Kind Of Intelligence Research Articles

Multiple Intelligence

There are maniple ways of learning and there are many of receiving information asl expression ourselves. Careener introduced and also defined different kinds of intelligence. Multiple intelligence box significant relationship with student achievement. Academicwheelmen needs understanding of concepts, remembering and presenting those concepts correctly @rough examinations. For this, rigidness of the curriculum has to be removed.

A Comprehensive Machine Learning Approach for Advanced Vehicle Detection and Counting

The exponential rise of urban areas and the associated surge in transportation congestion. Consequently, this study offers a thorough method for vehicle recognition and counting via the use of machine learning, as well as an effective system for real-time traffic monitoring, with the aim of reducing traffic. The first step is to develop a model that can identify and follow moving cars in still photos or video. This research delves into the topic of teaching a computer to count automobiles using machine learning, a kind of artificial intelligence. The purpose of this study is to provide a computational model for intelligent vehicle detection and tracking at a given location and time of day, using real-time images of passing cars. This approach uses OpenCV to evaluate the model's car detection and counting capabilities, and convolutional neural networks (CNNs) for object recognition and classification. The techniques laid the groundwork for early improvements, which were often enhanced using machine learning classifiers such as random forests and support vector machines (SVMs). To automate the process and get useful information regarding traffic patterns and management.

Runtime Verification-Based Safe MARL for Optimized Safety Policy Generation for Multi-Robot Systems

The intelligent warehouse is a modern logistics management system that uses technologies like the Internet of Things, robots, and artificial intelligence to realize automated management and optimize warehousing operations. The multi-robot system (MRS) is an important carrier for implementing an intelligent warehouse, which completes various tasks in the warehouse through cooperation and coordination between robots. As an extension of reinforcement learning and a kind of swarm intelligence, MARL (multi-agent reinforcement learning) can effectively create the multi-robot systems in intelligent warehouses. However, MARL-based multi-robot systems in intelligent warehouses face serious safety issues, such as collisions, conflicts, and congestion. To deal with these issues, this paper proposes a safe MARL method based on runtime verification, i.e., an optimized safety policy-generation framework, for multi-robot systems in intelligent warehouses. The framework consists of three stages. In the first stage, a runtime model SCMG (safety-constrained Markov Game) is defined for the multi-robot system at runtime in the intelligent warehouse. In the second stage, rPATL (probabilistic alternating-time temporal logic with rewards) is used to express safety properties, and SCMG is cyclically verified and refined through runtime verification (RV) to ensure safety. This stage guarantees the safety of robots’ behaviors before training. In the third stage, the verified SCMG guides SCPO (safety-constrained policy optimization) to obtain an optimized safety policy for robots. Finally, a multi-robot warehouse (RWARE) scenario is used for experimental evaluation. The results show that the policy obtained by our framework is safer than existing frameworks and includes a certain degree of optimization.

Research and Review on Chatbots in Digital Mental Health

In recent years, with advanced technology, various kinds of artificial intelligence (AI) applications in different domains are booming. However, chatbots in the field of digital mental health are still in their early stages and have not yet been widely adopted. Since peoples psychological problems have become increasingly prevalent in society, and many have not been handled, this paper provided comprehensive research and review on the necessity and potential for AI to address the psychological issues faced by the Chinese population through a questionnaire investigation. The questionnaire investigation aimed to gather information on people's attitudes towards using chatbots in digital mental health as a solution. The responses were collected from diverse age groups of participants, including both males and females and varying provinces of residence in China. Overall, the results of the questionnaire investigation showed the possible future of this kind of chatbot among Chinese people.

The Role of Threat Intelligence in Enhancing Cybersecurity Posture

Organizations confront more complex and persistent cyberattacks in the quickly changing cyber threat landscape of today. Through the provision of actionable insights on emerging threats, adversary tactics, and vulnerabilities, cyber threat intelligence (CTI) becomes an increasingly important component in strengthening the cybersecurity posture of organizational networks. The importance of CTI and its useful uses in enhancing cybersecurity defences are examined in this research study. It explores the several kinds of threat intelligence, methods for compiling and evaluating threat information, and proactive steps that businesses may take to make the most of CTI. This study emphasizes the significance of incorporating CTI into cybersecurity plans to more effectively identify, prevent, and respond to cyber attacks through a thorough review of industry practices and case studies. Organizations may improve their defences against cyberattacks and enhance vital assets and data by comprehending the role that CTI plays in cybersecurity.

The Relationship of Stimulation Implementation with Developmental Abilities in Pre-school Age Children

Preschool period to be a conducive period for developing various kinds of abilities, intelligence, talents, physical, cognitive, language, emotional and spiritual abilities in children. One of the factors that has a big influence in supporting children's development is the stimulation factor. The purpose to analysis the relationship application of stimulation to the developmental abilities with pre-school children. The research design is quantitative with a correlational descriptive method using a cross sectional study approach. This research used 242 respondents who were mothers of pre-school children aged 48-72 months and who were actively participating in kindergarten education. The research results showed that the application of developmental stimulation had been carried out well in 51.2% of respondents. Children's developmental abilities, 62% of children have appropriate developmental abilities, 28.9% of children have doubtful developmental abilities and 9.1% of children have the possibility of deviations in their development. From the results of statistical tests using the chi square test, it was found that the value of p = 0.000 < α 0.05 was statistically significant, so there was a significant relationship between the application of child development stimulation to the developmental abilities of pre-school aged children.

ChatGPT vs UpToDate: comparative study of usefulness and reliability of Chatbot in common clinical presentations of otorhinolaryngology–head and neck surgery

PurposeThe usage of Chatbots as a kind of Artificial Intelligence in medicine is getting to increase in recent years. UpToDate® is another well-known search tool established on evidence-based knowledge and is used daily by doctors worldwide. In this study, we aimed to investigate the usefulness and reliability of ChatGPT compared to UpToDate in Otorhinolaryngology and Head and Neck Surgery (ORL–HNS).Materials and methodsChatGPT-3.5 and UpToDate were interrogated for the management of 25 common clinical case scenarios (13 males/12 females) recruited from literature considering the daily observation at the Department of Otorhinolaryngology of Ege University Faculty of Medicine. Scientific references for the management were requested for each clinical case. The accuracy of the references in the ChatGPT answers was assessed on a 0–2 scale and the usefulness of the ChatGPT and UpToDate answers was assessed with 1–3 scores by reviewers. UpToDate and ChatGPT 3.5 responses were compared.ResultsChatGPT did not give references in some questions in contrast to UpToDate. Information on the ChatGPT was limited to 2021. UpToDate supported the paper with subheadings, tables, figures, and algorithms. The mean accuracy score of references in ChatGPT answers was 0.25–weak/unrelated. The median (Q1–Q3) was 1.00 (1.25–2.00) for ChatGPT and 2.63 (2.75–3.00) for UpToDate, the difference was statistically significant (p < 0.001). UpToDate was observed more useful and reliable than ChatGPT.ConclusionsChatGPT has the potential to support the physicians to find out the information but our results suggest that ChatGPT needs to be improved to increase the usefulness and reliability of medical evidence-based knowledge.

Optimal Scheduling Strategy of Wind–Solar–Thermal‐Storage Power Energy Based on CGAN and Dynamic Line–Rated Power

This paper introduces a new way to plan and manage the use of wind and solar power, along with traditional thermal power (TP) and batteries, to get the most environmental and economic benefits. It uses a special kind of artificial intelligence, called conditional generative adversarial networks (CGAN), to predict how much power wind and solar sources will produce. Subsequently, it takes into account the dynamic line–rated power (DLRP) in order to determine the dynamic transmission capacity of lines associated with wind and solar power generation. The primary objectives are to reduce the operating costs of TP plants, maximize the utilization of wind and solar energy, minimize power deviations in electricity transmission, and enhance revenue from electricity transmission. To solve this complex problem, the paper uses a smart method to simplify the model, making it possible to find solutions with CPLEX. Tests on a small network with six nodes show that this approach not only saves money but also makes better use of clean energy sources.

An Ethic of Military Uses of Artificial Intelligence: Sustaining Virtue, Granting Autonomy, and Calibrating Risk

Artificial intelligence in military operations comes in two kinds. First, there is narrow or specific intelligence – the autonomous ability to identify an instance of a species of target, and to track its changes of position. Second, there is broad or general intelligence – the autonomous ability to choose a species of target, identify instances, track their movements, decide when to strike them, learn from errors, and improve initial choices. These two kinds of artificial intelligence raise ethical questions mainly because of two features: the physical distance they put between the human agents deploying them and their targets, and their ability to act independently of those agents. The main ethical questions these features raise are three. First, how to maintain the traditional martial virtues of fortitude and chivalry while operating lethal weapons at a safe distance? Second, how much autonomy to grant a machine? And third, what risks to take with the possibility of technical error? This paper considers each of these questions in turn.

Emotional Intelligence As an Object of Psycholinguistic Research

The purpose of research is to conduct a theoretical psycholinguistic analysis of the phenomenon of "emotional intelligence", and to answer the following questions: 1) if emotional intelligence can be considered a syncretic psychological phenomenon or is it just a kind of general intelligence; 2) how and when emotional intelligence is formed in the process of ontogenesis; 3) to what extent the level of formation of emotional intelligence correlates with the level of development of speech ability.Methods. On the basis of L.S. Vygotsky's theory of speech activity, cognitive, constructivist theories of language ontogenesis, in particular, the theory of phasing and continuity of speech and cognitive development, a descriptive and comparative analyses of the models of emotional intelligence of Mayer-Salovey-Caruso, Goleman, Reuven Bar-On and the model of emotional literacy of Steiner is carried out. From the standpoint of modern psychology and psycholinguistics, the process of forming the abilities that make up the essence of the phenomenon of emotional intelligence is analyzed.The results. The considered models allowed us to identify a phenomenological core – emotions and their manifestations – that coincides in all. All models assume a priori the presence of abilities to perceive, control and understand their own emotions and emotional states and those in other people. It is proved that these abilities have continuity and are formed in the complex of all social interactions of the child in parallel with cognitive and speech development. The matter of the syncretic nature of the phenomenon of emotional intelligence is dismissed.Conclusion. Emotional intelligence is not a separate psychological education, but serves as a marker of the development of the cjgnitive functions, it is a "by-product" of the cognitive, speech and mental development of the child in the norm.

Societal's Attitude Towards the Essential of English for the Tourism Sector: Expectations and Actions

English is essential for national development involving the tourism sector. Unfortunately, it just serves as a foreign language in Indonesia, resulting in low speaking performance. This study observed stakeholders' and community's efforts to boost English-speaking fluency in the tourism object zone. It was a qualitative case study through interviews, document analysis, and photos in collecting the data. The research was done in Tana Toraja and Bulukumba regency of South Sulawesi province by involving stakeholders. The findings show that Stakeholders and local society are regularly active in training on the use of English for Specific Purposes (ESP), such as English for tour guides, hotel services, selling handicrafts, etc. Stakeholders also introduce and train the use of various kinds of Artificial Intelligence to improve English skills, such as "Google translation". The government localized a village which was named "Tourism English Village," where the local people try to speak English as much as possible. This study contributes to the second language acquisition acceleration in foreign language countries and promotes some tourism object zones in Indonesia..

Classification of cyclones using machine learning techniques

In this article, we provide a method for identifying and categorizing cyclones, both tropical and extratropical. The method is designed with the goal of producing a global labeled dataset for cyclones, and it is based on a set of rigorous criteria. The heuristics are defined from date, time, pressure, wind speed, wind directions, latitude and longitudes. Numerous researchers have confirmed that machine learning, a kind of artificial intelligence, can offer a fresh approach to overcoming the limitations of cyclone classification, whether employing a pure data-driven model or enhancing numerical models with machine learning. This article introduces progress based on machine learning in genesis classification, track records, intensities, and extreme weather forecasts associated with tropical as well as extratropical cyclones (such as strong winds and rainstorms and their disastrous impacts). The challenges of cyclones in recent years and successful cases of machine learning methods in these aspects are summarized and analyzed.

Applying AI in the Healthcare Sector: Difficulties

Artificial intelligence (AI) broadly speaking refers to any behavior shown by a computer or system that is similar to that of a person. Computers can learn from data without explicit human programming thanks to a kind of artificial intelligence known as &amp;quot;machine learning&amp;quot;. The application of artificial intelligence (AI) technologies in medicine is one of the most important current trends in global healthcare. Artificial intelligence-based technologies are radically changing the global healthcare system by allowing for a drastic rebuilding of the medical diagnostics system and a corresponding decrease in healthcare costs. Prior to beginning treatment, an illness must be classified into which class of disorders it belongs. It is possible to classify the disease kind according to the feature space of the ailment. Machine learning algorithms can help with this problem.

Development of a “Smart Dry Port” Indicator and Ranking Calculation for Spanish Dry Ports

The objectives set in the 2030 agenda gravitate towards the concept of sustainability, a concept that is closely related to the efficiency of port operations. As a direct derivative of the search for more efficient logistics and port operations, a disruption of new technologies, associated with the term ‘Smart’, is making its way with a large range of new digital applications. The logistics and port sector is also undergoing a process of transition towards this kind of operational intelligence through digitized and increasingly automated devices. In this work, an analysis of the most relevant Spanish dry ports is carried out, with the clear objective of discovering their degree of adaptation to the ideal Smart concept. This was developed through the implementation of a descriptive statistical analysis and a Delphi methodology, a battery of indicators and measurement variables that classify, in an integral and objective way, the degree of the adaptation of these ports to the concept of the ideal Smart Dry Port; in this way, we obtained a ranking of the ports. The current and future trend of this type of Smart facilities is solid and clearly points towards a greater digitalization of port processes and an openness of information, with port facilities interconnected with each other through automated processes. The analysis gives a clear picture of the adaptation to digitalization and automation of three of the largest Spanish dry ports, in which there are ongoing efforts to adapt to this concept but for which there is still a long way to go.

Preface

The 2023 2nd International Conference on Electronics Technology and Artificial Intelligence (ETAI 2023) took place during August 18th to 20th, 2023 in Changsha, China (hybrid form). ETAI exists as an international annual conference which tries to meet the needs for various kinds of electronics technology and artificial intelligence and has been established as a high-quality international conference.The Conference took “bringing together global wisdom in scientific innovation to promote high-quality development” as the theme. It encouraged the exchange of information on research frontiers in different fields, connected the most advanced academic resources at home and abroad, and turned research results into industrial solutions. It also promoted the development of the fields related to electronics technology and artificial intelligence, expanded the international scientific and academic exchange channels, enhanced scientific innovation on a global scale, and contributed to academic cooperation between China and the international community.The Conference was attended by about 50 participants and hosted 3 keynote speeches, several oral presentations as well as poster presentations. The 2nd ETAI covered various research fields where electronics technology and artificial intelligence are used, such as Power Electronics Technology, Integrated Circuit Design and Integrated Systems, Advanced Electromagnetics, Artificial Intelligence Modeling and Simulation, Intelligent and Artificial Intelligence Control, etc.According to all attendees, the scientific program was excellent with high level of presentations and the scientific environment was fruitful, thus all attendees had a great and creative time. Among them, Prof. Jahangir Hossain (University of Technology Sydney, Australia) first performed a keynote speech. He mainly focuses his study on areas of Power Systems, Wind Generator Integration and Stabilization, Voltage Stability, Micro Grids, Robust Control, etc. Besides, he has published more than 300 articles in international refereed journals and conferences which attracted more than 7100 citations (Google Scholar) with H-index 44. Prof. Bing Shi (Wuhan University of Technology, China), whose research fields cover artificial intelligence and multi-agent systems, also made a keynote report. With rounds of dramatic researches sharing and ideas exchanging, the Conference was made filled with strong academic atmosphere.We would like to thank our host and sponsor for providing their excellent organization and support for the needs of the Conference. We would also like to thank the members of the Organizing Committee as well as the members of the Technical Program Committee. Our gratitude also goes to Journal of Physics: Conference Series for its support in publishing this volume.The Committee of ETAI 2023List of Committee Member are available in the pdf.

Linguistic mastery: Advances in natural language processing

NLPstands for Natural Language Processing, it is a kind of artificial intelligence. That demonstrate with scrutinize, understanding, and accuse natural human languages. In such a manner that analog procedure would get in touch and human language excluding computer-propel language like programming language such as c, c++, python, javascript. NLP field contains the intellect computer programming into an understanding language which is understandable by humans. So, powerful algorithms can even interpret one language into another language scrupulously. Natural language processing occasionally also known as computational linguistics, it uses semantics and syntax. It assists computers to acknowledge how humans talk or write and also it will know how to deduce meaning of words that they are saying. A language is designate as a synchronize of rules and symbols. These Symbol are amalgamated and used for disseminate the data as well as make contact to other resources. Symbols are potentiate by the rules and regulations.

From industrialised to mindful medicine: including the politics of need and trust in child psychiatry

SUMMARYDiagnostic systems are not conducive to compassionate health-bringing psychiatric treatment. The systems were built around the fallacy that the politics of biomedicine could be reliably applied to the emergent properties of human psychological suffering and enable diagnosis-specific treatment packages. The resulting industrialised medicine, which reified people, failed to facilitate the compassion needed for healing. This article outlines an approach to psychiatric practice that involves understanding children's suffering and vulnerabilities in terms of their attachment strategies and adaptation to their context and takes a mindful approach to developing compassionate collaborative treatment goals (intelligent kindness). A shift towards mindful psychiatric medicine would encourage politicians to serve the people by addressing the contexts associated with human suffering and what makes people vulnerable, especially social inequalities. Healthy societies in which the psychiatric dis-ease of the population is adequately addressed will not be built with limited biomedical understanding of dis-ease.

Artificial Intelligence

Artificial Intelligence is the way one can solve problems occurring in everyday life. A lot of mathematical solutions are presented as to how one learns and the way one should learn to give rise to some kind of intelligence. Deep learning is an example of this [1]. Problems occur everywhere from mathematics to computer science. Intelligence is needed to solve problems. This paper is about that. It presents a simple method or way to solve problems intelligently. The next heading describes as to how one could solve problems in an intelligent manner.

“Everyone freaks out when the leaks are made”: data leaks, investigative journalism and intelligence practice

PurposeThis paper aims to examine the history of data leaks and investigative journalism, the techniques and technology that enable them and their influence in Australia and abroad. It explores the ethical and professional considerations of investigative journalists, how they approach privacy and information-sharing and how this differs from intelligence practice in government and industry. The paper assesses the strengths and limitations of Collaborative Investigative Reporting based on Information Leaks (CIRIL) as a kind of public-facing intelligence practice.Design/methodology/approachThis study draws on academic literature, source material from investigations by the International Consortium of Investigative Journalists and the Organised Crime and Corruption Reporting Project, and a survey of financial crime compliance professionals conducted in 2022.FindingsThe paper identifies three key causal factors that have enabled the rise of CIRIL even as traditional journalism has declined: the digital storage of information; increasing public interest in offshore finance and tax evasion; and “virtual newsrooms” enabled by internet communications. It concludes that the primary strength of CIRIL is its creation of complex global narratives to inform the public about corruption and tax evasion, while its key weakness is that the scale and breadth of the data released makes it difficult to focus on likely criminal activity. Results of a survey of industry and government professionals indicate that CIRIL is generally more effective as public information than as an investigative resource, owing to the volume, age and quality of information released. However, the trends enabling CIRIL are likely to continue, and this means that governments and financial institutions need to become more effective at using leaked information.Originality/valueOver the past decade, large-scale, data-driven investigative journalism projects such as the Pandora Papers and the Russian Laundromat have had a significant public impact by exposing money laundering, financial crime and corruption. These projects share certain hallmarks: the use of human intelligence, often sourced from anonymous leaks; inventive fusion of this intelligence with data from open sources; and collaboration among a global collective of investigative journalists to build a narrative. These projects prioritise informing the public. They are also an important information source for government and private sector organisations working to investigate and disrupt financial crime.

Prevention of surgical site infections: a personal odyssey

Prevention of surgical site infections: a personal odyssey