Search results for: vulnerability intelligence
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2259

Search results for: vulnerability intelligence

309 The Effect of Artificial Intelligence on Electric Machines and Welding

Authors: Mina Malak Zakaria Henin

Abstract:

The finite detail evaluation of magnetic fields in electromagnetic devices shows that the machine cores revel in extraordinary flux patterns consisting of alternating and rotating fields. The rotating fields are generated in different configurations variety, among circular and elliptical, with distinctive ratios between the fundamental and minor axes of the flux locus. Experimental measurements on electrical metal uncovered one-of-a-kind flux patterns that divulge distinctive magnetic losses in the samples below the test. Therefore, electric machines require unique interest throughout the core loss calculation technique to bear in mind the flux styles. In this look, a circular rotational unmarried sheet tester is employed to measure the middle losses in the electric-powered metallic pattern of M36G29. The sample becomes exposed to alternating fields, circular areas, and elliptical fields with axis ratios of zero.2, zero. Four, 0.6 and 0.8. The measured statistics changed into applied on 6-4 switched reluctance motors at 3 distinctive frequencies of interest to the industry 60 Hz, 400 Hz, and 1 kHz. The effects reveal an excessive margin of error, which can arise at some point in the loss calculations if the flux pattern difficulty is overlooked. The mistake in exceptional components of the gadget associated with considering the flux styles may be around 50%, 10%, and a couple of at 60Hz, 400Hz, and 1 kHz, respectively. The future paintings will focus on the optimization of gadget geometrical shape, which has a primary effect on the flux sample on the way to decrease the magnetic losses in system cores.

Keywords: converters, electric machines, MEA (more electric aircraft), PES (power electronics systems) synchronous machine, vector control Multi-machine/ Multi-inverter, matrix inverter, Railway tractionalternating core losses, finite element analysis, rotational core losses

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308 Information Visualization Methods Applied to Nanostructured Biosensors

Authors: Osvaldo N. Oliveira Jr.

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The control of molecular architecture inherent in some experimental methods to produce nanostructured films has had great impact on devices of various types, including sensors and biosensors. The self-assembly monolayers (SAMs) and the electrostatic layer-by-layer (LbL) techniques, for example, are now routinely used to produce tailored architectures for biosensing where biomolecules are immobilized with long-lasting preserved activity. Enzymes, antigens, antibodies, peptides and many other molecules serve as the molecular recognition elements for detecting an equally wide variety of analytes. The principles of detection are also varied, including electrochemical methods, fluorescence spectroscopy and impedance spectroscopy. In this presentation an overview will be provided of biosensors made with nanostructured films to detect antibodies associated with tropical diseases and HIV, in addition to detection of analytes of medical interest such as cholesterol and triglycerides. Because large amounts of data are generated in the biosensing experiments, use has been made of computational and statistical methods to optimize performance. Multidimensional projection techniques such as Sammon´s mapping have been shown more efficient than traditional multivariate statistical analysis in identifying small concentrations of anti-HIV antibodies and for distinguishing between blood serum samples of animals infected with two tropical diseases, namely Chagas´ disease and Leishmaniasis. Optimization of biosensing may include a combination of another information visualization method, the Parallel Coordinate technique, with artificial intelligence methods in order to identify the most suitable frequencies for reaching higher sensitivity using impedance spectroscopy. Also discussed will be the possible convergence of technologies, through which machine learning and other computational methods may be used to treat data from biosensors within an expert system for clinical diagnosis.

Keywords: clinical diagnosis, information visualization, nanostructured films, layer-by-layer technique

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307 Body of Dialectics: Exploring a Dynamic-Adaptational Model of Physical Self-Integrity and the Pursuit of Happiness in a Hostile World

Authors: Noam Markovitz

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People with physical disabilities constitute a very large and simultaneously a diverse group of general population, as the term physical disabilities is extensive and covers a wide range of disabilities. Therefore, individuals with physical disabilities are often faced with a new, threatening and stressful reality leading possibly to a multi-crisis in their lives due to the great changes they experience in somatic, socio-economic, occupational and psychological level. The current study seeks to advance understanding of the complex adaptation to physical disabilities by expanding the dynamic-adaptational model of the pursuit of happiness in a hostile world with a new conception of physical self-integrity. Physical self-integrity incorporates an objective dimension, namely physical self-functioning (PSF), and a subjective dimension, namely physical self-concept (PSC). Both of these dimensions constitute an experience of wholeness in the individual’s identification with her or his physical body. The model guiding this work is dialectical in nature and depicts two systems in the individual’s sense of happiness: subjective well-being (SWB) and meaning in life (MIL). Both systems serve as self-adaptive agents that moderate the complementary system of the hostile-world scenario (HWS), which integrates one’s perceived threats to one’s integrity. Thus, in situations of increased HWS, the moderation may take a form of joint activity in which SWB and MIL are amplified or a form of compensation in which one system produces a stronger effect while the other system produces a weaker effect. The current study investigated PSC in relations to SWB and MIL through pleasantness and meanings that are physically or metaphorically grounded in one’s body. In parallel, PSC also relates to HWS by activating representations of inappropriateness, deformation and vulnerability. In view of possibly dialectical positions of opposing and complementary forces within the current model, the current field study that aims to explore PSC as appearing in an independent, cross-sectional, design addressing the model’s variables in a focal group of people with physical disabilities. This study delineated the participation of the PSC in the adaptational functions of SWB and MIL vis-à-vis HWS-related life adversities. The findings showed that PSC could fully complement the main variables of the pursuit of happiness in a hostile world model. The assumed dialectics in the form of a stronger relationship between SWB and MIL in the face of physical disabilities was not supported. However, it was found that when HWS increased, PSC and MIL were strongly linked, whereas PSC and SWB were weakly linked. This highlights the compensatory role of MIL. From a conceptual viewpoint, the current investigation may clarify the role of PSC as an adaptational agent of the individual’s positive health in complementary senses of bodily wholeness. Methodologically, the advantage of the current investigation is the application of an integrative, model-based approach within a specially focused design with a particular relevance to PSC. Moreover, from an applicative viewpoint, the current investigation may suggest how an innovative model may be translated to therapeutic interventions used by clinicians, counselors and practitioners in improving wellness and psychological well-being, particularly among people with physical disabilities.

Keywords: older adults, physical disabilities, physical self-concept, pursuit of happiness in a hostile-world

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306 Pushover Analysis of a Typical Bridge Built in Central Zone of Mexico

Authors: Arturo Galvan, Jatziri Y. Moreno-Martinez, Daniel Arroyo-Montoya, Jose M. Gutierrez-Villalobos

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Bridges are one of the most seismically vulnerable structures on highway transportation systems. The general process for assessing the seismic vulnerability of a bridge involves the evaluation of its overall capacity and demand. One of the most common procedures to obtain this capacity is by means of pushover analysis of the structure. Typically, the bridge capacity is assessed using non-linear static methods or non-linear dynamic analyses. The non-linear dynamic approaches use step by step numerical solutions for assessing the capacity with the consuming computer time inconvenience. In this study, a nonlinear static analysis (‘pushover analysis’) was performed to predict the collapse mechanism of a typical bridge built in the central zone of Mexico (Celaya, Guanajuato). The bridge superstructure consists of three simple supported spans with a total length of 76 m: 22 m of the length of extreme spans and 32 m of length of the central span. The deck width is of 14 m and the concrete slab depth is of 18 cm. The bridge is built by means of frames of five piers with hollow box-shaped sections. The dimensions of these piers are 7.05 m height and 1.20 m diameter. The numerical model was created using a commercial software considering linear and non-linear elements. In all cases, the piers were represented by frame type elements with geometrical properties obtained from the structural project and construction drawings of the bridge. The deck was modeled with a mesh of rectangular thin shell (plate bending and stretching) finite elements. The moment-curvature analysis was performed for the sections of the piers of the bridge considering in each pier the effect of confined concrete and its reinforcing steel. In this way, plastic hinges were defined on the base of the piers to carry out the pushover analysis. In addition, time history analyses were performed using 19 accelerograms of real earthquakes that have been registered in Guanajuato. In this way, the displacements produced by the bridge were determined. Finally, pushover analysis was applied through the control of displacements in the piers to obtain the overall capacity of the bridge before the failure occurs. It was concluded that the lateral deformation of the piers due to a critical earthquake occurred in this zone is almost imperceptible due to the geometry and reinforcement demanded by the current design standards and compared to its displacement capacity, they were excessive. According to the analysis, it was found that the frames built with five piers increase the rigidity in the transverse direction of the bridge. Hence it is proposed to reduce these frames of five piers to three piers, maintaining the same geometrical characteristics and the same reinforcement in each pier. Also, the mechanical properties of materials (concrete and reinforcing steel) were maintained. Once a pushover analysis was performed considering this configuration, it was concluded that the bridge would continue having a “correct” seismic behavior, at least for the 19 accelerograms considered in this study. In this way, costs in material, construction, time and labor would be reduced in this study case.

Keywords: collapse mechanism, moment-curvature analysis, overall capacity, push-over analysis

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305 Leveraging on Application of Customer Relationship Management Strategy as Business Driving Force: A Case Study of Major Industries

Authors: Odunayo S. Faluse, Roger Telfer

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Customer relationship management is a business strategy that is centred on the idea that ‘Customer is the driving force of any business’ i.e. Customer is placed in a central position in any business. However, this belief coupled with the advancement in information technology in the past twenty years has experienced a change. In any form of business today it can be concluded that customers are the modern dictators to whom the industry always adjusts its business operations due to the increase in availability of information, intense market competition and ever growing negotiating ideas of customers in the process of buying and selling. The most vital role of any organization is to satisfy or meet customer’s needs and demands, which eventually determines customer’s long-term value to the industry. Therefore, this paper analyses and describes the application of customer relationship management operational strategies in some of the major industries in business. Both developed and up-coming companies nowadays value the quality of customer services and client’s loyalty, they also recognize the customers that are not very sensitive when it comes to changes in price and thereby realize that attracting new customers is more tasking and expensive than retaining the existing customers. However, research shows that several factors have recently amounts to the sudden rise in the execution of CRM strategies in the marketplace, such as a diverted attention of some organization towards integrating ideas in retaining existing customers rather than attracting new one, gathering data about customers through the use of internal database system and acquiring of external syndicate data, also exponential increase in technological intelligence. Apparently, with this development in business operations, CRM research in Academia remain nascent; hence this paper gives detailed critical analysis of the recent advancement in the use of CRM and key research opportunities for future development in using the implementation of CRM as a determinant factor for successful business optimization.

Keywords: agriculture, banking, business strategies, CRM, education, healthcare

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304 Orbit Determination from Two Position Vectors Using Finite Difference Method

Authors: Akhilesh Kumar, Sathyanarayan G., Nirmala S.

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An unusual approach is developed to determine the orbit of satellites/space objects. The determination of orbits is considered a boundary value problem and has been solved using the finite difference method (FDM). Only positions of the satellites/space objects are known at two end times taken as boundary conditions. The technique of finite difference has been used to calculate the orbit between end times. In this approach, the governing equation is defined as the satellite's equation of motion with a perturbed acceleration. Using the finite difference method, the governing equations and boundary conditions are discretized. The resulting system of algebraic equations is solved using Tri Diagonal Matrix Algorithm (TDMA) until convergence is achieved. This methodology test and evaluation has been done using all GPS satellite orbits from National Geospatial-Intelligence Agency (NGA) precise product for Doy 125, 2023. Towards this, two hours of twelve sets have been taken into consideration. Only positions at the end times of each twelve sets are considered boundary conditions. This algorithm is applied to all GPS satellites. Results achieved using FDM compared with the results of NGA precise orbits. The maximum RSS error for the position is 0.48 [m] and the velocity is 0.43 [mm/sec]. Also, the present algorithm is applied on the IRNSS satellites for Doy 220, 2023. The maximum RSS error for the position is 0.49 [m], and for velocity is 0.28 [mm/sec]. Next, a simulation has been done for a Highly Elliptical orbit for DOY 63, 2023, for the duration of 6 hours. The RSS of difference in position is 0.92 [m] and velocity is 1.58 [mm/sec] for the orbital speed of more than 5km/sec. Whereas the RSS of difference in position is 0.13 [m] and velocity is 0.12 [mm/sec] for the orbital speed less than 5km/sec. Results show that the newly created method is reliable and accurate. Further applications of the developed methodology include missile and spacecraft targeting, orbit design (mission planning), space rendezvous and interception, space debris correlation, and navigation solutions.

Keywords: finite difference method, grid generation, NavIC system, orbit perturbation

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303 Upcoming Fight Simulation with Smart Shadow

Authors: Ramiz Kuliev, Fuad Kuliev-Smirnov

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The 'Shadow Sparring' training exercise is widely used in the training of boxers and martial artists. The main disadvantage of the usual shadow sparring is that the trainer cannot fully control such training and evaluate its results. During the competition, the athlete, preparing for the upcoming fight, imagines the Shadow (upcoming opponent) in accordance with his own imagination. A ‘Smart-Shadow Sparring’ (SSS) is an innovative version of the ‘Shadow Sparring’. During SSS, the fighter will see the Shadow (virtual opponent that moves, defends, and punches) and understand when he misses the punches from the Shadow. The task of a real athlete is to spar with a virtual one, move around, punch in the direction of unprotected areas of the Shadow and dodge his punches. Moves and punches of Shadow are set up before each training. The system will give the coach full information about virtual sparring: (i) how many and what type of punches has the fighter landed, (ii) accuracy of these punches, (iii) how many and what type of virtual punches (punches of Smart-Shadow) has the fighter missed, etc. SSS will be recorded as animated fighting of two fighters and will help the coach to analyze past training. SSS can be configured to fit the physical and technical characteristics of the next real opponent (size, techniques, speed, missed and landed punches, etc.). This will allow to simulate and rehearse the upcoming fight and improve readiness for the next opponent. For amateur fighters, SSS will be reconfigured several times during a tournament, when the real opponent becomes known. SSS can be used in three versions: (1) Digital Shadow: the athlete will see a Shadow on a monitor (2) VR-Shadow: the athlete will see a Shadow in a VR-glasses (3) Smart Shadow: a Shadow will be controlled by artificial intelligence. These technologies are based on the ‘semi-real simulation’ method. The technology allows coaches to train athletes remotely. Simulation of different opponents will help the athletes better prepare for competition. Repeat rehearsals of the upcoming fight will help improve results. SSS can improve results in Boxing, Taekwondo, Karate, and Fencing. 41 sets of medals will be awarded in these sports at the 2020 Olympic Games.

Keywords: boxing, combat sports, fight simulation, shadow sparring

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302 A Rare Entity: Case Report on Anaesthetic Management in Robinow Syndrome

Authors: Vidhi Chandra, Arshpreet Singh Grewal

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A five-year-old male child born from non-consanguineous marriage, who presented with complaints of growth retardation and no appreciable increase in the penile size since birth and he was posted for de-gloving of penis with dissection of corpora under anaesthesia. After thorough preoperative evaluation it was revealed that patient had peculiar facial dysmorphism that of Robinow Syndrome, high arched palate, Mallampati grade III, mesomelic limbs, scoliotic spine and short stature. All routine investigation were within normal limit, electrocardiography (ECG) and 2D-Echocardiography (ECHO) were normal. In antero-posterior roentgenogram chest showed butterfly and hemivertebrae at multiple levels. The patient was considered to be ASA II. On the day of surgery after ensuring fasting of 6 hours, patient was taken in operation theatre, all standard ASA monitoring was done with ECG, non-invasive blood pressure, peripheral oxygen saturation (SpO2) and body temperature. The patient was pre-oxygenated with 100% oxygen with anatomical face mask. General anaesthesia was induced with Sevoflurane 1-8%, and airway was secured with an appropriate size supraglottic airway and anaesthesia was maintained with nitrous oxide and oxygen in 1:1 ratio along with sevoflurane 2%. An ultrasound guided caudal block was given owing to the skeletal deformities making it difficult even under USG guidance. Post operatively patient was given supportive care with proper hydration, antibiotics, anti-inflammatory and analgesics. He was discharged the next day and followed up weekly for a month. DISCUSSION Robinow syndrome is genetically inherited as autosomal dominant, autosomal recessive or heterogenous disorder involving tyrosine kinase ROR2 gene located on chromosome 9. It has low incidence with no preponderance for any gender. Though intelligence is normal but developmental delay and mental retardation occurs in 20%cases

Keywords: Robinow Syndrome, dwarfism, paediatric, anaesthesia

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301 Quality of Service Based Routing Algorithm for Real Time Applications in MANETs Using Ant Colony and Fuzzy Logic

Authors: Farahnaz Karami

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Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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300 Improving Chest X-Ray Disease Detection with Enhanced Data Augmentation Using Novel Approach of Diverse Conditional Wasserstein Generative Adversarial Networks

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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299 Bridge Healthcare Access Gap with Artifical Intelligence

Authors: Moshmi Sangavarapu

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The US healthcare industry has undergone tremendous digital transformation in recent years, but critical care access to lower-income ethnicities is still in its nascency. This population has historically showcased substantial hesitation to seek any medical assistance. While the lack of sufficient financial resources plays a critical role, the existing cultural and knowledge barriers also contribute significantly to widening the access gap. It is imperative to break these barriers to ensure timely access to therapeutic procedures that can save important lives! Based on ongoing research, healthcare access barriers can be best addressed by tapping the untapped potential of caregiver communities first. They play a critical role in patients’ diagnoses, building healthcare knowledge and instilling confidence in required therapeutic procedures. Recent technological advancements have opened many avenues by developing smart ways of reaching the large caregiver community. A digitized go-to-market strategy featuring connected media coupled with smart IoT devices and geo-location targeting can be collectively leveraged to reach this key audience group. AI/ML algorithms can be thoroughly trained to identify relevant data signals from users' location and browsing behavior and determine useful marketing touchpoints. The web behavior can be further assimilated with natural language processing to identify contextually relevant interest topics and decipher potential caregivers on digital avenues to serve that brand message. In conclusion, grasping the true health access journey of any lower-income ethnic group is important to design beneficial touchpoints that can alleviate patients’ concerns and allow them to break their own access barriers and opt for timely and quality healthcare.

Keywords: healthcare access, market access, diversity barriers, patient journey

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298 Integrating Artificial Intelligence (AI) into Education-Stakeholder Engagement and ICT Practices for Complex Systems: A Governance Framework for Addressing Counseling Gaps in Higher Education

Authors: Chinyere Ori Elom, Ikechukwu Ogeze Ukeje, Chukwudum Collins Umoke

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This paper aims to stimulate scholarly interest in AI, ICT and the existing (complex) systems trajectory- theory, practice, and aspirations within the African continent and to shed fresh light on the shortcomings of the higher education sector (HEs) through the prism of AI-driven Solutions for enhancing Guidance and Counseling and sound governance framework (SGF) in higher education modeling. It further seeks to investigate existing prospects yet to be realized in Nigerian universities by probing innovation neglect in the localities, exploring practices in the global ICT spaces neglected by Nigeria universities’ governance regimes (UGRs), and suggesting area applicability, sustainability and solution modeling in response to peculiar ‘wicked ICT-driven problems’ and or issues facing the continent as well as other universities in emerging societies. This study will adopt a mixed-method approach to collect both qualitative and quantitative data. This paper argues that it will command great relevance in the local and global university system by developing ICT relevance sustainability policy initiatives (SPIs) powered by a multi-stakeholder engagement governance model (MSEGm) that is sufficiently dynamic, eclectic and innovative to surmount complex and constantly rising challenges of the modern-developing world. Hence, it will consider diverse actors both as producers and users alike as victims and beneficiaries of common concerns in the ICT world; thereby providing pathways on how AI’s integration into education governance can significantly reduce counseling gaps, ensuring more students are attended to especially when human counselors are unavailable.

Keywords: AI-counseling solution, stakeholder engagement, university governance, higher education

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297 A Reflective Investigation on the Course Design and Coaching Strategy for Creating a Trans-Disciplinary Leaning Environment

Authors: Min-Feng Hsieh

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Nowadays, we are facing a highly competitive environment in which the situation for survival has come even more critical than ever before. The challenge we will be confronted with is no longer can be dealt with the single system of knowledge. The abilities we urgently need to acquire is something that can lead us to cross over the boundaries between different disciplines and take us to a neutral ground that gathers and integrates powers and intelligence that surrounds us. This paper aims at discussing how a trans-disciplinary design course organized by the College of Design at Chaoyang University can react to this modern challenge. By orchestrating an experimental course format and by developing a series of coaching strategies, a trans-disciplinary learning environment has been created and practiced in which students selected from five different departments, including Architecture, Interior Design, Visual Design, Industrial Design, Landscape and Urban Design, are encouraged to think outside their familiar knowledge pool and to learn with/from each other. In the course of implementing this program, a parallel research has been conducted alongside by adopting the theory and principles of Action Research which is a research methodology that can provide the course organizer emergent, responsive, action-oriented, participative and critically reflective insights for the immediate changes and amendments in order to improve the effect of teaching and learning experience. In the conclusion, how the learning and teaching experience of this trans-disciplinary design studio can offer us some observation that can help us reflect upon the constraints and division caused by the subject base curriculum will be pointed out. A series of concepts for course design and teaching strategies developed and implemented in this trans-disciplinary course are to be introduced as a way to promote learners’ self-motivated, collaborative, cross-disciplinary and student-centered learning skills. The outcome of this experimental course can exemplify an alternative approach that we could adopt in pursuing a remedy for dealing with the problematic issues of the current educational practice.

Keywords: course design, coaching strategy, subject base curriculum, trans-disciplinary

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296 Human Behavioral Assessment to Derive Land-Use for Sustenance of River in India

Authors: Juhi Sah

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Habitat is characterized by the inter-dependency of environmental elements. Anthropocentric development approach is increasing our vulnerability towards natural hazards. Hence, manmade interventions should have a higher level of sensitivity towards the natural settings. Sensitivity towards the environment can be assessed by the behavior of the stakeholders involved. This led to the establishment of a hypothesis: there exists a legitimate relationship between the behavioral sciences, land use evolution and environment conservation, in the planning process. An attempt has been made to establish this relationship by reviewing the existing set of knowledge and case examples pertaining to the three disciplines under inquiry. Understanding the scarce & deteriorating nature of fresh-water reserves of earth and experimenting the above concept, a case study of a growing urban center's river flood plain is selected, in a developing economy, India. Cases of urban flooding in Chennai, Delhi and other mega cities of India, imposes a high risk on the unauthorized settlement, on the floodplains of the rivers. The issue addressed here is the encroachment of floodplains, through psychological enlightenment and modification through knowledge building. The reaction of an individual or society can be compared to a cognitive process. This study documents all the stakeholders' behavior and perception for their immediate natural environment (water body), and produce various land uses suitable along a river in an urban settlement as per different stakeholder's perceptions. To assess and induce morally responsible behavior in a community (small scale or large scale), tools of psychological inquiry is used for qualitative analysis. The analysis will deal with varied data sets from two sectors namely: River and its geology, Land use planning and regulation. Identification of a distinctive pattern in the built up growth, river ecology degradation, and human behavior, by handling large quantum of data from the diverse sector and comments on the availability of relevant data and its implications, has been done. Along the whole river stretch, condition and usage of its bank vary, hence stakeholder specific survey questionnaires have been prepared to accurately map the responses and habits of the rational inhabitants. A conceptual framework has been designed to move forward with the empirical analysis. The classical principle of virtues says "virtue of a human depends on its character" but another concept defines that the behavior or response is a derivative of situations and to bring about a behavioral change one needs to introduce a disruption in the situation/environment. Owing to the present trends, blindly following the results of data analytics and using it to construct policy, is not proving to be in favor of planned development and natural resource conservation. Thus behavioral assessment of the rational inhabitants of the planet is also required, as their activities and interests have a large impact on the earth's pre-set systems and its sustenance.

Keywords: behavioral assessment, flood plain encroachment, land use planning, river sustenance

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295 The Implications of Technological Advancements on the Constitutional Principles of Contract Law

Authors: Laura Çami (Vorpsi), Xhon Skënderi

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In today's rapidly evolving technological landscape, the traditional principles of contract law are facing significant challenges. The emergence of new technologies, such as electronic signatures, smart contracts, and online dispute resolution mechanisms, is transforming the way contracts are formed, interpreted, and enforced. This paper examines the implications of these technological advancements on the constitutional principles of contract law. One of the fundamental principles of contract law is freedom of contract, which ensures that parties have the autonomy to negotiate and enter into contracts as they see fit. However, the use of technology in the contracting process has the potential to disrupt this principle. For example, online platforms and marketplaces often offer standard-form contracts, which may not reflect the specific needs or interests of individual parties. This raises questions about the equality of bargaining power between parties and the extent to which parties are truly free to negotiate the terms of their contracts. Another important principle of contract law is the requirement of consideration, which requires that each party receives something of value in exchange for their promise. The use of digital assets, such as cryptocurrencies, has created new challenges in determining what constitutes valuable consideration in a contract. Due to the ambiguity in this area, disagreements about the legality and enforceability of such contracts may arise. Furthermore, the use of technology in dispute resolution mechanisms, such as online arbitration and mediation, may raise concerns about due process and access to justice. The use of algorithms and artificial intelligence to determine the outcome of disputes may also raise questions about the impartiality and fairness of the process. Finally, it should be noted that there are many different and complex effects of technical improvements on the fundamental constitutional foundations of contract law. As technology continues to evolve, it will be important for policymakers and legal practitioners to consider the potential impacts on contract law and to ensure that the principles of fairness, equality, and access to justice are preserved in the contracting process.

Keywords: technological advancements, constitutional principles, contract law, smart contracts, online dispute resolution, freedom of contract

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294 Earthquake Preparedness of School Community and E-PreS Project

Authors: A. Kourou, A. Ioakeimidou, S. Hadjiefthymiades, V. Abramea

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During the last decades, the task of engaging governments, communities and citizens to reduce risk and vulnerability of the populations has made variable progress. Experience has demonstrated that lack of awareness, education and preparedness may result in significant material and other losses both on the onset of the disaster. Schools play a vital role in the community and are important elements of values and culture of the society. A proper school education not only teaches children, but also is a key factor in the promotion of a safety culture into the wider community. In Greece School Earthquake Safety Initiative has been undertaken by Earthquake Planning and Protection Ogranization with specific actions (seminars, lectures, guidelines, educational material, campaigns, national or EU projects, drills etc.). The objective of this initiative is to develop disaster-resilient school communities through awareness, self-help, cooperation and education. School preparedness requires the participation of Principals, teachers, students, parents, and competent authorities. Preparation and earthquake readiness involves: a) learning what should be done before, during, and after earthquake; b) doing or preparing to do these things now, before the next earthquake; and c) developing teachers’ and students’ skills to cope efficiently in case of an earthquake. In the above given framework this paper presents the results of a survey aimed to identify the level of education and preparedness of school community in Greece. More specifically, the survey questionnaire investigates issues regarding earthquake protection actions, appropriate attitudes and behaviors during an earthquake and existence of contingency plans at elementary and secondary schools. The questionnaires were administered to Principals and teachers from different regions of the country that attend the EPPO national training project 'Earthquake Safety at Schools'. A closed-form questionnaire was developed for the survey, which contained questions regarding the following: a) knowledge of self protective actions b) existence of emergency planning at home and c) existence of emergency planning at school (hazard mitigation actions, evacuation plan, and performance of drills). Survey results revealed that a high percentage of teachers have taken the appropriate preparedness measures concerning non-structural hazards at schools, emergency school plan and simulation drills every year. In order to improve the action-planning for ongoing school disaster risk reduction, the implementation of earthquake drills, the involvement of students with disabilities and the evaluation of school emergency plans, EPPO participates in E-PreS project. The main objective of this project is to create smart tools which define, simulate and evaluate all hazards emergency steps customized to the unique district and school. The project comes up with a holistic methodology using real-time evaluation involving different categories of actors, districts, steps and metrics. The project is supported by EU Civil Protection Financial Instrument with a duration of two years. Coordinator is the Kapodistrian University of Athens and partners are from four countries; Greece, Italy, Romania and Bulgaria.

Keywords: drills, earthquake, emergency plans, E-PreS project

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293 Multi Biomertric Personal Identification System Based On Hybird Intellegence Method

Authors: Laheeb M. Ibrahim, Ibrahim A. Salih

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Biometrics is a technology that has been widely used in many official and commercial identification applications. The increased concerns in security during recent years (especially during the last decades) have essentially resulted in more attention being given to biometric-based verification techniques. Here, a novel fusion approach of palmprint, dental traits has been suggested. These traits which are authentication techniques have been employed in a range of biometric applications that can identify any postmortem PM person and antemortem AM. Besides improving the accuracy, the fusion of biometrics has several advantages such as increasing, deterring spoofing activities and reducing enrolment failure. In this paper, a first unimodel biometric system has been made by using (palmprint and dental) traits, for each one classification applying an artificial neural network and a hybrid technique that combines swarm intelligence and neural network together, then attempt has been made to combine palmprint and dental biometrics. Principally, the fusion of palmprint and dental biometrics and their potential application has been explored as biometric identifiers. To address this issue, investigations have been carried out about the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. Also the results of the multimodal approach have been compared with each one of these two traits authentication approaches. This paper studies the features and decision fusion levels in multimodal biometrics. To determine the accuracy of GAR to parallel system decision-fusion including (AND, OR, Majority fating) has been used. The backpropagation method has been used for classification and has come out with result (92%, 99%, 97%) respectively for GAR, while the GAR) for this algorithm using hybrid technique for classification (95%, 99%, 98%) respectively. To determine the accuracy of the multibiometric system for feature level fusion has been used, while the same preceding methods have been used for classification. The results have been (98%, 99%) respectively while to determine the GAR of feature level different methods have been used and have come out with (98%).

Keywords: back propagation neural network BP ANN, multibiometric system, parallel system decision-fusion, practical swarm intelligent PSO

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292 Global Learning Supports Global Readiness with Projects with Purpose

Authors: Brian Bilich

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A typical global learning program is a two-week project based, culturally immersive and academically relevant experience built around a project with purpose and catered to student and business groups. Global Learning in Continuing Education at Austin Community College promotes global readiness through projects with purpose with special attention given to balancing learning, hospitality and travel. A recent project involved CommunityFirst! Village; a 51-acre planned community which provides affordable, permanent housing for men and women coming out of chronic homelessness. Global Learning students collaborated with residents and staff at the Community First! Village on a project to produce two-dimensional remodeling plans of residents’ tiny homes with a focus on but not limited to design improvements on elements related to accessibility, increased usability of living and storage space and esthetic upgrades to boost psychological and emotional appeal. The goal of project-based learning in the context of global learning in Continuing Educaiton at Austin Community Collegen general is two fold. One, in rapid fashion we develop a project which gives the learner a hands-on opportunity to exercise soft and technical skills, like creativity and communication and analytical thinking. Two, by basing projects on global social conflict issues, the project of purpose promotes the development of empathy for other people and fosters a sense of corporate social responsibility in future generations of business leadership. In the example provide above the project informed the student group on the topic of chronic homelessness and promoted awareness and empathy for this underserved segment of the community. Project-based global learning based on projects with purpose has the potential to cultivate global readiness by developing empathy and strengthening emotional intelligence for future generations.

Keywords: project-based learning, global learning, global readiness, globalization, international exchange, collaboration

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291 Stress Reduction Techniques for First Responders: Scientifically Proven Methods

Authors: Esther Ranero Carrazana, Maria Karla Ramirez Valdes

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First responders, including firefighters, police officers, and emergency medical personnel, are frequently exposed to high-stress scenarios that significantly increase their risk of mental health issues such as depression, anxiety, and post-traumatic stress disorder (PTSD). Their work involves life-threatening situations, witnessing suffering, and making critical decisions under pressure, all contributing to psychological strain. The objectives of this research on "Stress Reduction Techniques for First Responders: Scientifically Proven Methods" are as follows. One of them is to evaluate the effectiveness of stress reduction techniques. The primary objective is to assess the efficacy of various scientifically proven stress reduction techniques explicitly tailored for first responders. Heart Rate Variability (HRV) Training, Interoception and Exteroception, Sensory Integration, and Body Perception Awareness are scrutinized for their ability to mitigate stress-related symptoms. Furthermore, we evaluate and enhance the understanding of stress mechanisms in first responders by exploring how different techniques influence the physiological and psychological responses to stress. The study aims to deepen the understanding of stress mechanisms in high-risk professions. Additionally, the study promotes psychological resilience by seeking to identify and recommend methods that can significantly enhance the psychological resilience of first responders, thereby supporting their mental health and operational efficiency in high-stress environments. Guide training and policy development is an additional objective to provide evidence-based recommendations that can be used to guide training programs and policy development aimed at improving the mental health and well-being of first responders. Lastly, the study aims to contribute valuable insights to the existing body of knowledge in stress management, specifically tailored to the unique needs of first responders. This study involved a comprehensive literature review assessing the effectiveness of various stress reduction techniques tailored for first responders. Techniques evaluated include Heart Rate Variability (HRV) Training, Interoception and Exteroception, Sensory Integration, and Body Perception Awareness, focusing on their ability to alleviate stress-related symptoms. The review indicates promising results for several stress reduction methods. HRV Training demonstrates the potential to reflect stress vulnerability and enhance physiological and behavioral flexibility. Interoception and Exteroception help modulate the stress response by enhancing awareness of the body's internal state and its interaction with the environment. Sensory integration plays a crucial role in adaptive responses to stress by focusing on individual senses and their integration. Therefore, body perception awareness addresses stress and anxiety through enhanced body perception and mindfulness. The evaluated techniques show significant potential in reducing stress and improving the mental health of first responders. Implementing these scientifically supported methods into routine training could significantly enhance their psychological resilience and operational effectiveness in high-stress environments.

Keywords: first responders, HRV training, mental health, sensory integration, stress reduction

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290 E-Learning Platform for School Kids

Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

Procedia PDF Downloads 157
289 Positioning Mama Mkubwa Indigenous Model into Social Work Practice through Alternative Child Care in Tanzania: Ubuntu Perspective

Authors: Johnas Buhori, Meinrad Haule Lembuka

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Introduction: Social work expands its boundary to accommodate indigenous knowledge and practice for better competence and services. In Tanzania, Mama Mkubwa Mkubwa (MMM) (Mother’s elder sister) is an indigenous practice of alternative child care that represents other traditional practices across African societies known as Ubuntu practice. Ubuntu is African Humanism with values and approaches that are connected to the social work. MMM focuses on using the elder sister of a deceased mother or father, a trusted elder woman from the extended family or indigenous community to provide alternative care to an orphan or vulnerable child. In Ubuntu's perspective, it takes a whole village or community to raise a child, meaning that every person in the community is responsible for child care. Methodology: A desk review method guided by Ubuntu theory was applied to enrich the study. Findings: MMM resembles the Ubuntu ideal of traditional child protection of those in need as part of alternative child care throughout Tanzanian history. Social work practice, along with other formal alternative child care, was introduced in Tanzania during the colonial era in 1940s and socio-economic problems of 1980s affected the country’s formal social welfare system, and suddenly HIV/AIDS pandemic triggered the vulnerability of children and hampered the capacity of the formal sector to provide social welfare services, including alternative child care. For decades, AIDS has contributed to an influx of orphans and vulnerable children that facilitated the re-emerging of traditional alternative child care at the community level, including MMM. MMM strongly practiced in regions where the AIDS pandemic affected the community, like Njombe, Coastal region, Kagera, etc. Despite of existing challenges, MMM remained to be the remarkably alternative child care practiced in both rural and urban communities integrated with social welfare services. Tanzania envisions a traditional mechanism of family or community environment for alternative child care with the notion that sometimes institutionalization care fails to offer children all they need to become productive members of society, and later, it becomes difficult to reconnect in the society. Implications to Social Work: MMM is compatible with social work by using strengths perspectives; MMM reflects Ubuntu's perspective on the ground of humane social work, using humane methods to achieve human goals. MMM further demonstrates the connectedness of those who care and those cared for and the inextricable link between them as Ubuntu-inspired models of social work that view children from family, community, environmental, and spiritual perspectives. Conclusion: Social work and MMM are compatible at the micro and mezzo levels; thus, application of MMM can be applied in social work practice beyond Tanzania when properly designed and integrated into other systems. When MMM is applied in social work, alternative care has the potential to support not only children but also empower families and communities. Since MMM is a community-owned and voluntary base, it can relieve the government, social workers, and other formal sectors from the annual burden of cost in the provision of institutionalized alternative child care.

Keywords: ubuntu, indigenous social work, african social work, ubuntu social work, child protection, child alternative care

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288 Improving Grade Control Turnaround Times with In-Pit Hyperspectral Assaying

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

Procedia PDF Downloads 113
287 Sexual Consent and Persons with Psychosocial Disabilities: Exploring Sexual Rights under Indian Laws

Authors: Sachin Sharma

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Sexual consent is integral to every sexual relationship. It is a process to facilitate sexual autonomy and bodily integrity. It assures complete sexual personhood and allows an individual to explore her sexual expressions independently. But the said proposition is not true for people with psychosocial disabilities. Generally, they are considered seraphic or mephistophelic and denied access to sexual autonomy. This result in institutionalizing the sexuality of disabled persons, where the eugenics-ableist narrative defines assessment and access to consent. This way, sexuality and disability are distanced apart. It is primarily due to the stigmatized socio-cultural constructs of sexuality that define sex within a “standard” and “charmed” circle. Such stigmatized expression influences the law, as it considers people with psychosocial disabilities incapable of sexual consent. The approach of legal institutions is very narrow towards interpreting their sexual rights. It echoes the modernist-ableism and strangulates the sexual choices. This way, it reflects the repressive model of sex and denies space to people with psychosocial disabilities. Moreover, judicial courts follow old and conservative methods while dealing with sexual issues. For instance, courts still practice the “standardized” norm of intelligence quotient (IQ) for determining the credibility of persons with psychosocial disabilities. Further, there is still doubt about assistive communicative techniques. This paper will try to question the normative structure of sexual consent and related laws while specifically addressing the issues of sex as desire and abuse. Considering the commitment to the United Nations Convention on the Rights of Persons with Disabilities (herein referred to as UNCRPD) and common law experience, the paper will draw a comparative study on the legal position of sexual rights in India. The paper will also analyze the role of UNCRPD in addressing sexual rights. The author will examine the position of sexual rights of people with psychosocial disabilities after the drafting of UNCRPD and specific state laws. The paper primarily follows the doctrinal method.

Keywords: sexual autonomy, institutionalized choices, overregulated laws, violation of individuality

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286 Chemical Warfare Agent Simulant by Photocatalytic Filtering Reactor: Effect of Operating Parameters

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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285 The Social Aspects of Mental Illness among Orthodox Christians of the Tigrinya Ethnic Group in Eritrea

Authors: Erimias Firre

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This study is situated within the religio-cultural milieu of Coptic Orthodox Christians of the Tigrinya ethnic group in Eritrea. With this ethnic group being conservative and traditionally bound, extended family structures dissected along various clans and expansive community networks are the distinguishing mark of its members. Notably, Coptic Tigrinya constitutes the largest percentage of all Christian denominations in Eritrea. As religious, cultural beliefs, rituals and teachings permeate in all aspects of social life, a distinct worldview and traditionalized health and illness conceptualization are common. Accordingly, this study argues that religio-culturally bound illness ideologies immensely determine the perception, help seeking behavior and healing preference of Coptic Tigrinya in Eritrea. The study bears significance in the sense that it bridges an important knowledge gap, given that it is ethno-linguistically (within the Tigrinya ethnic group), spatially (central region of Eritrea) and religiously (Coptic Christianity) specific. The conceptual framework guiding this research centered on the social determinants of mental health, and explores through the lens of critical theory how existing systems generate social vulnerability and structural inequality, providing a platform to reveal how the psychosocial model has the capacity to emancipate and empower those with mental disorders to live productive and meaningful lives. A case study approach was employed to explore the interrelationship between religio-cultural beliefs and practices and perception of common mental disorders of depression, anxiety, bipolar affective, schizophrenia and post-traumatic stress disorders and the impact of these perceptions on people with those mental disorders. Purposive sampling was used to recruit 41 participants representing seven diverse cohorts; people with common mental disorders, family caregivers, general community members, ex-fighters , priests, staff at St. Mary’s and Biet-Mekae Community Health Center; resulting in rich data for thematic analysis. Findings highlighted current religio-cultural perceptions, causes and treatment of mental disorders among Coptic Tigrinya result in widespread labelling, stigma and discrimination, both of those with mental disorders and their families. Traditional healing sources are almost exclusively tried, sometimes for many years, before families and sufferers seek formal medical assessment and treatment, resulting difficult to treat illness chronicity. Service gaps in the formal medical system result in the inability to meet the principles enshrined in the WHO Mental Health Action Plan 2013-2020 to which the Eritrean Government is a signatory. However, the study found that across all participant cohorts, there was a desire for change that will create a culture whereby those with mental disorders will have restored hope, connectedness, healing and self-determination.

Keywords: Coptic Tigrinya, mental disorders, psychosocial model social integration and recovery, traditional healing

Procedia PDF Downloads 187
284 Grid and Market Integration of Large Scale Wind Farms using Advanced Predictive Data Mining Techniques

Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

Procedia PDF Downloads 519
283 Argumentation Frameworks and Theories of Judging

Authors: Sonia Anand Knowlton

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With the rise of artificial intelligence, computer science is becoming increasingly integrated in virtually every area of life. Of course, the law is no exception. Through argumentation frameworks (AFs), computer scientists have used abstract algebra to structure the legal reasoning process in a way that allows conclusions to be drawn from a formalized system of arguments. In AFs, arguments compete against each other for logical success and are related to one another through the binary operation of the attack. The prevailing arguments make up the preferred extension of the given argumentation framework, telling us what set of arguments must be accepted from a logical standpoint. There have been several developments of AFs since its original conception in the early 90’s in efforts to make them more aligned with the human reasoning process. Generally, these developments have sought to add nuance to the factors that influence the logical success of competing arguments (e.g., giving an argument more logical strength based on the underlying value it promotes). The most cogent development was that of the Extended Argumentation Framework (EAF), in which attacks can themselves be attacked by other arguments, and the promotion of different competing values can be formalized within the system. This article applies the logical structure of EAFs to current theoretical understandings of judicial reasoning to contribute to theories of judging and to the evolution of AFs simultaneously. The argument is that the main limitation of EAFs, when applied to judicial reasoning, is that they require judges to themselves assign values to different arguments and then lexically order these values to determine the given framework’s preferred extension. Drawing on John Rawls’ Theory of Justice, the examination that follows is whether values are lexical and commensurable to this extent. The analysis that follows then suggests a potential extension of the EAF system with an approach that formalizes different “planes of attack” for competing arguments that promote lexically ordered values. This article concludes with a summary of how these insights contribute to theories of judging and of legal reasoning more broadly, specifically in indeterminate cases where judges must turn to value-based approaches.

Keywords: computer science, mathematics, law, legal theory, judging

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282 Autonomous Exploration, Navigation and Mapping Payload Integrated on a Quadruped Robot

Authors: Julian Y. Raheema, Michael R. Hess, Raymond C. Provost, Mark Bilinski

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The world is rapidly moving towards advancing and utilizing artificial intelligence and autonomous robotics. The ground-breaking Boston Dynamics quadruped robot, SPOT, was designed for industrial and commercial tasks requiring limited autonomous navigation. Out of the box, SPOT has route memorization and playback – it can repeat a path that it has been manually piloted through, but it cannot autonomously navigate an area that has not been previously explored. The presented SPOT payload package is built on ROS framework to support autonomous navigation and mapping of an unexplored environment. The package is fully integrated with SPOT to take advantage of motor controls and collision avoidance that comes natively with the robot. The payload runs all computations onboard, takes advantage of visual odometry SLAM and uses an Intel RealSense depth camera and Velodyne LiDAR sensor to generate 2D and 3D maps while in autonomous navigation mode. These maps are fused into the navigation stack to generate a costmap to enable the robot to safely navigate the environment without causing damage to the surroundings or the robot. The operator defines the operational zone and start location and then sends the explore command to have SPOT explore, generate 2D and 3D maps of the environment and return to the start location to await the operator's next command. The benefit of the presented package is that it is much lighter weight and less expensive than previous approaches and, importantly, operates in GPS-denied scenarios, which is ideal for indoor mapping. There are numerous applications that are hazardous to humans for SPOT enhanced with the autonomy payload, including disaster response, nuclear inspection, mine inspection, and so on. Other less extreme uses cases include autonomous 3D and 2D scanning of facilities for inspection, engineering and construction purposes.

Keywords: autonomous, SLAM, quadruped, mapping, exploring, ROS, robotics, navigation

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281 Modelling the Impact of Installation of Heat Cost Allocators in District Heating Systems Using Machine Learning

Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

Procedia PDF Downloads 251
280 Hybrid CNN-SAR and Lee Filtering for Enhanced InSAR Phase Unwrapping and Coherence Optimization

Authors: Hadj Sahraoui Omar, Kebir Lahcen Wahib, Bennia Ahmed

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Interferometric Synthetic Aperture Radar (InSAR) coherence is a crucial parameter for accurately monitoring ground deformation and environmental changes. However, coherence can be degraded by various factors such as temporal decorrelation, atmospheric disturbances, and geometric misalignments, limiting the reliability of InSAR measurements (Omar Hadj‐Sahraoui and al. 2019). To address this challenge, we propose an innovative hybrid approach that combines artificial intelligence (AI) with advanced filtering techniques to optimize interferometric coherence in InSAR data. Specifically, we introduce a Convolutional Neural Network (CNN) integrated with the Lee filter to enhance the performance of radar interferometry. This hybrid method leverages the strength of CNNs to automatically identify and mitigate the primary sources of decorrelation, while the Lee filter effectively reduces speckle noise, improving the overall quality of interferograms. We develop a deep learning-based model trained on multi-temporal and multi-frequency SAR datasets, enabling it to predict coherence patterns and enhance low-coherence regions. This hybrid CNN-SAR with Lee filtering significantly reduces noise and phase unwrapping errors, leading to more precise deformation maps. Experimental results demonstrate that our approach improves coherence by up to 30% compared to traditional filtering techniques, making it a robust solution for challenging scenarios such as urban environments, vegetated areas, and rapidly changing landscapes. Our method has potential applications in geohazard monitoring, urban planning, and environmental studies, offering a new avenue for enhancing InSAR data reliability through AI-powered optimization combined with robust filtering techniques.

Keywords: CNN-SAR, Lee Filter, hybrid optimization, coherence, InSAR phase unwrapping, speckle noise reduction

Procedia PDF Downloads 14