Search results for: cognitive intelligence

Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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Solymorph, a kinetic building facade designed for optimal energy capture and architectural expression, is explored in this paper. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of novel facade systems is necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, Solymorph leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, 3D printing, and laser cutting, were utilized to fabricate the physical components. Finally, a modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of Solymorph to an existing library building at Politecnico di Milano is presented. The facade system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. Solymorph demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, Solymorph paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

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Authors: Jose L. Diego, Antonio Berlanga, Gregorio López, Diana López

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The Rayuela method is a success story, as it is part of a project selected by the European Commission to face the challenge launched by itself for achieving a better understanding of human factors, as well as social and organisational aspects that are able to solve issues in fighting against crime. Rayuela's method specifically focuses on the drivers of cyber criminality, including approaches to prevent, investigate, and mitigate cybercriminal behavior. As the internet has become an integral part of young people’s lives, they are the key target of the Rayuela method because they (as a victim or as a perpetrator) are the most vulnerable link of the chain. Considering the increased time spent online and the control of their internet usage and the low level of awareness of cyber threats and their potential impact, it is understandable the proliferation of incidents due to human mistakes. 51% of Europeans feel not well informed about cyber threats, and 86% believe that the risk of becoming a victim of cybercrime is rapidly increasing. On the other hand, Law enforcement has noted that more and more young people are increasingly committing cybercrimes. This is an international problem that has considerable cost implications; it is estimated that crimes in cyberspace will cost the global economy $445B annually. Understanding all these phenomena drives to the necessity of a shift in focus from sanctions to deterrence and prevention. As a research project, Rayuela aims to bring together law enforcement agencies (LEAs), sociologists, psychologists, anthropologists, legal experts, computer scientists, and engineers, to develop novel methodologies that allow better understanding the factors affecting online behavior related to new ways of cyber criminality, as well as promoting the potential of these young talents for cybersecurity and technologies. Rayuela’s main goal is to better understand the drivers and human factors affecting certain relevant ways of cyber criminality, as well as empower and educate young people in the benefits, risks, and threats intrinsically linked to the use of the Internet by playing, thus preventing and mitigating cybercriminal behavior. In order to reach that goal it´s necessary an interdisciplinary consortium (formed by 17 international partners) carries out researches and actions like Profiling and case studies of cybercriminals and victims, risk assessments, studies on Internet of Things and its vulnerabilities, development of a serious gaming environment, training activities, data analysis and interpretation using Artificial intelligence, testing and piloting, etc. For facilitating the real implementation of the Rayuela method, as a community policing strategy, is crucial to count on a Police Force with a solid background in trust-building and community policing in order to do the piloting, specifically with young people. In this sense, Valencia Local Police is a pioneer Police Force working with young people in conflict solving, through providing police mediation and peer mediation services and advice. As an example, it is an official mediation institution, so agreements signed by their police mediators have once signed by the parties, the value of a judicial decision.

Keywords: fight against crime and insecurity, avert and prepare young people against aggression, ICT, serious gaming and artificial intelligence against cybercrime, conflict solving and mediation with young people

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Authors: Yas Barzegar, Atrin Barzegar

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Drinking water quality assessment is a major issue today; technology and practices are continuously improving; Artificial Intelligence (AI) methods prove their efficiency in this domain. The current research seeks a hierarchical fuzzy model for predicting drinking water quality in Rome (Italy). The Mamdani fuzzy inference system (FIS) is applied with different defuzzification methods. The Proposed Model includes three fuzzy intermediate models and one fuzzy final model. Each fuzzy model consists of three input parameters and 27 fuzzy rules. The model is developed for water quality assessment with a dataset considering nine parameters (Alkalinity, Hardness, pH, Ca, Mg, Fluoride, Sulphate, Nitrates, and Iron). Fuzzy-logic-based methods have been demonstrated to be appropriate to address uncertainty and subjectivity in drinking water quality assessment; it is an effective method for managing complicated, uncertain water systems and predicting drinking water quality. The FIS method can provide an effective solution to complex systems; this method can be modified easily to improve performance.

Keywords: water quality, fuzzy logic, smart cities, water attribute, fuzzy inference system, membership function

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Authors: Rasika Dayarathna

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Computing has reached every corner of our lives in many forms. The Internet, particularly Social Media, Artificial Intelligence, are prominent among them. As a result, computing has changed our lives and it is expected that severe changes will take place in the coming years. It has introduced a new set of ethical challenges and amplified the existing ethical challenges. It is the duty of everyone involved from conceptualizing, designing, implementing, deploying, and using to follow generally accepted practices in order to avoid or minimize harm and improve the quality of life. Since computing in various forms mentioned above has a significant impact on our lives, various codes of conduct and standards have been introduced. Among many, the ACM (Association of Computing Machinery) Code of Ethics and Professional Conduct is a leading one. This was drafted for everyone, including aspiring computing professionals. However, teaching a code of conduct for aspiring computing professionals is very challenging since this universal code needs to be taught for young computing professionals in a local setting where there are value mismatches and exposure to information systems. This paper discusses the importance of teaching the code, how to overcome the challenges, and suggestions to improve the code to make it more appealing and buying in. It is expected that the improved approach would contribute to improving the quality of life.

Keywords: code of conduct, professionalism, ethics, code of ethics, ethics education, moral development

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Authors: Azwan Hamdan, Mohd Qayyum Ab Latip, Hasliza Abu Hassim, Tengku Rinalfi Putra Tengku Azizan, Hafandi Ahmad

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Animal cognition provides some evidence for self-recognition, which is described as the ability to recognize oneself as an individual separate from the environment and other individuals. The mirror self-recognition (MSR) or mark test is a behavioral technique to determine whether an animal have the ability of self-recognition or self-awareness in front of the mirror. It also describes the capability for an animal to be aware of and make judgments about its new environment. Thus, the objectives of this study are to measure and to compare the ability of wild and captive wildlife in mirror self-recognition. Wild animals from the Royal Belum Rainforest Malaysia were identified based on the animal trails and salt lick grounds. Acrylic mirrors with wood frame (200 x 250cm) were located near to animal trails. Camera traps (Bushnell, UK) with motion-detection infrared sensor are placed near the animal trails or hiding spot. For captive wildlife, animals such as Malayan sun bear (Helarctos malayanus) and chimpanzee (Pan troglodytes) were selected from Zoo Negara Malaysia. The captive animals were also marked using odorless and non-toxic white paint on its forehead. An acrylic mirror with wood frame (200 x 250cm) and a video camera were placed near the cage. The behavioral data were analyzed using ethogram and classified through four stages of MSR; social responses, physical inspection, repetitive mirror-testing behavior and realization of seeing themselves. Results showed that wild animals such as barking deer (Muntiacus muntjak) and long-tailed macaque (Macaca fascicularis) increased their physical inspection (e.g inspecting the reflected image) and repetitive mirror-testing behavior (e.g rhythmic head and leg movement). This would suggest that the ability to use a mirror is most likely related to learning process and cognitive evolution in wild animals. However, the sun bear’s behaviors were inconsistent and did not clearly undergo four stages of MSR. This result suggests that when keeping Malayan sun bear in captivity, it may promote communication and familiarity between conspecific. Interestingly, chimp has positive social response (e.g manipulating lips) and physical inspection (e.g using hand to inspect part of the face) when they facing a mirror. However, both animals did not show any sign towards the mark due to lost of interest in the mark and realization that the mark is inconsequential. Overall, the results suggest that the capacity for MSR is the beginning of a developmental process of self-awareness and mental state attribution. In addition, our findings show that self-recognition may be based on different complex neurological and level of encephalization in animals. Thus, research on self-recognition in animals will have profound implications in understanding the cognitive ability of an animal as an effort to help animals, such as enhanced management, design of captive individuals’ enclosures and exhibits, and in programs to re-establish populations of endangered or threatened species.

Keywords: mirror self-recognition (MSR), self-recognition, self-awareness, wildlife

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Authors: Alfons Aziz Asaad Hozain

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The goal of sustainable architecture is to design buildings that have the least negative impact on the environment and provide better conditions for people. What forms of development enhance the area? This question was asked at the Center for the Study of Spatial Development and Building Forms in Cambridge in the late 1960s. This has resulted in many influential articles that have had a profound impact on the practice of urban planning. This article focuses on the sustainability outcomes caused by the climatic conditions of traditional Iranian architecture in hot and dry regions. Since people spend a lot of time at home, it is very important that these homes meet their physical and spiritual needs as well as the cultural and religious aspects of their lifestyle. In a country as large as Iran with different climates, traditional builders have put forward a number of logical solutions to ensure human comfort. With these solutions, the environmental problems of the have long been solved. Taking into account the experiences of traditional architecture in Iran's hot and dry climate, sustainable architecture can be achieved.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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Authors: Fevy Kae Mateo, Kimberly Javier, Alyzza Marie Palles

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Leadership is a process of relationship involving interaction with other people. Leaders emphasise authority, which executes and implements regulations, maintains the rules and leads to a better future. The First Time voters are very significant because there are the stakeholders of the type of leader to be deployed. They also have the capacity of engaging the government and can be the agents of change. The objective of the study is to identify the strengths and weaknesses of leader. Moreover, the study identifies the qualities of a leader. Finally, the study determines first-time voter’s representation of a leader. Focus Group Discussion was carried out into two groups of first time voter’s ages 18 to 21 years old. Verbatim transcripts of the discussion were analyzed using Thematic Analysis. Overall results showed super ordinate themes for weaknesses of leader: Lace of transparency in the government, poor communication strategy, and valuing experience over potential and other contributory factor; for strength of a leader: analytical skill, emotional intelligence in political work, analytical ability and economic status on political participation; finally, in the representation of a leader: positive representation of a leader and negative representation of a leader.

Keywords: first time voters, focus group discussion, leadership, qualitative research design

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Sana Sayed

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The words objectives, outcomes, and assessment are commonplace in academia. Educators, especially those who use their emotional intelligence as a useful teaching tool, strive to find creative and innovative ways to connect to their students while meeting the objectives, outcomes, and assessment measures for their respective courses. However, what happens to these outcomes once the objectives have been met, students have completed a specific course, and generic letter grades have been generated? How can their knowledge and acquired skills be assessed over the course of semesters, throughout their years of study, and until their final year right before they graduate? Considering the courses students complete for different departments in various disciplines, how can these outcomes be measured, or at least maintained, across the curriculum? This research-driven paper uses the key course outcomes of first year, required writing courses and traces them in two senior level, required civil engineering design courses at the American University of Sharjah, which is located in the United Arab Emirates. The purpose of this research is two-fold: (1) to assess specific learning outcomes using a case study that focuses on courses from two different disciplines during two very distinctive years of study, and (2) to demonstrate how learning across the curriculum fosters life-long proficiencies among graduating students that are aligned with a university’s mission statement.

Keywords: assessment, learning across the curriculum, objectives, outcomes

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Authors: Anastasia V. Kovaleva, Alena A. Ryabova, Vladimir N. Kasatkin

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Background: The most simple form of entrainment to a sensory (typically auditory) rhythmic stimulus involves perceiving and synchronizing movements with an isochronous beat with one level of periodicity, such as that produced by a metronome. Children with pediatric cancer usually treated with chemo- and radiotherapy. Because of such treatment, psychologists and health professionals declare cognitive and motor abilities decline in cancer patients. The purpose of our study was to measure working memory characteristics with association with audio-motor synchronization tasks, also involved some memory resources, in children with different degrees of central nervous system lesions: posterior fossa tumors, acute lymphoblastic leukemia, and healthy controls. Methods: Our sample consisted of three groups of children: children treated for posterior fossa tumors (PFT-group, n=42, mean age 12.23), children treated for acute lymphoblastic leukemia (ALL-group, n=11, mean age 11.57) and neurologically healthy children (control group, n=36, mean age 11.67). Participants were tested for working memory characteristics with Cambridge Neuropsychological Test Automated Battery (CANTAB). Pattern recognition memory (PRM) and spatial working memory (SWM) tests were applied. Outcome measures of PRM test include the number and percentage of correct trials and latency (speed of participant’s response), and measures of SWM include errors, strategy, and latency. In the synchronization tests, the instruction was to tap out a regular beat (40, 60, 90 and 120 beats per minute) in synchrony with the rhythmic sequences that were played. This meant that for the sequences with an isochronous beat, participants were required to tap into every auditory event. Variations of inter-tap-intervals and deviations of children’s taps from the metronome were assessed. Results: Analysis of variance revealed the significant effect of group (ALL, PFT and control) on such parameters as short-term PRM, SWM strategy and errors. Healthy controls demonstrated more correctly retained elements, better working memory strategy, compared to cancer patients. Interestingly that ALL patients chose the bad strategy, but committed significantly less errors in SWM test then PFT and controls did. As to rhythmic ability, significant associations of working memory were found out only with 40 bpm rhythm: the less variable were inter-tap-intervals of the child, the more elements in memory he/she could retain. The ability to audio-motor synchronization may be related to working memory processes mediated by the prefrontal cortex whereby each sensory event is actively retrieved and monitored during rhythmic sequencing. Conclusion: Our results suggest that working memory, tested with appropriate cognitive methods, is associated with the ability to synchronize movements with rhythmic sounds, especially in sub-second intervals (40 per minute).

Keywords: acute lymphoblastic leukemia (ALL), audio-motor synchronization, posterior fossa tumor, working memory

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Authors: Shreyas Kumar, Mili Shangari

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Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

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Authors: Dimitris E. Kontaxis, George Litainas, Dimitris P. Ptochos

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Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real-time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination, and sustainability of the supply chain procedures. The technology, the features, and the characteristics of a complete, proprietary system, including hardware, firmware, and software tools -developed in the context of a co-funded R&D programme- are addressed and presented in this paper.

Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Thammarak Srimarut, Witthaya Mekhum

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This study analysed and developed a model for monk’s food bowl production on occupational health safety and environment at work for the encouragement of Rattanakosin local wisdom at Banbart Community. The process of blowpipe welding was necessary to produce the bowl which was very dangerous or 93.59% risk. After the employment of new sitting posture, the work risk was lower 48.41% or moderate risk. When considering in details, it was found that: 1) the traditional sitting posture could create work risk at 88.89% while the new sitting posture could create the work risk at 58.86%. 2) About the environmental pollution, with the traditional sitting posture, workers exposed to the polluted fume from welding at 61.11% while with the new sitting posture workers exposed to the polluted fume from welding at 40.47%. 3) On accidental risk, with the traditional sitting posture, workers exposed to the accident from welding at 94.44% while with the new sitting posture workers exposed to the accident from welding at 62.54%.

Keywords: occupational health safety, environment at work, Monk’s food bowl, machine intelligence

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Authors: Carla Van De Sande, Jana Vandenberg

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Just like physical skills, cognitive skills grow rusty over time unless they are regularly used and practiced, so academic breaks can have negative consequences on student learning and success. The Keeping in School Shape (KiSS) program is an engaging, accessible, and cost-effective intervention that harnesses the benefits of retrieval practice by using technology to help students maintain proficiency over breaks from school by delivering a daily review problem via text message or email. A growth mindset is promoted through feedback messages encouraging students to try again if they get a problem wrong and to take on a challenging problem if they get a problem correct. This paper reports on the relationship between confidence, accuracy, and decision-making during the implementation of the KiSS Program at a large university during winter break for students enrolled in an engineering introductory Calculus course sequence.

Keywords: growth mindset, learning loss, on-the-go learning, retrieval practice

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Authors: Hyeon-Kyo Lim, Sang-Hun Byun

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Risk assessment is carried out in most industrial plants for accident prevention, but there exists insufficient data for statistical decision making. It is commonly said that risk can be expressed as a product of consequence and likelihood of a corresponding hazard factor. Eventually, therefore, risk assessment involves human decision making which cannot be objective per se. This study was carried out to comprehend perceptive characteristics of human beings in industrial plants. Subjects were shown a set of illustrations describing scenes of industrial plants, and were asked to assess the risk of each scene with not only linguistic variables but also numeric scores in the aspect of consequence and likelihood. After that, their responses were formulated as fuzzy membership functions, and compared with those of university students who had no experience of industrial works. The results showed that risk level of industrial workers were lower than those of any other groups, which implied that the workers might generally have a tendency to neglect more hazard factors in their work fields.

Keywords: fuzzy, hazard, linguistic variable, risk assessment

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Rob Gesley Capistrano, Jasper James Isaac, Rose Mae Moralda, Therese Anne Peleo, Danica Rillo, Maria Virginia Santillian

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One of the valuable things that shows the intelligence among individuals is the academic background specifically their Grade Weighted Average and the significant result of the Comprehensive Examination. The general objective of the researchers to this study is to determine if there is a significant difference between General Weighted Average and Comprehensive Examination Result of Psychometrician Board Passers and Non-Board Passers. The respondents of this study composed of board passers and non-board passers. The researchers used purposive sampling technique. The result utilized by using T-test Independent Sample to determine the comparison of General Weighted Average and Comprehensive Examination Result of Board Passers and Non Board Passers. At the end, it concluded that the General Weighted Average of Board Passers and Non-Board Passers shows that there is no significant difference, but the average showed a minimal variation. The Comprehensive Examination Result of Board Passers and Non-Board Passers result revealed that there is a significant difference. The performance of comprehensive examination that will test the overall knowledge of an individual and will determine whose more proficient will likely to have a higher score. The result of the comprehensive examination had an impact in the passing performance of board examination.

Keywords: board passers, comprehensive examination result, grade weighted average, non board passers

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Authors: Sadaf Nawaz, Adnan Ahmed Khan, Asad Mahmood, Chaudhary Farrukh Javed

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Classically, an energy detector is implemented in time domain (TD). However, frequency domain (FD) based energy detector has demonstrated an improved performance. This paper presents a comparison between the two approaches as to analyze their pros and cons. A detailed performance analysis of the classical TD energy-detector and the periodogram based detector is performed. Exact and approximate mathematical expressions for probability of false alarm (Pf) and probability of detection (Pd) are derived for both approaches. The derived expressions naturally lead to an analytical as well as intuitive reasoning for the improved performance of (Pf) and (Pd) in different scenarios. Our analysis suggests the dependence improvement on buffer sizes. Pf is improved in FD, whereas Pd is enhanced in TD based energy detectors. Finally, Monte Carlo simulations results demonstrate the analysis reached by the derived expressions.

Keywords: cognitive radio, energy detector, periodogram, spectrum sensing

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Authors: Raymond C. Hawkins II, Catherine A. Hawkins

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The System Contextual Integrated Model (SCIM), developed as a trans-theoretical framework for selecting measures for psychotherapy process and outcome, is reformulated for behavioral health applications. The SCIM “healing cycle” is an allostatic hedonic affective-cognitive right-hemisphere–left-hemisphere coordinated process involving positive alliesthesia that mitigates traumatic pain and generates psychological flexibility. The SCIM “trauma cycle” is an allostatic overload alliesthesia opponent process with long-lasting pathology sequelae. The social ecological context moderates the “healing cycle” and the “trauma cycle.” Repeated evocation of the “healing cycle” in a therapeutic relationship can gradually relieve trauma sequelae. The SCIM is applied to pain, obese binge eating, and substance use disorders.

Keywords: allostasis, alliesthesia, opponent process, behavioral health, assessment

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Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

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Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: uncoupled design, axiomatic design, nature design, design evaluation

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: clustering analysis, community of practice, data mining, higher education, new faculty challenges, social network, social influence, professional development

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Authors: Zhang Tianci, Ding Meng, Zuo Hongfu, Zeng Lina, Sun Zejun

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Automation of airport operations can greatly improve ground movement efficiency. In this paper, we study the speed profile design problem for advanced airport ground movement control and guidance. The problem is constrained by the surface four-dimensional trajectory generated in taxi planning. A decomposed approach of two stages is presented to solve this problem efficiently. In the first stage, speeds are allocated at control points which ensure smooth speed profiles can be found later. In the second stage, detailed speed profiles of each taxi interval are generated according to the allocated control point speeds with the objective of minimizing the overall fuel consumption. We present a swarm intelligence based algorithm for the first-stage problem and a discrete variable driven enumeration method for the second-stage problem since it only has a small set of discrete variables. Experimental results demonstrate the presented methodology performs well on real world speed profile design problems.

Keywords: airport ground movement, fuel consumption, particle swarm optimization, smoothness, speed profile design

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Authors: Chin Tangtarntana

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The main purpose of this study was to investigate the effects of animation in offensive product advertising. Experiment was conducted to collect consumer responses toward animated and static ads of offensive and non-offensive products. The study was conducted by distributing questionnaires to the target respondents. According to statistics from Innovative Internet Research Center, Thailand, majority of internet users are 18 – 44 years old. The results revealed an interaction between ad design and offensive product. Specifically, when used in offensive product advertisements, animated ads were not effective for consumer attention, but yielded positive response in terms of attitude toward product. The findings support that information processing model is accurate in predicting consumer cognitive response toward cartoon ads, whereas U&G, arousal, and distinctive theory is more accurate in predicting consumer affective response. In practical, these findings can also be used to guide ad designers and marketers that are suitable for offensive products.

Keywords: animation, banner ad design, consumer responses, offensive product advertising, stock exchange of Thailand

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Authors: Azza A. Ali, Abeer I. Abd El-Fattah, Shaimaa S. Hussein, Hanan A. Abd El-Samea, Karema Abu-Elfotuh

Abstract:

Background: Aluminium (Al) represents an environmental risk factor. Exposure to high levels of Al causes neurotoxic effects and different diseases. Vinpocetine is widely used to improve cognitive functions, it possesses memory-protective and memory-enhancing properties and has the ability to increase cerebral blood flow and glucose uptake. Cocoa bean represents a rich source of iron as well as a potent antioxidant. It can protect from the impact of free radicals, reduces stress as well as depression and promotes better memory and concentration. Wheatgrass is primarily used as a concentrated source of nutrients. It contains vitamins, minerals, carbohydrates, amino acids and possesses antioxidant and anti-inflammatory activities. Coenzyme Q10 (CoQ10) is an intracellular antioxidant and mitochondrial membrane stabilizer. It is effective in improving cognitive disorders and has been used as anti-aging. Zinc is a structural element of many proteins and signaling messenger that is released by neural activity at many central excitatory synapses. Objective: To study the role of some nutrients and drugs as Vinpocetine, Cocoa, Wheatgrass, CoQ10 and Zinc against neurotoxicity induced by Al in rats as well as to compare between their potency in providing protection. Methods: Seven groups of rats were used and received daily for three weeks AlCl3 (70 mg/kg, IP) for Al-toxicity model groups except for the control group which received saline. All groups of Al-toxicity model except one group (non-treated) were co-administered orally together with AlCl3 the following treatments; Vinpocetine (20mg/kg), Cocoa powder (24mg/kg), Wheat grass (100mg/kg), CoQ10 (200mg/kg) or Zinc (32mg/kg). Biochemical changes in the rat brain as acetyl cholinesterase (ACHE), Aβ, brain derived neurotrophic factor (BDNF), inflammatory mediators (TNF-α, IL-1β), oxidative parameters (MDA, SOD, TAC) were estimated for all groups besides histopathological examinations in different brain regions. Results: Neurotoxicity and neurodegenerations in the rat brain after three weeks of Al exposure were indicated by the significant increase in Aβ, ACHE, MDA, TNF-α, IL-1β, DNA fragmentation together with the significant decrease in SOD, TAC, BDNF and confirmed by the histopathological changes in the brain. On the other hand, co-administration of each of Vinpocetine, Cocoa, Wheatgrass, CoQ10 or Zinc together with AlCl3 provided protection against hazards of neurotoxicity and neurodegenerations induced by Al, their protection were indicated by the decrease in Aβ, ACHE, MDA, TNF-α, IL-1β, DNA fragmentation together with the increase in SOD, TAC, BDNF and confirmed by the histopathological examinations of different brain regions. Vinpocetine and Cocoa showed the most pronounced protection while Zinc provided the least protective effects than the other used nutrients and drugs. Conclusion: Different degrees of protection from neurotoxicity and neuronal degenerations induced by Al could be achieved through the co-administration of some nutrients and drugs during its exposure. Vinpocetine and Cocoa provided the most protection than Wheat grass, CoQ10 or Zinc which showed the least protective effects.

Keywords: aluminum, neurotoxicity, vinpocetine, cocoa, wheat grass, coenzyme Q10, Zinc, rats

Procedia PDF Downloads 241

Authors: A. Bortkiewcz, A. Dudarewicz, P. Małecki, M. Kłaczyński, T. Wszołek, Małgorzata Pawlaczyk-Łuszczyńska

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Low-frequency noise (LFN) has been recognized as a special environmental pollutant. It is usually considered a broadband noise with the dominant content of low frequencies from 10 Hz to 250 Hz. A growing body of data shows that LFN differs in nature from other environmental noises, which are at comparable levels but not dominated by low-frequency components. The primary and most frequent adverse effect of LFN exposure is annoyance. Moreover, some recent investigations showed that LFN at relatively low A-weighted sound pressure levels (40−45 dB) occurring in office-like areas could adversely affect the mental performance, especially of high-sensitive subjects. It is well documented that high-frequency noise disturbs various types of human functions; however, there is very little data on the impact of LFN on well-being and health, including the cardiovascular system. Heart rate variability (HRV) is a sensitive marker of autonomic regulation of the circulatory system. Walker and co-workers found that LFN has a significantly more negative impact on cardiovascular response than exposure to high-frequency noise and that changes in HRV parameters resulting from LFN exposure tend to persist over time. The negative reactions of the cardiovascular system in response to LFN generated by wind turbines (20-200 Hz) were confirmed by Chiu. The scientific aim of the study is to assess the relationship between the spectral-temporal characteristics of LFN and the activity of the autonomic nervous system, considering the subjective assessment of annoyance, sensitivity to this type of noise, and cognitive and general health status. The study will be conducted in 20 male students in a special, acoustically prepared, constantly supervised room. Each person will be tested 4 times (4 sessions), under conditions of non-exposure (sham) and exposure to noise of wind turbines recorded at a distance of 250 meters from the turbine with different frequencies and frequency ranges: acoustic band 20 Hz-20 kHz, infrasound band 5-20 Hz, acoustic band + infrasound band. The order of sessions of the experiment will be randomly selected. Each session will last 1 h. There will be a 2-3 days break between sessions to exclude the possibility of the earlier session influencing the results of the next one. Before the first exposure, a questionnaire will be conducted on noise sensitivity, general health status using the GHQ questionnaire, hearing organ status and sociodemographic data. Before each of the 4 exposures, subjects will complete a brief questionnaire on their mood and sleep quality the night before the test. After the test, the subjects will be asked about any discomfort and subjective symptoms during the exposure. Before the test begins, Holter ECG monitoring equipment will be installed. HRV will be analyzed from the ECG recordings, including time and frequency domain parameters. The tests will always be performed in the morning (9-12) to avoid the influence of diurnal rhythm on HRV results. Students will perform psychological tests 15 minutes before the end of the test (Vienna Test System).

Keywords: neurovegetative control, heart rate variability (HRV), cognitive processes, low frequency noise

Procedia PDF Downloads 68

Authors: Dulanjali Ranasinghe, Isuru Supasan, Kaushalya Premachandra, Ranjan Dissanayake, Ajith Rajapaksha, Eustace Fernando

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Proteomics studies of organisms are considered to be significantly information-rich compared to their genomic counterparts because proteomes of organisms represent the expressed state of all proteins of an organism at a given time. In modern top-down and bottom-up proteomics workflows, the primary analysis methods employed are gel–based methods such as two-dimensional (2D) electrophoresis and mass spectrometry based methods. Machine learning (ML) and artificial intelligence (AI) have been used increasingly in modern biological data analyses. In particular, the fields of genomics, DNA sequencing, and bioinformatics have seen an incremental trend in the usage of ML and AI techniques in recent years. The use of aforesaid techniques in the field of proteomics studies is only beginning to be materialised now. Although there is a wealth of information available in the scientific literature pertaining to proteomics workflows, no comprehensive review addresses various aspects of the combined use of proteomics and machine learning. The objective of this review is to provide a comprehensive outlook on the application of machine learning into the known proteomics workflows in order to extract more meaningful information that could be useful in a plethora of applications such as medicine, agriculture, and biotechnology.

Keywords: proteomics, machine learning, gel-based proteomics, mass spectrometry

Procedia PDF Downloads 138

Authors: Roberta Martino, Viviana Ventre

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The Discounted Utility Model is the essential reference for calculating the utility of intertemporal prospects. According to this model, the value assigned to an outcome is the smaller the greater the distance between the moment in which the choice is made and the instant in which the outcome is perceived. This diminution determines the intertemporal preferences of the individual, the psychological significance of which is encapsulated in the discount rate. The classic model provides a discount rate of linear or exponential nature, necessary for temporally consistent preferences. Empirical evidence, however, has proven that individuals apply discount rates with a hyperbolic nature generating the phenomenon of intemporal inconsistency. What this means is that individuals have difficulty managing their money and future. Behavioral finance, which analyzes the investor's attitude through cognitive psychology, has made it possible to understand that beyond individual financial competence, there are factors that condition choices because they alter the decision-making process: behavioral bias. Since such cognitive biases are inevitable, to improve the quality of choices, research has focused on a personalized approach to strategies that combines behavioral finance with personality theory. From the considerations, it emerges the need to find a procedure to construct the personalized strategies that consider the personal characteristics of the client, such as age or gender, and his personality. The work is developed in three parts. The first part discusses and investigates the weight of the degree of impatience and impatience decrease in the anomalies of the discounted utility model. Specifically, the degree of decrease in impatience quantifies the impact that emotional factors generated by haste and financial market agitation have on decision making. The second part considers the relationship between decision making and personality theory. Specifically, four behavioral categories associated with four categories of behavioral investors are considered. This association allows us to interpret intertemporal choice as a combination of bias and temperament. The third part of the paper presents a method for constructing personalized strategies using Analytic Hierarchy Process. Briefly: the first level of the analytic hierarchy process considers the goal of the strategic plan; the second level considers the four temperaments; the third level compares the temperaments with the anomalies of the discounted utility model; and the fourth level contains the different possible alternatives to be selected. The weights of the hierarchy between level 2 and level 3 are constructed considering the degrees of decrease in impatience derived for each temperament with an experimental phase. The results obtained confirm the relationship between temperaments and anomalies through the degree of decrease in impatience and highlight that the actual impact of emotions in decision making. Moreover, it proposes an original and useful way to improve financial advice. Inclusion of additional levels in the Analytic Hierarchy Process can further improve strategic personalization.

Keywords: analytic hierarchy process, behavioral finance anomalies, intertemporal choice, personalized strategies

Procedia PDF Downloads 84

Authors: Sandhya Rao Mehta

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As ChatGpt and other Artificial Intelligence (AI) forms are becoming part of our regular academic world, the consequences are being gradually discussed. The extent to which an essay written by a student is itself of any value if it has been downloaded by some form of AI is perhaps central to this discourse. A larger question is whether writing should be taught as an academic skill at all. In literature classrooms, this has major consequences as writing a traditional paper is still the single most preferred form of assessment. This study suggests that it is imperative to investigate alternative forms of assessment in literature, not only because the existing forms can be written by AI, but in a larger sense, students are increasingly skeptical of the purpose of such work. The extent to which an essay actually helps the students professionally is a question that academia has not yet answered. This paper suggests that using real-world tasks like creating podcasts, video tutorials, and websites is a far better way to evaluate students' critical thinking and application of ideas, as well as to develop digital skills which are important to their future careers. Using the example of a course in literature, this study will examine the possibilities and challenges of creating digital projects as a way of confronting the complexities of student evaluation in the future. The study is based on a specific university English as a Foreign Language (EFL) context.

Keywords: assessment, literature, digital humanities, chatgpt

Procedia PDF Downloads 71

Authors: V. S. S. Kumar, V. Ramya

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In the modern electronic warfare, the signal scenario is changing at a rapid pace with the introduction of Low Probability of Intercept (LPI) radars. In the modern battlefield, radar system faces serious threats from passive intercept receivers such as Electronic Attack (EA) and Anti-Radiation Missiles (ARMs). To perform necessary target detection and tracking and simultaneously hide themselves from enemy attack, radar systems should be LPI. These LPI radars use a variety of complex signal modulation schemes together with pulse compression with the aid of advancement in signal processing capabilities of the radar such that the radar performs target detection and tracking while simultaneously hiding enemy from attack such as EA etc., thus posing a major challenge to the ES/ELINT receivers. Today an increasing number of LPI radars are being introduced into the modern platforms and weapon systems so these LPI radars created a requirement for the armed forces to develop new techniques, strategies and equipment to counter them. This paper presents various modulation techniques used in generation of LPI signals and development of Time Frequency Algorithms to analyse those signals.

Keywords: anti-radiation missiles, cross terms, electronic attack, electronic intelligence, electronic warfare, intercept receiver, low probability of intercept

Procedia PDF Downloads 453