotional materials and advertising campaigns. On the other hand, generative artificial intelligence technology can be used unethically within the framework of generating disinformation, informational factoids and deepfakes. The significance of this problem, including the growing disinformation on the Internet, has grown rapidly in recent years. The deepfake image processing technique involves combining images of human faces using artificial intelligence techniques.

In order to reduce the scale of disinformation spreading on the Internet media, it is necessary to create a universal system for labeling photos, graphics, animations and videos created using generative artificial intelligence technology. On the other hand, a key factor facilitating the development of such a problem of generating disinformation is that many legal issues related to the technology have not yet been settled. Therefore, it is also necessary to refine legal norms on copyright issues, intellectual property protection that take into account the creation of works that have been created using generative artificial intelligence technology. In addition to this, social media companies should constantly improve tools for detecting and removing graphic and/or video materials created using deepfake technology.

I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

I have come across some ideas which I hope will be pursued by academics in the associated disciplines:

1) Topics Broadly outlined in the following articles

Fathabadi OS (2022) Voluntary Selection; Bringing Evolution at the Service of Humanity. Scientific J Genet Gene Ther 8(1): 009-015.DOI: http://dx.doi.org/10.17352/sjggt.000021

Fathabadi OS (2023) The way of future through voluntary selection. Glob J Ecol 8(1): 034-041. DOI: 10.17352/gje.000079

2) Explanation of how violence is the link between evolution and society. What is not clear in the articles above is that just as a disease shows symptoms such as fever in its early stages, violence that is caused by the lack of evolutionary order in society also shows itself in the form of problems like bullying, harassment, discrimination, passive aggression, coercive control, etc and then It may appear in the form of an increase in the rate of crimes and social riots and finally in the form of naked violence, civil wars, genocides and foreign wars. The purpose of the topics raised in both articles is to realize the evolutionary order through the methods proposed in control engineering and by achieving the desired statistical goals, not only to prevent violence, but also to spread satisfaction in the society and to provide internal and external security.

3) Interpretation of historical events including genocides and world wars through the lens of insights provided above for example how passive aggression became widespread prior to such events.

4) The articles above argue that Control Theory, in conjunction with data science, can help establish and maintain democracies with an unprecedented level of stability and provide optimal levels of living standards by regulating evolutionary health of societies and the relationships between them. This goal however, requires interpretation of the theory widely used in engineering, for application in Humanities. Control Engineering remains a rather challenging field to learn and its theoreticians and practitioners are mostly active in areas other than humanities - most critically politics - and even despite the large number of engineering graduates receiving education in Systems and Control Theory as part of their curriculum, the specific practical pathway for application of the theory for solving problems in Humanities remains rather unclear; let alone the inaccessibility of the field to the practitioners of humanities even to the extent necessary to allow them to express the problems in terms approachable by control engineering experts. Projects should therefore be defined to develop highly targeted educational materials and tools which provide a shortcut to applying the theory in solving practical problems in humanities. It is particularly important to understand that the type of Control Theory applicable to Humanities would be "Non-Linear Time-Varying Control" which is an extension of control Theory as relevant to most engineering problems and as such, the specific theory will need to be developed specifically beyond what a classically educated expert in Control Engineering would be comfortably equipped with even if educated with a PhD. For example the types of time constants and uncertainties relevant in Humanities and the types of irregularities which can be created by collective mis-intentions of social groups as well as moral aspects of implications of such techniques on human population will extend to matters associated in politics, biology, culture, education, and media. Actually it is important to understand that the knowledge and tools, will not act as a pill to fix problems but through insights, they provide directions and "Decision Support Systems" with local applicability and temporal relevance which despite their limitations, will provide unprecedented powers for providing better living standards for all populations and individuals. Such tools need to be maintained in order to remain relevant to the changes in the system under control and time. The developed materials will help students, researchers and practitioners get started and up to speed with the expertise through minimal training or self-study and the impact I believe would be revolutionary. In addition to Systems and Control Theory, the mentioned books/educational materials/tools may also cover topics such as Programming, Differential Equations, Numerical Optimisation, System Identification, Artificial Intelligence and to some extent Statistics. The set of these topic may one day help establish an independent field of study namely "Humanities Engineering".

5) Applications of the theory, educational materials, and tools mentioned above, to solve practical problems associated in sociology, psychology, politics and other fields of humanities is the ultimate goal and such projects make great topics for research in universities, Think tanks, and governments. It is important to mention that using the mean-values and standard deviations defining phenotypic profiles of populations is a way of taking into account the differences of different populations in achieving desirable results within them and in regulating the relationship between them.

6) It is also possible to characterise discourses, and broadcasted contents by defining relevant indices that quantify various aspects of them and then model and predict their relationship with the outcomes in society. These models can then act as decision support systems to identify and implement adjustments for achieving the desired social outcomes. If sufficiently predictive, they can also be used in combination with other models or in isolation as part of the control loops associated in Control Theory in order to achieve the desired outcomes in terms of sustainability, social stability, freedoms, economic welfare, health, national security, psychological security, gender equality, and optimal levels of happiness in all individuals and social groups, etc.

7) It is possible to compile a set of contents including matters mentioned in the articles above, to act as a mental anchorage for people. Something that is scientifically proven, convincing and understandable by those who put in the effort and allows them to remain motivated, morally directed, socially responsible and supported and mentally healthy. I believe adding a content starting from Genetics explaining how "Life is a complex Product of Nature" and how "Survival and Reproduction are Complex Interpretations of Laws of Nature" is necessary. Topics such as cosmology and Quantum Physics can also be included.

8) It is possible to define a project on optimal forms of democracy for different populations with emphasis on the fact that peoples' choices represent their interests as they understand them as individuals while much of what comprises our existing living standards or is necessary for achieving higher standards of living are a result of societies and mechanisms maintaining them. Societies were formed by cultures/religions as an aftermath of painful evolutionary events which occurred when people pursued their personal interests and emerged as optimal ways of achieving a better average standard of living for larger numbers of individuals over a larger proportion of their lives. In other words, many aspects of our existing living standards are by-products of societies and could not be achieved or maintained only pursuing our individual choices which is what a democracy guarantees. Democracies should be pursued for optimum living standards and preventing abuse however, it is necessary to have democracies in place to guarantee the maintenance of society itself (what you can call an evolutionary order) and realise/maintain its desired levels of standards of living and this should not be compromised by the choice of individuals.

9) Ethics of Voluntary Selection and application of methods concerned in Control Theory and AI in solving problems in Humanities specially to prevent abuse of individuals, and minorities under the flag of interests of society and to prevent creating senseless scientific approvals for imposing disadvantage on individuals and social groups. It is also necessary to minimise pain imposed on individuals and social groups in transitions as a result of adjustments.

10) While the first article introduces the concept of "Voluntary Selection" and a methodology to use it in a calculated way, it only acts as a beginning and if it is going to be implemented, a huge methodological and experimental effort is needed for identifying relevant phenotypes, developing phenotypic maps for distinct populations, identifying the results when choosing donor and receiver populations, and developing tools to predict and monitor the progress of such programs besides studying the implications for society, economy and beyond. Research can also dig deeper and take into account genotype-phenotype relationships in achieving the desired results.

One of the new technologies that has been thoroughly discussed is AI in general and ChatGPT in specific. How do you see its role in teaching and learning in terms of benefits and disadvantages? What are the models to integrate such innovations in your instruction? How do you see the future trends and beliefs of faculty members in this domain?

Regarding Turing's proposal to follow the example of the development of intelligence in humans and apply it to machines. Specifically, the example of a child who, in addition to learning discipline, needs to learn the spirit of initiative and decision-making. Could this kind of intelligence be compared to the case of a simple machine, or what Turing called the “child machine,” which is provided with basic instructions that enable it to learn and make its decisions later?

The Legal Impact of AI development on business and rural society in the Asia-Pacific and ASEAN region is at a crossroads. How will AI impact the local community (urban and rural) now?

As a student in Bachelor degree program in computer science field we have a project in course of "Language Theory", our project related with Natural Language Processing:

- First phase talks about giving a dictionary of "Physical Objects Name's" and give it a "Text" (all this in input) after that it gives us a list of "Physical Objects Name's" in our "Text" (this is the output as a file).

- Second phase is to use the last list to as input and implement a code that can classify words by topics and the result will be the general topic or idea of our text.

In this project I did the first phase but in the second one I don't understand how can I implement my code.

P.S: I try to add a python file but I can't, so for all those who wanna help me I can send them my work.

I have 293 (at the moment) videos of artificial intelligence system:

How do I make automatic annotation of videos in Russian?

Even though Saeedi, Logothetis et al. (2024) have concluded that visual illusions are a product of extrastriate rather than striate mechanisms (based on neural response latencies of illusions versus real-images as well as the optogenetic silencing of the object-encoding area of extrastriate cortex), we suspect that ultimately the creation of the mismatch is due to a discrepancy between the efference-copy representation stored in the cerebellum (perhaps going back to the time of development) and the real-world representations contained in the cortical sensory systems (Tehovnik, Hasanbegović, Chen 2024). The reason for this is that the cerebellum, with its disproportionate number of neurons (Herculano-Housel 2009), is the structure whose job it is to put all the senses in register with the motor system. For example, Hebb (1969) observed that a subject donning a prism that bent an otherwise straight line eventually adapts such that if asked to draw a straight line by hand, for example, the line to an outside observer would be deemed straight even though initially (before adaptation) this line appeared curved to the subject wearing the prism. That the cerebellum is necessary for prism adaptation as well as other types of sensory-motor realignments is well accepted (Bell, Sawtell et al. 2008; Braizer and Glickstein 1973,1999; Gallistel et al. 2022; Gilbert and Thach 1977; Giovannicci et al. 2017; Guell et al. 2018; Heun et al. 1999; Ito 2008; Kitazawa et al.1998; Miles and Lisberger 1981; Robinson 1981; Soetedjo and Fuchs 2006; Soetedjo et al. 2008; Smaers et al. 2018; Swain et al. 2011; Thach et al. 1992). It is this re-alignment that permits for highly automated acts to be executed precisely and at the shortest latencies by all vertebrates. Indeed, in the 14th Century, Pope Benedict XI set out to have the wall of St. Peter’s cathedral remodeled. To accomplish this, applicants were required to submit their art, but Giotto di Bondone (1267-1337) did not have any art to submit, so he took out a sheet of paper upon which he drew a perfect circle. Today in Tuscany this circle is known as ‘The round O of Giotto’ (Schiller and Tehovnik 2015). Without the cerebellum, Giotto’s circle would not have been precisely round, a perspective to have by anyone remodeling a building.

I heard on television a famous professor of ethics speaking about the rights of intelligent machines. There are no intelligent machines and there is no artificial intelligence. Machines function in the way people designed and programmed them to function. A discourse bout intelligent machines leads into a totalitarian society, in which people will succumb to what machines say. And machines will say what power-holders ordered to programmers to program them to say and do.

I graduated computer science; I am now retired and I regret the fact that I spent my career teaching something what now leads people into a mental and physical slavery.

Production logistics management in a manufacturing company is currently one of the key areas of business management that significantly affects the level of technical and organizational efficiency of business operations. The change in the level of technical and organizational efficiency of business operations also usually has a significant impact and correlates with the issue of business efficiency and affects the financial results generated in the business entity. Among the key segments of logistics in the enterprise are also internal production logistics, on the way of organization of which the efficiency of the operation of production processes and the efficiency of the enterprise also largely depends. In recent years, more and more companies and enterprises have been optimizing production logistics through the implementation of information systems and automation of individual operations in the process. Production logistics is mainly concerned with ensuring the optimal flow of materials and information in the process of producing all types of goods. Production logistics does not deal with the technology of production processes, but only with the organization of the production system together with the storage and transport environment. Production logistics is mainly concerned with the optimization of all operations related to the production process, such as: supplying the plant with raw materials, semi-finished products and components necessary for production; transporting items between successive stages of production; and transferring the finished product to disposal warehouses. Precisely defining optimal production logistics is a lengthy process, requiring analysis and modification of almost every process taking place in a company. One of the key factors in the optimization of production logistics is the reduction of inventory levels and their adjustment to the ongoing production process. This translates directly into a decrease in storage costs. Effective management of production logistics should ensure timely delivery, while maintaining high product quality. Effective production logistics management can be supported by the implementation of new Industry 4.0/5.0 technologies, including Big Data and generative artificial intelligence.

The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best wishes,

Dariusz Prokopowicz

PhD student

I have 293 (at the moment) videos of artificial intelligence system:

How do I make automatic annotation of videos in Russian?

I have participated in trainings whose organizers advertised on social media and during which they first presented their achievements in social media, pointed out the large income they generate within the framework of large reach in these online media, then talked about social media, marketing and online advertising used in these media, the possibility of using various applications based on artificial intelligence technology within the framework of marketing activities, creating and running advertising campaigns in social media and then presented their paid offers to gain access to these applications through created additional overlays, intermediary platforms, websites. Such training courses, webinars are usually free of charge. After the training, participants can receive free certificates confirming their participation in the training. This is a free additional form of incentive to participate in the training. On the other hand, among the forms of encouraging the purchase of access to specific AI applications is a promotional offer that lasts until the end of the training time and/or until the end of the day. however, it happens that the people conducting this type of training are not computer scientists who create AI applications, they are influencers, youtubers who have contrived to sell access to selected applications based on artificial intelligence technology, which for a certain fee will be available on created overlays, websites that act as intermediary applications to access specific source applications that are available for free on the Internet. In addition, it happens that those who conduct this kind of training do not even have a registered business and cannot even issue a VAT invoice for the services sold in this way in mediating access to selected AI applications. Surprisingly, the tax authorities in the various countries where such youtubers operate have not yet addressed this issue, given that some unethical individuals operating in this way boast about the high income they earn during such training sessions. It can be a problem of sorts for public tax authorities operating in individual countries if this kind of training and business activity is conducted via the Internet from other countries, which can be a kind of tax haven for this kind of activity. However, the problem can be serious if this kind of activity is conducted from a country referred to as a tax haven and is aimed at citizens of other countries. Apparently, there is still a lack of legal regulations that would effectively limit the use of unethical, unreliable business practices in the use of certain solutions based on artificial intelligence.

I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:

In view of the above, I address the following question to the esteemed community of scientists and researchers:

What do you think about this topic?

What is your opinion on this issue?

Please answer,

I invite everyone to join the discussion,

Thank you very much,

Best regards,

Dariusz Prokopowicz

We see that the world is in disarray and there is no meaningful global cooperation. Nation states keep warring at an increasing rate with more intensity. None of our problems are solved and things just keep getting worse and they add new existential threats like artificial intelligence to the mix. How could anyone think that AI can be kept under control at such an environment bogs my mind. There is competition instead of collaboration, there is war, and there are no principles. UN is a total sham as can be seen once again in the example of Palestine/Israel. What good is a regulation then?

As AI detection improves, so will AI generation of text? Should we be defeatist?

Artificial intelligence

AI in research offers tremendous potential, but ethical considerations are crucial. Biases in data or algorithms can lead to discriminatory or unfair results. The "black box" nature of some AI models makes it difficult to understand their reasoning, raising concerns about accountability. Ensuring data privacy, transparency in research methods, and maintaining human oversight are all essential for ethical AI-powered research.

The frequent question that will AI excessive use reduce novelty? Is an interesting perspective.

Depending on AI too heavily can indeed lead to concerns about reduced innovation or novelty, as machines tend to optimize for efficiency and predictability rather than creativity. AI often works by analyzing existing data and patterns, which means it can sometimes perpetuate the status quo rather than generate new ideas.

Using AI as a tool to augment human creativity and decision-making, rather than replace it, could be a more balanced approach. This way, humans can leverage AI’s processing power and data analysis capabilities while still driving innovation with human creativity and intuition.

What do you think could be done to maintain a good balance between using AI and preserving human-driven innovation?

In recent years, more and more perfect robots equipped with artificial intelligence have been developed. New generations of artificial intelligence and/or machine learning technologies, when equipped with software that enables the creation of unique works, new creations, creative solutions, etc., can create a kind of artwork in the chosen field of creativity and artistry. If we connect a 3D printer to a robot equipped with an artificial intelligence system that is capable of designing and producing beautiful sculptures, can we thus obtain a kind of work of art?

When a robot equipped with an artificial intelligence system paints beautiful pictures, can the resulting works be considered fully artistic works of art?

If NO, why not?

And if YES, then who is the artist of the works of art created in this way, is it a robot equipped with artificial intelligence that creates them or a human being who created this artificial intelligence and programmed it accordingly?

What is your opinion on this topic?

What do you think about this topic?

Please reply,

I invite you all to discuss,

Thank you very much,

Best regards,

Dariusz Prokopowicz