Search results for: autonomous intelligence

Authors: Angela Oktavia Suryani, Bernadeth Gloria, Edwin Sutamto, Jessica Kristianty, Ni Made Rai Sapitri, Patricia Catherine Agla, Sitti Arlinda Rochiadi

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It was found that some blogs or personal websites in Indonesia sell standardized intelligence tests (for example, Progressive Matrices (PM), Intelligence Structure Test (IST), and Culture Fair Intelligence Test (CFIT)) and other psychological tests, together with the manual and the key answers for public. Individuals can buy and prepare themselves for selection or recruitment with the real test. This action drives people to lie to the institution (education or company) and also to themselves. It was also found that those tests are old. Some items are not relevant with the current context, for example a question about a diameter of a certain coin that does not exist anymore. These problems motivate us to develop a new intelligence battery test, namely of Multiple Aptitude Battery (MAB). The battery test was built by using Thurstone’s Primary Mental Abilities theory and intended to be used by high schools students, university students, and worker applicants. The battery tests consist of 9 subtests. In the current study we examine six subtests, namely Reading Comprehension, Verbal Analogies, Numerical Inductive Reasoning, Numerical Deductive Reasoning, Mechanical Ability, and Two Dimensional Spatial Reasoning for university students. The study included 1424 data from students recruited by convenience sampling from eight faculties at Atma Jaya Catholic University of Indonesia. Classical and modern test approaches (Item Response Theory) were carried out to identify the item difficulties of the items and confirmatory factor analysis was applied to examine their internal validities. The validity of each subtest was inspected by using convergent–discriminant method, whereas the reliability was examined by implementing Kuder–Richardson formula. The result showed that the majority of the subtests were difficult in medium level, and there was only one subtest categorized as easy, namely Verbal Analogies. The items were found homogenous and valid measuring their constructs; however at the level of subtests, the construct validity examined by convergent-discriminant method indicated that the subtests were not unidimensional. It means they were not only measuring their own constructs but also other construct. Three of the subtests were able to predict academic performance with small effect size, namely Reading Comprehension, Numerical Inductive Reasoning, and Two Dimensional Spatial Reasoning. GPAs in intermediate level (GPAs at third semester and above) were considered as a factor for predictive invalidity. The Kuder-Richardson formula showed that the reliability coefficients for both numerical reasoning subtests and spatial reasoning were superior, in the range 0.84 – 0.87, whereas the reliability coefficient for the other three subtests were relatively below standard for ability test, in the range of 0.65 – 0.71. It can be concluded that some of the subtests are ready to be used, whereas some others are still need some revisions. This study also demonstrated that the convergent-discrimination method is useful to identify the general intelligence of human.

Keywords: intelligence, psychometric examination, multiple aptitude battery, university students

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Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

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As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

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Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Youcef Serhane, Abdelkrim Bouzaza, Dominique Wolbert, Aymen Amin Assadi

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Throughout history, the use of chemical weapons is not exclusive to combats between army corps; some of these weapons are also found in very targeted intelligence operations (political assassinations), organized crime, and terrorist organizations. To improve the speed of action, important technological devices have been developed in recent years, in particular in the field of protection and decontamination techniques to better protect and neutralize a chemical threat. In order to assess certain protective, decontaminating technologies or to improve medical countermeasures, tests must be conducted. In view of the great toxicity of toxic chemical agents from (real) wars, simulants can be used, chosen according to the desired application. Here, we present an investigation about using a photocatalytic filtering reactor (PFR) for highly contaminated environments containing diethyl sulfide (DES). This target pollutant is used as a simulant of CWA, namely of Yperite (Mustard Gas). The influence of the inlet concentration (until high concentrations of DES (1200 ppmv, i.e., 5 g/m³ of air) has been studied. Also, the conversion rate was monitored under different relative humidity and different flow rates (respiratory flow - standards: ISO / DIS 8996 and NF EN 14387 + A1). In order to understand the efficacity of pollutant neutralization by PFR, a kinetic model based on the Langmuir–Hinshelwood (L–H) approach and taking into account the mass transfer step was developed. This allows us to determine the adsorption and kinetic degradation constants with no influence of mass transfer. The obtained results confirm that this small configuration of reactor presents an extremely promising way for the use of photocatalysis for treatment to deal with highly contaminated environments containing real chemical warfare agents. Also, they can give birth to an individual protection device (an autonomous cartridge for a gas mask).

Keywords: photocatalysis, photocatalytic filtering reactor, diethylsulfide, chemical warfare agents

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Authors: Mai Anh Tuan, Wenlong Liu, Meng Li

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Despite warnings and concerns about the use of fast food that has health effects, the fast-food industry is actually a source of profit for the global food industry. Obviously, in the face of such huge economic benefits, investors will not hesitate to continuously add recipes, processing methods, menu diversity, etc., to improve and apply information technology in enhancing the diners' experience; the ultimate goal is still to attract diners to find their brand and give them the fastest, most convenient and enjoyable service. In China, as the achievements of the industrial revolution 4.0, big data and artificial intelligence are reaching new heights day by day, now fast-food diners can instantly pay the bills only by identifying the biometric signature available on the self-ordering kiosk, using their own face without any additional form of confirmation. In this study, the author will evaluate the acceptance level of customers with this new form of payment through a survey of customers who have used and witnessed the use of smart kiosks and biometric payments within the city of Nanjing, China. A total of 200 valid volunteers were collected in order to test the customers' intentions and feelings when choosing and experiencing payment through AI services. 55% think that it bothers them because of the need for personal information, but more than 70% think that smart kiosk brings out many benefits and convenience. According to the data analysis findings, perceived innovativeness has a positive influence on satisfaction which in turn affects behavioral intentions, including reuse and word-of-mouth intentions.

Keywords: artificial intelligence, catering industry, smart kiosks, technology acceptance

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Authors: Lourens Millard, Gerrit Jan Breukelman, Nonkululeko Mathe

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Aim: The research aims to investigate the differences in visio-spatial skills (VSS) between athletes and non-athletes, as well as variations across sports, presenting conflicting findings. Therefore, the objective of this study was to determine if there exist significant differences in visio-spatial intelligence skills between rugby players and netball players, and whether such disparities are present when comparing both groups to non-athletes. Methods: Participants underwent an optometric assessment, followed by an evaluation of VSS using six established tests: the Hart Near Far Rock, saccadic eye movement, evasion, accumulator, flash memory, and ball wall toss tests. Results: The results revealed that rugby players significantly outperformed netball players in speed of recognition, peripheral awareness, and hand-eye coordination (p=.000). Moreover, both rugby players and netball players performed significantly better than non-athletes in five of the six tests (p=.000), with the exception being the visual memory test (p=.809). Conclusion: This discrepancy in performance suggests that certain VSS are superior in athletes compared to non-athletes, highlighting potential implications for theories of vision, test selection, and the development of sport-specific VSS testing batteries. Furthermore, the use of a hand-eye coordination-specific VSS test battery effectively differentiated between different sports. However, this pattern was not consistent across all VSS tests, indicating that further research should explore the training methods employed by both sports, as these factors may contribute to the observed differences.

Keywords: visio-spatial intelligence (VSI), rugby vision, netball vision, visual skills, sport vision.

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Authors: Jean-François Caron

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The current attempts to develop what we can call 'super soldiers' are problematic in many regards. This is what this text will try to explore by concentrating primarily on the repercussions of this technology and medical research on the physical and psychological integrity of soldiers. It argues that medicines or technologies may affect soldiers’ psychological and mental features and deprive them of their capacity to reflect upon their actions as autonomous subjects and that such a possibility entails serious moral as well as judicial consequences.

Keywords: military research, super soldiers, involuntary intoxication, criminal responsibility

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Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

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The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

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Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

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Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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Authors: Jinsiang Shaw, Sheng-Xiang Xu

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This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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Authors: Wendy de Gomez

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Standardization is a critical element in the ability of a society to reduce uncertainty, subjectivity, misrepresentation, and interpretation while simultaneously contributing to innovation. Technological standardization is critical to codify specific operationalization through legal instruments that provide rules of development, expectation, and use. In the current emerging technology landscape Artificial Intelligence (AI) hardware as a general use technology has seen incredible growth as evidenced from AI technology patents between 2012 and 2018 in the United States Patent Trademark Office (USPTO) AI dataset. However, as outlined in the 2023 United States Government National Standards Strategy for Critical and Emerging Technology the codification through standardization of emerging technologies such as AI has not kept pace with its actual technological proliferation. This gap has the potential to cause significant divergent possibilities for the downstream outcomes of AI in both the short and long term. This original empirical research provides an overview of the standardization efforts around AI in different geographies and provides a background to standardization law. It quantifies the longitudinal trend of Artificial Intelligence hardware patents through the USPTO AI dataset. It seeks evidence of existing Standard Essential Patents from these AI hardware patents through a text analysis of the Statement of patent history and the Field of the invention of these patents in Patent Vector and examines their determination as a Standard Essential Patent and their inclusion in existing AI technology standards across the four main AI standards bodies- European Telecommunications Standards Institute (ETSI); International Telecommunication Union (ITU)/ Telecommunication Standardization Sector (-T); Institute of Electrical and Electronics Engineers (IEEE); and the International Organization for Standardization (ISO). Once the analysis is complete the paper will discuss both the theoretical and operational implications of F/Rand Licensing Agreements for the owners of these Standard Essential Patents in the United States Court and Administrative system. It will conclude with an evaluation of how Standard Setting Organizations (SSOs) can work with SEP owners more effectively through various forms of Intellectual Property mechanisms such as patent pools.

Keywords: patents, artifical intelligence, standards, F/Rand agreements

Procedia PDF Downloads 87

Authors: Serge Lacroix

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The proposed study looks at the psychoeducational assessment of bilingual students, in English and French in this case. It will be the opportunity to look at language of assessment and specifically how certain tests can be administered in one language and others in another language. It is also a look into the questioning of the validity of the test scores that are obtained as well as the quality and generalizability of the conclusions that can be drawn. Bilingualism and multiculturalism, although in constant expansion, is not considered in norms development and remains a poorly understood factor when it is at play in the context of a psychoeducational assessment. Student placement, diagnoses, accurate measures of intelligence and achievement are all impacted by the quality of the assessment procedure. The same is true for questionnaires administered to parents and self-reports completed by bilingual students who, more often than not, are assessed in a language that is not their primary one or are compared to monolinguals not dealing with the same challenges or the same skills. Results show that students, when offered to work in a bilingual fashion, chooses to do so in a significant proportion. Recommendations will be offered to support educators aiming at expanding their skills when confronted with multilingual students in an assessment context.

Keywords: psychoeducational assessment, bilingualism, multiculturalism, intelligence, achievement

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Henning Lahmann, Benjamyn I. Scott, Bart Custers

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Suboptimal adoption of AI in defence organisations carries risks for the protection of the freedom, safety, and security of society. Despite the vast opportunities that defence AI-technology presents, there are also a variety of ethical, legal, and societal concerns. To ensure the successful use of AI technology by the military, ethical, legal, and societal aspects (ELSA) need to be considered, and their concerns continuously addressed at all levels. This includes ELSA considerations during the design, manufacturing and maintenance of AI-based systems, as well as its utilisation via appropriate military doctrine and training. This raises the question how defence organisations can remain strategically competitive and at the edge of military innovation, while respecting the values of its citizens. This paper will explain the set-up and share preliminary results of a 4-year research project commissioned by the National Research Council in the Netherlands on the ethical, legal, and societal aspects of AI in defence. The project plans to develop a future-proof, independent, and consultative ecosystem for the responsible use of AI in the defence domain. In order to achieve this, the lab shall devise a context-dependent methodology that focuses on the ‘analysis’, ‘design’ and ‘evaluation’ of ELSA of AI-based applications within the military context, which include inter alia unmanned aircraft. This is bolstered as the Lab also recognises and complements the existing methods in regards to human-machine teaming, explainable algorithms, and value-sensitive design. Such methods will be modified for the military context and applied to pertinent case-studies. These case-studies include, among others, the application of autonomous robots (incl. semi- autonomous) and AI-based methods against cognitive warfare. As the perception of the application of AI in the military context, by both society and defence personnel, is important, the Lab will study how these perceptions evolve and vary in different contexts. Furthermore, the Lab will monitor – as they may influence people’s perception – developments in the global technological, military and societal spheres. Although the emphasis of the research project is on different forms of AI in defence, it focuses on several case studies. One of these case studies is on unmanned aircraft, which will also be the focus of the paper. Hence, ethical, legal, and societal aspects of unmanned aircraft in the defence domain will be discussed in detail, including but not limited to privacy issues. Typical other issues concern security (for people, objects, data or other aircraft), privacy (sensitive data, hindrance, annoyance, data collection, function creep), chilling effects, PlayStation mentality, and PTSD.

Keywords: autonomous weapon systems, unmanned aircraft, human-machine teaming, meaningful human control, value-sensitive design

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Authors: Zahra Ebrahimi, Abbas Moradan

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This study investigated the effect of applying different layers of activity for different Iranian intermediate EFL learner’s oral proficiency and two of its components (fluency and accura-cy) for the beneficial use of films within speaking classes. For this purpose, thirty Iranian EFL intermediate learners were selected based on availability sampling, they were divided into one experimental group and one control group, each consisting of 15 participants, who were proved to be homogeneous based on the results obtained from IELTS oral proficien-cy test prior to the treatment. Experimental Group received the treatment which was apply-ing different layers of speaking tasks according to learners’ level of fluency and accuracy. Control group received ordinal treatment of speaking classrooms. The materials for this study consisted of 11 English movies for each session, voice-recorder device, and IELTS oral proficiency tests as well as two interviews based on Ur’s oral scale for measuring fluen-cy and accuracy. The treatment was run for 12 sessions in six weeks. At the end of the treatment, all the students both in experimental and control group were given a post-test interview based on Ur’s scale. To compare and contrast the amount of progress of the learners in different groups the results of the pre-test and post-test of speaking were analysed by using T-tests. Moreover, Multivariate analysis of variance was also used to check the hypotheses. Results showed that application of different layers of activity with regard to students’ level, led to a significantly superior performance in experimental group. Thus, this study verified the positive effect of implementation of different layers of activity and tasks to achieve progress in speaking skill. It can also help to create a less stressful at-mosphere of learning in which all the students will be given specific time to speak and lead them to be autonomous learners.

Keywords: differentiated instruction, learners’ style, multiple intelligence, speaking skill, task-based activities

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Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

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In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

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Authors: Brittany Duboz-Quinville

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Emotional Intelligence (EI) is a growing field, and many studies are examining how it pertains to the workplace. In the context of crisis management several studies have postulated that EI could play a role in individuals’ ability to execute crisis plans. However, research evaluating the EI of leaders who have actually managed a crisis is still lacking. The COVID-19 pandemic forced many businesses into a crisis situation beginning in March and April of 2020. This study sought to measure both EI and effective crisis management (CM) during the COVID-19 pandemic to determine if they were positively correlated. A quantitative survey was distributed via the internet that comprised of 15 EI statements, and 15 CM statements with Likert scale responses, and 6 demographic questions with discrete responses. The hypothesis of the study was: it is believed that EI correlates positively with effective crisis management. The results of the study did not support the studies hypothesis as the correlation between EI and CM was not statistically significant. An additional correlation was tested, comparing employees’ perception of their superiors’ EI (Perception) to employees’ opinion of how their superiors managed the crisis (Opinion). This Opinion and Perception correlation was statistically significant. Furthermore, by examining this correlation through demographic divisions there are additional significant results, notably that French speaking employees have a stronger Opinion/Perception correlation than English speaking employees. Implications for cultural differences in EI and CM are discussed as well as possible differences across job sectors. Finally, it is hoped that this study will serve to convince more companies, particularly in France, to embrace EI training for staff and especially managers.

Keywords: crisis management, emotional intelligence, empathy, management training

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Authors: Justin Bin

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Artificial intelligence (AI) has been rapidly rising in usage recently, already active in the daily lives of millions, from distinguished AIs like the popular ChatGPT or Siri to more obscure, inconspicuous AIs like those used in social media or internet search engines. As upcoming generations grow immersed in emerging technology, AI will play a vital role in their development. Namely, the education sector, an influential portion of a person’s early life as a student, faces a vast ocean of possibilities concerning the implementation of AI. The main purpose of this study is to analyze the effect that AI will have on the future of the educational field. More particularly, this study delves deeper into the following three categories: school admissions, the productivity of students, and ethical concerns (role of human teachers, purpose of schooling itself, and significance of diplomas). This study synthesizes research and data on the current effects of AI on education from various published literature sources and journals, as well as estimates on further AI potential, in order to determine the main, overarching effects it will have on the future of education. For this study, a systematic organization of data in terms of type (quantitative vs. qualitative), the magnitude of effect implicated, and other similar factors were implemented within each area of significance. The results of the study suggest that AI stands to change all the beforementioned subgroups. However, its specific effects vary in magnitude and favorability (beneficial or harmful) and will be further discussed. The results discussed will reveal to those affiliated with the education field, such as teachers, counselors, or even parents of students, valuable information on not just the projected possibilities of AI in education but the effects of those changes moving forward.

Keywords: artificial intelligence, education, schools, teachers

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Authors: Shen Xiaoyun

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The AI-generated works must intersect with the right holder’s work, thus having a certain impact on the rights and interests of the right holder’s work. The law needs to explore and improve the regulation of the fair use of AI creations and build a compensation system to adapt to the development of the times. The development of AI technology has brought about problems such as the unclear relationship between fair use and infringement of copyright, the unclear general terms and conditions of application, and the incomplete criteria for judging at different stages. Through different theoretical methods, the legitimacy of the rational use of the system can be demonstrated. The compensation standard for fair use of copyright in AI creation can refer to the market pricing of the right holder's work, and the compensation can construct a formula for the amount of damages for AI copyright infringement, and construct the compensation standard based on the main factors affecting the market value of the work, so as to provide a reference for the construction of a compensation system for fair use of works generated by AI.

Keywords: artificial intelligence, creative acts, fair use of copyright, copyright compensation system

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Authors: Monjur E-Khoda Tarafdar

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Institutional autonomy and academic freedom corresponding to accountability are seen as a core concept of university governance. Universities are crucial factors in search of truth for knowledge production and dissemination. Academic leaders are the pivots to progressively influence the university governance. Therefore, in a continuum of debate about autonomy and accountability in the aspect of perception, academic leadership has been studied. Having longstanding acquaintance in the field the researcher has been instrumental to gain lived experiences of the informants in this qualitative study. Case studies are useful to gain an understanding of the complexities of a particular site to preserve a sense of wholeness of the site being investigated. Thus, multiple case study approach has been employed with a sample size of seventy-one. Such large size of informants was interviewed in order to capture a wider range of views that exist in Bangladesh. This qualitative multiple case study has engaged in-depth interviewing method of academic leaders and policy makers of three case universities. Open-ended semi-structured questionnaires are used to have a comprehensive understanding of how the perception of autonomy and accountability of academic leaders has impacted university governance in the context of Bangladesh. The paper has interpreted the voices of the informants and distinguished both the transformational and transactional style of academic leaderships in local university settings against the globally changed higher education demography. The study finds contextual dissimilarity in the perspectives of autonomy and accountability of academic leadership towards university governance. Unaccountability results in losing autonomous power and collapsing academic excellence. Since accountability grows competitiveness and competence, the paper also focuses on how academic leaders abuse the premise of academic loyalty to universities.

Keywords: academic loyalty, accountability, autonomy, leadership, perception, university governance

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Authors: Mohammed Talib Alkiyumi

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The Sultanate of Oman is characterized by a huge musical heritage that remains mostly preserved. 142 different traditional musical genres and styles (funun) have been registered in the Sultanate. This large number is a unique phenomenon that is worthy of attention and study. These genres and styles are different from others in their origins, rhythms, melodies, poetry, dance movements, etc. Certainly, Oman is exposed to other cultures and there is a variety of ethnicities in the Sultanate; however, this musical diversity is mostly an Omani product. This paper investigates the psychological motives behind Omani musical creativity. This qualitative study is based on relevant documents, as well as an analysis of Omani performance in those genres through documentary films and direct observations. Musical genres are performed in social events such as weddings and celebrations; however, research has shown psychological motives that motivated Omani people to create these various genres, such as provocation of enthusiasm, meditation, religious motivations, poetic competition, and emotional motivation. For each motive, musical genres have been presented.

Keywords: traditional musical, creativity, musical intelligence, Sultanate of Oman

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Authors: Chih Chin Yang, Chung Shan Sun

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In this paper, the relationships between professional competences and school curricula in IC design industry are explored. The semi-structured questionnaire survey and focus group interview is the research method. Study participants are graduates of microelectronics engineering professional departments who are currently employed in the IC industry. The IC industries are defined as the electronic component manufacturing industry and optical-electronic component manufacturing industry in the semiconductor industry and optical-electronic material devices, respectively. Study participants selected from IC design industry include IC engineering and electronic & semiconductor engineering. The human training with IC design professional competence in microelectronics engineering professional departments is explored in this research. IC professional competences of human resources in the IC design industry include general intelligence and professional intelligence.

Keywords: IC design, curricula, competence, task, duty

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Authors: Ciro Cursio, Pio Luigi Cursio, Giulia Cursio, Isabella Chiardi, Luigi Cursio

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Introduction: Full-face aesthetic treatments often present a difficult task: since different patients possess different anatomical and tissue characteristics, there is no guarantee that the same treatment will have the same effect on multiple patients; additionally, full-face rejuvenation and beautification treatments require not only a high degree of technical skill but also the ability to choose the right product for each area and a keen artistic eye. Method: We present an artificial intelligence-based algorithm that can generate realistic post-treatment 3D models based on the patient’s requests together with the doctor’s input. These 3-dimensional predictions can be used by the practitioner for two purposes: firstly, they help ensure that the patient and the doctor are completely aligned on the expectations of the treatment; secondly, the doctor can use them as a visual guide, obtaining a natural result that would normally stem from the practitioner's artistic skills. To this end, the algorithm is able to predict injection zones, the type and quantity of hyaluronic acid, the injection depth, and the technique to use. Results: Our innovation consists in providing an objective visual representation of the patient that is helpful in the patient-doctor dialogue. The patient, based on this information, can express her desire to undergo a specific treatment or make changes to the therapeutic plan. In short, the patient becomes an active agent in the choices made before the treatment. Conclusion: We believe that this algorithm will reveal itself as a useful tool in the pre-treatment decision-making process to prevent both the patient and the doctor from making a leap into the dark.

Keywords: hyaluronic acid, fillers, full face, artificial intelligence, 3D

Procedia PDF Downloads 89

Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Payal Maheshwari, Bansari Shah

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The research aimed to study the level of emotional intelligence (EI) and organizational role stress (ORS) of fire-fighters and the relationship between the two variables. Hundred and twenty fire-fighters were selected from different fire stations of Mumbai by purposive sampling. The firefighters who had the basic training, a minimum experience of 2 years and had been on the field during a crisis situation were selected for the study. The firefighters selected ranged from 23-58 years of age, and the number of years of experience ranged from 2 to 33 years. The findings of the study revealed that majority of the firefighters perceived themselves to be at an above average (57) and high (58) level of EI (M=429.35, SD=38.712). Domain-wise analysis disclosed that compared to self-awareness (92) and relationship management (93), more number of participants perceived themselves in the high category in the domains of self-management (108) and social management (106). Further, examination of the subdomain scores conveyed that a large number of participants rated themselves in the average level of these skills of accurate self-assessment (50), emotional self-control (50), adaptability (56) initiative (41), influence (66), change catalyst (53), and conflict management (50). With relation to the stress variable, it was found that almost half the number of the participants (59) rated themselves as having an average level of stress (M=137.44, SD=28.800). In most of the domains, majority of the participants perceived themselves as having an average level of stress, while in the domain of role isolation, self-role distance, and role ambiguity, majority of the firefighters rated themselves as having a low level of stress. A strong negative correlation (r=-.360**, p=.000) was found between EI and ORS. This study is a contribution to the literature and has implications for fire-fighters at the personal level, for the policymakers, and the fire department.

Keywords: emotional intelligence, organizational role stress, firefighters, relationship

Procedia PDF Downloads 114

Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

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The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

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Authors: John Hardy

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A range of future-oriented intelligence techniques is commonly used by states to assess their national security and develop strategies to detect and manage threats, to develop and sustain capabilities, and to recover from attacks and disasters. Although homeland security organizations use future's intelligence tools to generate scenarios and simulations which inform their planning, there have been relatively few studies of the methods available or their applications for homeland security purposes. This study presents an assessment of one category of strategic intelligence techniques, termed Multi-Path Futures Analyses (MPFA), and how it can be applied to three distinct tasks for the purpose of analyzing homeland security issues. Within this study, MPFA are categorized as a suite of analytic techniques which can include effects-based operations principles, general morphological analysis, multi-path mapping, and multi-criteria decision analysis techniques. These techniques generate multiple pathways to potential futures and thereby generate insight into the relative influence of individual drivers of change, the desirability of particular combinations of pathways, and the kinds of capabilities which may be required to influence or mitigate certain outcomes. The study assessed eighteen uses of MPFA for homeland security purposes and found that there are five key applications of MPFA which add significant value to analysis. The first application is generating measures of success and associated progress indicators for strategic planning. The second application is identifying homeland security vulnerabilities and relationships between individual drivers of vulnerability which may amplify or dampen their effects. The third application is selecting appropriate resources and methods of action to influence individual drivers. The fourth application is prioritizing and optimizing path selection preferences and decisions. The fifth application is informing capability development and procurement decisions to build and sustain homeland security organizations. Each of these applications provides a unique perspective of a homeland security issue by comparing a range of potential future outcomes at a set number of intervals and by contrasting the relative resource requirements, opportunity costs, and effectiveness measures of alternative courses of action. These findings indicate that MPFA enhances analysts’ ability to generate tangible measures of success, identify vulnerabilities, select effective courses of action, prioritize future pathway preferences, and contribute to ongoing capability development in homeland security assessments.

Keywords: homeland security, intelligence, national security, operational design, strategic intelligence, strategic planning

Procedia PDF Downloads 139