Search results for: legal artificial intelligence

Authors: John Hardy

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The expansion of special operations forces (SOF) in the twenty-first century is often discussed in terms of the size and disposition of SOF units. Research regarding the number SOF personnel, the equipment SOF units procure, and the variety of roles and mission that SOF fulfill in contemporary conflicts paints a fascinating picture of changing expectations for the use of force. A strong indicator of the changing nature of SOF in contemporary conflicts is the fusion of strike and intelligence functions in the SOF in many countries. What were once more distinct roles on the kind of battlefield generally associated with the concept of conventional warfare have become intermingled in the era of persistent conflict which SOF face. This study presents a historical analysis of the co-evolution of the intelligence and direct action functions carried out by SOF in counterterrorism, counterinsurgency, and training and mentoring missions between 2004 and 2016. The study focuses primarily on innovation in the US military and the diffusion of key concepts to US allies first, and then more broadly afterward. The findings show that there were three key phases of evolution throughout the period of study, each coinciding with a process of innovation and doctrinal adaptation. The first phase was characterized by the fusion of intelligence at the tactical and operational levels. The second phase was characterized by the industrial counterterrorism campaigns used by US SOF against irregular enemies in Iraq and Afghanistan. The third phase was characterized by increasing forward collection of actionable intelligence by SOF force elements in the course of direct action raids. The evolution of strike and intelligence functions in SOF operations between 2004 and 2016 was significantly influenced by reciprocity. Intelligence fusion led to more effective targeting, which then increased intelligence collection. Strike and intelligence functions were then enhanced by greater emphasis on intelligence exploitation during operations, which further increased the effectiveness of both strike and intelligence operations.

Keywords: counterinsurgency, counterterrorism, intelligence, irregular warfare, military operations, special operations forces

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Authors: Zhilin Wang, Zhihao Zheng, Linxin Liu

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This study proposes a low-code model-building approach that aims to simplify the development and deployment of artificial intelligence (AI) models. With an intuitive way to drag and drop and connect components, users can easily build complex models and integrate multiple algorithms for training. After the training is completed, the system automatically generates a callable model service API. This method not only lowers the technical threshold of AI development and improves development efficiency but also enhances the flexibility of algorithm integration and simplifies the deployment process of models. The core strength of this method lies in its ease of use and efficiency. Users do not need to have a deep programming background and can complete the design and implementation of complex models with a simple drag-and-drop operation. This feature greatly expands the scope of AI technology, allowing more non-technical people to participate in the development of AI models. At the same time, the method performs well in algorithm integration, supporting many different types of algorithms to work together, which further improves the performance and applicability of the model. In the experimental part, we performed several performance tests on the method. The results show that compared with traditional model construction methods, this method can make more efficient use, save computing resources, and greatly shorten the model training time. In addition, the system-generated model service interface has been optimized for high availability and scalability, which can adapt to the needs of different application scenarios.

Keywords: low-code, model building, artificial intelligence, algorithm integration, model deployment

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Authors: Joel Vilca Tarazona, Igor Aguilar-Alonso

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The problem of this research related to business intelligence is the lack of a tool that supports automated and efficient financial analysis for decision-making and allows an evaluation of the financial statements, which is why the availability of the information is difficult. Relevant information to managers and users as an instrument in decision making financial, and administrative. For them, a business intelligence solution is proposed that will reduce information access time, personnel costs, and process automation, proposing a 4-layer architecture based on what was reviewed by the research methodology.

Keywords: decision making, business intelligence, Google Cloud, Microsoft Power BI

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Authors: Mustafa Jahanara

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The aim of present research was to study of the relationship between emotional intelligence, perceived stress, positive religious coping with psychological distress to in a sample of undergraduate students in Polytechnic University in Kabul. One hundred and fifty-tow students (102 male, 50 female) were included in this study. All participants completed the Emotional Intelligence Scale (EIS), General Health Questionnaire (GHQ 12), Perceived Stress Scale (PSS-10), and the Brief RCOPE. The results revealed that EI was negatively associated with perceived stress and psychological distress. Also emotional intelligence was positively correlated with positive religious coping. Perceived stress was positive related with psychological distress and negatively correlated with positive religious coping. Eventually positive religious coping was significantly and negatively correlated with psychological distress. However, emotional intelligence and positive religious coping could influence on mental health.

Keywords: emotional intelligence, perceived stress, positive religious coping, psychological distress

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Authors: Edwin Njoroge Kimani, Alan M. Munyao

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Despite Kenya’s status as a regional economic powerhouse, it struggles with economic shocks that expose the consumers. This, however, seems not to affect major cooperates such as those in the telecommunication and energy sectors. Through their operations, they have not only been able to fluctuate prices at will but also they have been accused of curtailing their rivals from penetrating the market. This study, through literature review of the legal and institutional framework, reports and publications interrogates the law and uncovers the following; i) failings of the legal framework to define market dominance and abuse of such positions, ii) the participation of the state, iii) the inertia of the government to prosecute corporations that abuse their market dominance, iv) the role of the state as a market player and as a regulator through the Competition Authority of Kenya. This study concludes that the market distortion is as a result of weak legal and institutional framework as well as conflict of interest by the government. Not much has been researched in the field of competition law the greater East Africa. This research is intended to form part of the growing research in the field and inform legal reform.

Keywords: competition law, economic power, dominance, Kenya

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Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

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Authors: Salah Ghamari

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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

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Authors: Sarah Kalaouze, Maxine Iannucelli, Kristen Dunfield

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Children’s implicit beliefs regarding intelligence (i.e., intelligence mindsets) influence their motivation, perseverance, and success. Previous research suggests that the way parents perceive failure influences the development of their child’s intelligence mindsets. We invited 151 children-parent dyads (Age= 5–6 years) to complete a series of difficult puzzles over zoom. We assessed parents’ intelligence and failure mindsets using questionnaires and recorded parents’ person/performance-oriented (e.g., “you are smart” or "you were almost able to complete that one) and process-oriented (e.g., “you are trying really hard” or "maybe if you place the bigger pieces first") failure feedback. We were interested in observing the relation between parental mindsets and the type of feedback provided. We found that parents’ intelligence mindsets were not predictive of the feedback they provided children. Failure mindsets, on the other hand, were predictive of failure feedback. Parents who view failure-as-debilitating provided more person-oriented feedback, focusing on performance and personal ability. Whereas parents who view failure-as-enhancing provided process-oriented feedback, focusing on effort and strategies. Taken all together, our results allow us to determine that although parents might already have a growth intelligence mindset, they don’t necessarily have a failure-as-enhancing mindset. Parents adopting a failure-as-enhancing mindset would influence their children to view failure as a learning opportunity, further promoting practice, effort, and perseverance during challenging tasks. The focus placed on a child’s learning, rather than their performance, encourages them to perceive intelligence as malleable (growth mindset) rather than fix (fixed mindset). This implies that parents should not only hold a growth mindset but thoroughly understand their role in the transmission of intelligence beliefs.

Keywords: mindset(s), failure, intelligence, parental feedback, parents

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Authors: Ilker Ali Ozkan

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In this study, an artificial neural network model has been developed to estimate chronic kidney failure which is a common disease. The patients’ age, their blood and biochemical values, and 24 input data which consists of various chronic diseases are used for the estimation process. The input data have been subjected to preprocessing because they contain both missing values and nominal values. 147 patient data which was obtained from the preprocessing have been divided into as 70% training and 30% testing data. As a result of the study, artificial neural network model with 25 neurons in the hidden layer has been found as the model with the lowest error value. Chronic kidney failure disease has been able to be estimated accurately at the rate of 99.3% using this artificial neural network model. The developed artificial neural network has been found successful for the estimation of chronic kidney failure disease using clinical data.

Keywords: estimation, artificial neural network, chronic kidney failure disease, disease diagnosis

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Authors: Akram Waheb Nasef Alzordoky

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The wars and armed conflicts have frequently ended in violations of global humanitarian law and regularly devote the maximum severe global crimes, which include war crimes, crimes towards humanity, aggression and genocide. But, simplest inside the XX century, the guideline changed into an articulated idea of establishing a frame of worldwide criminal justice so that you can prosecute those crimes and their perpetrators. The first steps on this subject were made with the aid of setting up the worldwide army tribunals for warfare crimes at Nuremberg and Tokyo, and the formation of ad hoc tribunals for the former Yugoslavia and Rwanda. Ultimately, the global criminal courtroom was established in Rome in 1998 with the aim of justice and that allows you to give satisfaction to the sufferers of crimes and their families. The aim of the paper was to provide an ancient and comparative analysis of the establishments of worldwide criminal justice primarily based on which those establishments de lege lata fulfilled the goals of individual criminal responsibility and justice. Moreover, the authors endorse de lege ferenda that the everlasting global crook Tribunal, in addition to the potential case, additionally takes over the current ICTY and ICTR cases.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Keroles Akram Saed Ghatas

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The near future will bring significant changes in modern organizations and management due to the growing role of intangible assets and knowledge workers. The area of copyright, intellectual property, digital (intangible) assets and media redistribution appears to be one of the greatest challenges facing business and society in general and management sciences and organizations in particular. The proposed article examines the views and perceptions of fairness in digital media sharing among Harvard Law School's LL.M.s. Students, based on 50 qualitative interviews and 100 surveys. The researcher took an ethnographic approach to her research and entered the Harvard LL.M. in 2016. at, a Face book group that allows people to connect naturally and attend in-person and private events more easily. After listening to numerous students, the researcher conducted a quantitative survey among 100 respondents to assess respondents' perceptions of fairness in digital file sharing in various contexts (based on media price, its availability, regional licenses, copyright holder status, etc.). to understand better . .). Based on the survey results, the researcher conducted long-term, open-ended and loosely structured ethnographic interviews (50 interviews) to further deepen the understanding of the results. The most important finding of the study is that Harvard lawyers generally support digital piracy in certain contexts, despite having the best possible legal and professional knowledge. Interestingly, they are also more accepting of working for the government than the private sector. The results of this study provide a better understanding of how “fairness” is perceived by the younger generation of lawyers and pave the way for a more rational application of licensing laws.

Keywords: cognitive impairments, communication disorders, death penalty, executive function communication disorders, cognitive disorders, capital murder, executive function death penalty, egyptian law absence, justice, political cases piracy, digital sharing, perception of fairness, legal profession

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Authors: G. A. Kuanaliyeva, G. T. Aigarinova, G. K. Shulanbekova

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This article is devoted to judicial control in criminal legal proceedings of the Republic of Kazakhstan in the light of the new Concept of legal policy till 2020. In article the general characteristic and concept of judicial control, and also its signs and types are considered. Different views of scientists are analyzed. Foreign experiment on application of judicial control is given. The author states also the point sight on this problem and gives the definition to concept of judicial control. The code of criminal procedure of the Republic of Kazakhstan (RK Criminal Procedure Code) doesn't consolidate concept of judicial control. The author in article suggests making change and addition to the existing Code of criminal procedure of the Republic of Kazakhstan by definition of judicial control. The decree of the President of the Republic of Kazakhstan of August 24, 2009 No. 858 approved the Concept of legal policy of the Republic for the period from 2010 to 2020. The new Concept of legal policy of the Republic of Kazakhstan, defines prospects of development of national legal system of the country on the following decade. The concept of legal policy completely mentions also institute of judicial control. Since finding of the independence by Kazakhstan the set of laws, including the rights directed on providing, freedoms and a legitimate interest of citizens was accepted. Certainly, in any country, whatever democratic it was, there are problems to human rights. However, it is obvious that Kazakhstan strongly intends to guarantee all Republic of Kazakhstan proclaimed in the Constitution the rights and freedoms of the citizens. Our country seeks for creation of the constitutional state, tries to provide a guarantee from various arbitrariness in activity of competent government bodies, officials. In the concept of legal policy of the Republic of Kazakhstan it is specified: "...priority of development of the criminal procedure right there is a further consecutive realization of the fundamental principles of the criminal legal proceedings directed on protection of the rights and freedoms of the person". Judicial control just also is such guarantee.

Keywords: rights and freedoms of the person, concept, legal policy, court, judicial control

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Authors: Saad Saeed Althiabi

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This paper discusses the corporate positioning and how it became popular as a way to systematize production because of the unique manner in which incorporation legalized organizers to secure financial capital through locking it in. The power to lock in capital comes from the fact that a corporate exists as a separate legal entity, whose survival and governance are separated from any of its participants. The law essentially creates a different legal person when a corporation is created. Although this idea has been played down in the legal learning of the last decades in favor of the view that a corporation is purely something through which natural persons interrelate, recent legal research has begun to reassess the importance of entity status. Entity status, under the law and the related separation of governance from input of financial capital through the configuration of a corporation, sanctioned corporate participants to do somewhat more than connect in a series of business transactions.

Keywords: corporate law, entity status, locking in capital, financial capital

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Authors: Mohammed Qutishat, Khaldoun Aldiabat, Khaled Bader, Mohammad Al Qadire

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Cyberchondria refers to the irrational increase of distress about the condition of one's health as a consequence of the World Wide Web quest for medical details. The aim of this study was to examine the relationship between emotional intelligence and cyberchondria among Omani university students. A descriptive correlational design was used to collect data from eligible 370 participants using the Emotional Intelligence Questionnaire, and the short-form version of the Cyberchondria Severity Scale (CSS-12) between January and May 2020 at XX University-Oman. The participants’ age ranged between 18 and 37 years (M = 20.28). The majority of the participants were female, 59.7% (n = 221), single 99.5% (368), in their second academic year, 29.2% (n =108). The mean score of cyberchondria experiences was 32.51, and the mean score of emotional intelligence was 34.91. Linear regression indicated a strong association between cyberchondria and emotional intelligence [F (34.639) = 5.885, P=.000], with a .086 R². In conclusion, the exchange of expertise and peer networking for health-related details utilizing the Internet can benefit students with and without having health problems. Further research and methods should be developed to help students track the online medical tools effectively for the right purposes.

Keywords: emotional intelligence, cyberchondria, smartphone addiction, social media

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Maaza Saeed

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The current study examined the mediating roles of emotional intelligence (EI) and resilience in the relationship between mindfulness and life satisfaction among Chinese and Pakistani samples. 450 participants completed the mindful attention awareness scale, resilience scale, wong law emotional intelligence scale, and satisfaction with life scale from both cultures. Path analysis revealed that both emotional intelligence (EI) and resilience fully mediated the relationship between mindfulness and life satisfaction among participants of both cultures. Besides, a multi-group evaluation suggests that Chinese participants with significant EI scores are more likely to sustain greater life satisfaction than their Pakistani counterparts. Insinuation for prospective researches and current study pitfalls are discussed.

Keywords: mindfulness, life satisfaction, resilience, emotional intelligence

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Zahid Shafait, Jiayu Huang

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Purpose: This study is based on a trait-based theory of emotional intelligence. This study intends to explore the enabling effect of organizational climate, i.e., affiliation, innovation, and fairness, on the emotional intelligence of teachers in Chinese higher education institutes. This study, additionally, intends to investigate the direct impact of teachers’ emotional intelligence on their learning outcomes, i.e., cognitive, social, self-growth outcomes and satisfaction with the university experience. Design/methodology/approach: This study utilized quantitative research techniques to scrutinize the data. Moreover, partial least squares structural equation modeling, i.e., PLS-SEM, was used to assess the hypothetical relationships to conclude their statistical significance. Findings: Results confirmed the supposed associations, i.e., the organizational climate has an enabling effect on emotional intelligence. Likewise, emotional intelligence was concluded to have a direct and positive association with learning outcomes in higher education. Practical implications: This study has investigated abandoned research that is enabling the effects of organizational climate on teachers’ emotional intelligence in Chinese higher education. Organizational climate enables emotionally intelligent teachers to learn efficiently and, at the same time, augments their satisfaction and productivity within an institution. Originality/value: This study investigated the enabling effects of organizational climate on teachers’ emotional intelligence in Chinese higher education that is original in investigated country and sector.

Keywords: organizational climate, emotional intelligence, learning outcomes, higher education

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Authors: Bahadir Aydin

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Today it is difficult to reach accurate knowledge because of mass data. This huge data makes the environment more and more caotic. Data is a main piller of intelligence. There is a close tie between knowledge and intelligence. Information gathered from different sources can be modified, interpreted and classified by using knowledge development process. This process is applied in order to attain intelligence. Within this process the effect of knowledge is crucial. Knowledge is classified as explicit and tacit knowledge. Tacit knowledge can be seen as "only the tip of the iceberg”. This tacit knowledge accounts for much more than we guess in all intelligence cycle. If the concept of intelligence scrutinized, it can be seen that it contains risks, threats as well as success. The main purpose for all organization is to be succesful by eliminating risks and threats. Therefore, there is a need to connect or fuse existing information and the processes which can be used to develop it. By the help of process the decision-maker can be presented with a clear holistic understanding, as early as possible in the decision making process. Planning, execution and assessments are the key functions that connects to information to knowledge. Altering from the current traditional reactive approach to a proactive knowledge development approach would reduce extensive duplication of work in the organization. By new approach to this process, knowledge can be used more effectively.

Keywords: knowledge, intelligence cycle, tacit knowledge, KIDW

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Authors: Athari Farhani

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Abstract The existence of space debris is a direct implication of human activities in outer space. The amount of orbital debris resulting from human exploration and use of outer space has been steadily increasing in the history of human exploration and use of outer space, so that space debris in the responsibility of the launching state. Space debris not only hs a direct impact on environmentalpollution but can also harm and endanger the safety of human life. Despite the legal provisions governing the exploration and use of outer space, both international space law and liability convention, however, these legal provisions are only basic prinsiples, so that further thought or effort are needed, such as new international legal instruments to regulate the existence of space debris. The method used in this research is normative juridical with an approach to written legal regulation, especially international agreements related to space law.

Keywords: state’s responsibility, space debris, outerspace, international law

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Authors: Mohammad Yousef

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The issue of targeted killing has become a part of modern international law topics, as its spread has been accompanied by the technological development of weapons and military equipment, especially armed drones. Until now, there is no specific definition or legal framework for targeted killing in international law, and the issue of its compatibility with international law is still subject to debate and controversy. The case of the targeted killing of General Qassem Soleimani sparked waves of reactions and discussions between legal scholars and US officials in an argument about the legality of killing him in the light of international law rules and US domestic law. This paper firstly discusses the legality of targeted killing in international law and US domestic law; after that, it studies the legal bases and the legal system that governs these operations, while in the second section, it sheds light on the case of Soleimani’s targeted killing in light of international law and US domestic law, by examining the different views of jurists in this regard.

Keywords: targeted killing, international law, US domestic law, Qassem Soleimani

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: Hamid Vahidkia

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This article explores advancements in global law and how they interact with domestic legal systems. The article's introduction highlights that nations that gained independence from authoritarian governments tend to be more open to international law. A nation can choose to follow either a monist strategy regarding international law, viewing it as an integral part of its own legal system, or opt for a dualist approach, where it keeps its domestic law distinct from international law. The beginning goes on to recognize the origins of international law, such as treaties and countries' ways of following them, customary international law, and declarations. The introduction ends by acknowledging the growing significance and development of international law.

Keywords: international law, customary law, treaties, human right

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Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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In the increasingly interconnected global environment brought about by globalization, it is crucial for countries to timely grasp the development motivations in relevant research fields of other countries and seize development opportunities. Motivation, as the intrinsic driving force behind actions, is abstract in nature, making it difficult to directly measure and evaluate. Drawing on the ideas of social influence network theory, the research motivations of a country can be understood as the driving force behind the development of its science and technology sector, which is simultaneously influenced by both the country itself and other countries/regions. In response to this issue, this paper improves upon Friedkin's social influence network theory and applies it to motivation description, constructing a dynamic alliance network and hostile network centered around the United States and China, as well as a sensitivity matrix, to remotely assess the changes in national research motivations under the influence of international relations. Taking artificial intelligence as a case study, the research reveals that the motivations of most countries/regions are declining, gradually shifting from a neutral attitude to a negative one. The motivation of the United States is hardly influenced by other countries/regions and remains at a high level, while the motivation of China has been consistently increasing in recent years. By comparing the results with real data, it is found that this model can reflect, to some extent, the trends in national motivations.

Keywords: influence network theory, remote assessment, relation matrix, dynamic sensitivity matrix

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Authors: Zhang Rui

Abstract:

Context: The paper addresses the necessity of incorporating the principle of sustainable development into international law to guide states and international organizations towards achieving this goal. Research aim: To emphasize the importance of integrating sustainable development into international law and establishing procedures to attain this objective. Methodology: The study utilizes document analysis, comparative law analysis, and international law analysis to support the argument for including sustainable development in international legal frameworks. Findings: The findings suggest that integrating sustainable development into international law can lead to significant improvements in legal practices, treaty interpretations, and state behaviors. Theoretical importance: The paper highlights the potential impacts of the principle of sustainable development on reshaping existing legal norms and promoting sustainable practices globally. Data collection: The data is gathered through the analysis of relevant legal documents, comparative studies, and international legal frameworks. Analysis procedures: The analysis involves examining how the principle of sustainable development can influence legal outcomes, treaty interpretations, and state behaviors. Questions addressed: The study addresses how the principle of sustainable development can be integrated into international law and what implications this integration can have on legal practices and state behaviors. Conclusion: Integrating sustainable development into international law is crucial for advancing global sustainability objectives and guiding states and international organizations towards sustainable practices.

Keywords: international law, sustainable development, environmental legislation, sovereign equality

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Authors: Frank Frimpong Opuni, Michael Mba Allan, Kwame Adu-Gyamfi, Michael Sarkodie Baffoe

Abstract:

This paper assesses the effect of relationship marketing on service quality and customer satisfaction from the perspective of the moderating role of emotional intelligence in the insurance industry in Ghana. A descriptive quantitative research technique was employed. A random sample of 384 each of customers and service providers in 3 insurance firms in Accra were used as the source of data. According to findings, emotional intelligence makes a strong positive effect on relationship marketing at 5% significance level, r (283) = .817, p = .000. Though relationship marketing makes a strong positive effect on service quality (r = .767, p < .05) and customer satisfaction (r = .647, p < .05), this effect becomes insignificant (p > .05) when the effect of emotional intelligence on relationship marketing is controlled for. It is therefore recommended that insurance firms give priority to equipping their relationship employees with emotional intelligence to maximise service quality and customer satisfaction.

Keywords: relationship marketing, service quality, customer satisfaction, emotional intelligence

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Authors: Zhang Rui

Abstract:

The primary aim of the study is to compare legislative jurisdiction and judicial jurisdiction in international law, highlighting the unique conditions and bases for their exercise in legal practice.The research employs a comparative law analysis approach alongside a thorough examination of international law principles to achieve a comprehensive understanding of legislative and judicial jurisdiction in the international legal context. The findings of this research underscore the diverse development trajectory of legislative jurisdiction in international law, emphasizing the continued significance of territoriality as a primary basis for exercising judicial jurisdiction.

Keywords: international law, judicial jurisdiction, legislative jurisdiction, legal implementation

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