Search results for: Collective Intelligence
757 The Portuguese Legal Instruments to Combat the Improper Use of the Contract Service
Authors: Ana Lambelho
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Nowadays is very common that an activity may be performed independently or dependently. In Portugal, the Labour Law exclusively protects the dependent labour relations. The independent work is regulated by civil law, where the autonomy of the will is the main principle. For companies is more advantageous to hire people under a service agreement since, in that case, the relation is not submitted to the limits established in Labour law and collective bargaining. This practice has nothing wrong, if the performance of work is, in fact, made autonomously. The problem is the increased frequency of the celebration of service agreements to hide a legal relation of subordination. Aware of this and regarding the huge difficulty to demonstrate the existence of subordinated work (that often runs against the employee), the Portuguese legislator devoted some legislative rules in order to facilitate the evidence of legal subordination and, on the other hand, to avoid the misuse of the provision of service agreements. This study focuses precisely on the analysis of this solution, namely the so-called presumption of ‘laboralidade’ and on the lawsuit to recognize the existence of a labour contract. The presumption of the existence of a labour contract is present in the Portuguese legal system since 2003, and received, with the 2009 Labour Code, a new redaction that, according to the doctrine and the jurisprudence, finally approached it to a legal presumption, with the consequent reversal of the burden of proof and, in consequence, made easier to proof the legal subordination, because the employee will just have to plead and prove the existence of two of the elements described in the law to use this presumption. Another change in the Portuguese legal framework is related with the competencies of the Authority for Working Conditions (AWC): now, if during an inspection, the Authority finds a situation that seems to be an undeclared employment situation, it may access the company and, if it does not regularize voluntarily the situation, AWC has a duty to communicate to the public prosecutor, who will begin the lawsuit for the recognition of the existence of an employment contract. To defend the public interest, the action to recognize the existence of an employment contract will follow its terms, even against the employee will. Although the existence of these mechanisms does not solve by itself the problem of evasion of labour law and false ‘green receipts’, it is undeniable that it is an important step in combating fraud in this field.Keywords: independent work, labour contract, Portugal, service agreement
Procedia PDF Downloads 327756 Repetitive Compulsions of Trauma: Critically Analyzing Damages Done When Perpetuating Heroic White Masculinity at Federally Managed United States Civil War Battlefields
Authors: Cait M. Henry, Sarah Jackson
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Abstract-This study is built from the culmination of four years of research into the cultural interpretation of Civil War heritage at a National Park Service (NPS) site, namely the Manassas National Battlefield Park, within an increasingly contentious political landscape surrounding the U.S. Civil War. Originating as questions regarding the relevancy of historic battlefields to the current culture within the United States soon evolved into more philosophical questions about what it means to feel welcome at a battlefield site, and what are considered appropriate actions and behaviors at what was once a mass gravesite. In trying to answer these questions, this work aims to critically analyze the confluence between the cultural authority of the NPS and collective memories of the U.S. Civil War. Operationalizing trauma as repeated violent acts within public spaces, the authors posit that the normalization of violence from white or white-passing men partially stems from the glorification of heroic white masculinity at National Park Service Civil War battlefield sites—especially those which also commemorate Confederate military strategy and prowess. From here the study moves outward to focus on the prevalence of heroic white masculinity within the nation’s current social zeitgeist, and particularly the notion that to take back masculinity one must utilize violence as a means of symbolic restoration from perceptions of white victimhood. The study ends with case studies of dark tourism framing at international battlefields as models for expanding heritage interpretation at the NPS site to foster narratives of empathy and responsibility within an increasingly contentious political landscape within the United States of America. Visitors do not leave Manassas National Battlefield Park with answers about the social and moral implications of the U.S. Civil War, but the tools for championing their own (predominantly white) heroic masculinity. As such, it is only logical that one common reaction when masculinity is symbolically threatened is to enact violence against Others as a restorative force within the United States.Keywords: confederate heritage, military history, national park service, trauma, United States civil war
Procedia PDF Downloads 16755 Modern Proteomics and the Application of Machine Learning Analyses in Proteomic Studies of Chronic Kidney Disease of Unknown Etiology
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 152754 Investigating Best Strategies Towards Creating Alternative Assessment in Literature
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 86753 Low Probability of Intercept (LPI) Signal Detection and Analysis Using Choi-Williams Distribution
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 473752 A Method for False Alarm Recognition Based on Multi-Classification Support Vector Machine
Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li
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Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.Keywords: false alarm, fault diagnosis, SVM, k-means, BIT
Procedia PDF Downloads 156751 Framework for Integrating Big Data and Thick Data: Understanding Customers Better
Authors: Nikita Valluri, Vatcharaporn Esichaikul
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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data
Procedia PDF Downloads 163750 Artificial Intelligent Tax Simulator to Minimize Tax Liability for Multinational Corporations
Authors: Sean Goltz, Michael Mayo
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The purpose of this research is to use Global-Regulation.com database of the world laws, focusing on tax treaties between countries, in order to create an AI-driven tax simulator that will run an AI agent through potential tax scenarios across countries. The AI agent goal is to identify the scenario that will result in minimum tax liability based on tax treaties between countries. The results will be visualized by a three dimensional matrix. This will be an online web application. Multinational corporations are running their business through multiple countries. These countries, in turn, have a tax treaty with many other countries to regulate the payment of taxes on income that is transferred between these countries. As a result, planning the best tax scenario across multiple countries and numerous tax treaties is almost impossible. This research propose to use Global-Regulation.com database of word laws in English (machine translated by Google and Microsoft API’s) in order to create a simulator that will include the information in the tax treaties. Once ready, an AI agent will be sent through the simulator to identify the scenario that will result in minimum tax liability. Identifying the best tax scenario across countries may save multinational corporations, like Google, billions of dollars annually. Given the nature of the raw data and the domain of taxes (i.e., numbers), this is a promising ground to employ artificial intelligence towards a practical and beneficial purpose.Keywords: taxation, law, multinational, corporation
Procedia PDF Downloads 200749 Designing a Patient Monitoring System Using Cloud and Semantic Web Technologies
Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis
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Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare
Procedia PDF Downloads 510748 The Threat of International Terrorism and Its Impact on UK Migration Policy and Practice
Authors: Baljit Soroya
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Transnational communities are as a consequence of greater mobility of people, globalization and digitization have had a major impact on international relations and diasporas in the context of external conflicts. To a significant extent conflicts are becoming deterritorialised and informed by both internal (state politics) and external (foreign policy) players such as in Iraq and Syria leading to forced migration of unprecedented levels within the last two decades. The situation of forced migrants has, it is suggested, worsened as a consequence of the neo-liberal policies and requirements of organizations such as the European Bank. A case example of this being that of Greece, and the exacerbation of insecurity for Greek nationals and the demonization of refugees seeking sanctuary. This has been as a consequence, in part, of the neoliberal dogma of the European Bank. The article analyses the complex intersection of the real and perceived threats of international terrorism and the manner in which UK migration policy and Practice is unfolding. The policy and practice developments are explored in the context of the shift in politics in both the UK and wider Europe to the far right and the drift of main stream political parties to the right. In many cases, the mainstream political groupings, have co-opted the fears as presented by far right organization for political their own political gains, such as in the UK and France In its analysis it will be argued that, whilst international terrorism is an issue of concern, however in the context of the UK it is not of the same scale as the effects of climate change or indeed domestic violence. Given that, the question has to be asked why the threat of international terrorism is having such an impact on UK migration policy and practice and, specifically refugees. Furthermore, it is argued that this policy and practice are being formulated within a narrative that portrays migrants as the problem both in relation to terrorism and the disenfranchisement of ‘ordinary white communities’. The intersectionality of social, economic inequalities, fear of international terrorism, increase in conflicts and the political climate have contributed to a lack of trust of political establishments that have in turn sought to impress the public with their anti-immigrant rhetoric and policy agendas. The article ends by suggesting that whilst politics and political affiliations have become fractured there are nevertheless spaces for collective action, particularly in relation to issues of refugees.Keywords: international terrorism, migration policy, conflict, media, community, politics
Procedia PDF Downloads 335747 Teaching during the Pandemic Using a Feminist Pedagogy: Classroom Conversations and Practices
Authors: T. Northcut, A. Rai, N. Perkins
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Background: The COVID-19 pandemic has had a serious impact on academia in general and social work education in particular, changing permanently the way in which we approach educating students. The new reality of the pandemic coupled with the much-needed focus on racism across the country inspired and required educators to get creative with their teaching styles in order to disrupt the power imbalance in the classroom and attend to the multiple layers of needs of diverse students in precarious sociological and economic circumstances. This paper highlights research examining educators with distinctive positionalities and approaches to classroom instruction who use feminist and antiracist pedagogies while adapting to online teaching during the pandemic. Despite being feminist scholars, whose ideologies developed during different waves of feminism, our commitment to having student-led classrooms, liberation, and equity of all, and striving for social change, unified our feminist teaching pedagogies as well as provided interpersonal support. Methodology: Following a narrative qualitative inquiry methodology, the five authors of this paper came together to discuss our pedagogical styles and underlying values using Zoom in a series of six conversations. Narrative inquiry is an appropriate method to use when researchers are bound by common stories or personal experiences. The use of feminist pedagogy in the classroom before and during the pandemic guided the discussions. After six sessions, we reached the point of data saturation. All data from the dialogic process was recorded and transcribed. We used in vivo, narrative, and descriptive coding for the data analytic process. Results: Analysis of the data revealed several themes, which included (1) the influence of our positionalities as an intersection of race, sexual orientation, gender, and years of teaching experience in the classroom, (2) the meaning and variations between different liberatory pedagogical approaches, (3) the tensions between these approaches and institutional policies and practices, (4) the role of self-reflection in everyday teaching, (5) the distinctions between theory and practice and its utility for students, and (6) the challenges of applying a feminist-centered pedagogical approach during the pandemic while utilizing an online platform. As a collective, we discussed several challenges that limited the use of our feminist pedagogical approaches due to instruction through Zoom.Keywords: feminist, pedagogy, COVID, zoom
Procedia PDF Downloads 46746 Convolutional Neural Network and LSTM Applied to Abnormal Behaviour Detection from Highway Footage
Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos
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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage
Procedia PDF Downloads 168745 Linking Excellence in Biomedical Knowledge and Computational Intelligence Research for Personalized Management of Cardiovascular Diseases within Personal Health Care
Authors: T. Rocha, P. Carvalho, S. Paredes, J. Henriques, A. Bianchi, V. Traver, A. Martinez
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The main goal of LINK project is to join competences in intelligent processing in order to create a research ecosystem to address two central scientific and technical challenges for personal health care (PHC) deployment: i) how to merge clinical evidence knowledge in computational decision support systems for PHC management and ii) how to provide achieve personalized services, i.e., solutions adapted to the specific user needs and characteristics. The final goal of one of the work packages (WP2), designated Sustainable Linking and Synergies for Excellence, is the definition, implementation and coordination of the necessary activities to create and to strengthen durable links between the LiNK partners. This work focuses on the strategy that has been followed to achieve the definition of the Research Tracks (RT), which will support a set of actions to be pursued along the LiNK project. These include common research activities, knowledge transfer among the researchers of the consortium, and PhD student and post-doc co-advisement. Moreover, the RTs will establish the basis for the definition of concepts and their evolution to project proposals.Keywords: LiNK Twin European Project, personal health care, cardiovascular diseases, research tracks
Procedia PDF Downloads 216744 Learning from Flood: A Case Study of a Frequently Flooded Village in Hubei, China
Authors: Da Kuang
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Resilience is a hotly debated topic in many research fields (e.g., engineering, ecology, society, psychology). In flood management studies, we are experiencing the paradigm shift from flood resistance to flood resilience. Flood resilience refers to tolerate flooding through adaptation or transformation. It is increasingly argued that our city as a social-ecological system holds the ability to learn from experience and adapt to flood rather than simply resist it. This research aims to investigate what kinds of adaptation knowledge the frequently flooded village learned from past experience and its advantages and limitations in coping with floods. The study area – Xinnongcun village, located in the west of Wuhan city, is a linear village and continuously suffered from both flash flood and drainage flood during the past 30 years. We have a field trip to the site in June 2017 and conducted semi-structured interviews with local residents. Our research summarizes two types of adaptation knowledge that people learned from the past floods. Firstly, at the village scale, it has formed a collective urban form which could help people live during both flood and dry season. All houses and front yards were elevated about 2m higher than the road. All the front yards in the village are linked and there is no barrier. During flooding time, people walk to neighbors through houses yards and boat to outside village on the lower road. Secondly, at individual scale, local people learned tacit knowledge of preparedness and emergency response to flood. Regarding the advantages and limitations, the adaptation knowledge could effectively help people to live with flood and reduce the chances of getting injuries. However, it cannot reduce local farmers’ losses on their agricultural land. After flood, it is impossible for local people to recover to the pre-disaster state as flood emerges during June and July will result in no harvest. Therefore, we argue that learning from past flood experience could increase people’s adaptive capacity. However, once the adaptive capacity cannot reduce people’s losses, it requires a transformation to a better regime.Keywords: adaptation, flood resilience, tacit knowledge, transformation
Procedia PDF Downloads 334743 Energy Efficient Clustering with Adaptive Particle Swarm Optimization
Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha
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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering
Procedia PDF Downloads 249742 Survival Struggle: To Be a Female Competitor in Survivor
Authors: Gülbuğ Erol, Gamze Beyge, Hakan Ekemen
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In Turkey national TV channels broadcast a wide range of programs to audience attract viewers. Since the year 2000, especially the competition programs were directed towards entertainment and audience has gained. Even today, television channels have just begun to be broadcast on entertainment channels. Except from the news, the TV collects pleasure with its broadcasts aiming to meet the expectation of the Turkish people of TV 8 TV channels. Survivor, one of the TV 8 programs, draws attention with the ratings it receives and the broad target audience it addresses. Survivor, however, is one of the most exciting competitions on the Turkish television scene, which is rightly and ambitiously competitive in television contest programs. It is a format in which women and men struggle their power borders by winning the competition with their names thanks to their intelligence and endurance games. The contestants of the program, which has been running since March 22, 2005, are seen in a platform where they must present their struggle for their various awards. In Survivor, where competition is at stake, courage and strength are reduced by the reduction of sex. In this study, the critical discourse was made taking into consideration the challenges of female competitors competing to the final stage which is behind the male competitors. Secondly, the variables from the beginning to the present day of the adaptation of the judge to Turkey have been debated in a critical context.Keywords: television, meaning, discourse, contest program
Procedia PDF Downloads 223741 Covid-19 Associated Stress and Coping Strategies
Authors: Bar Shapira-Youngster, Sima Amram-Vaknin, Yuliya Lipshits-Braziler
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The study examined how 811 Israelis experienced and coped with the COVID-19 lockdown. Stress, uncertainty, and loss of control were reported as common emotional experiences. Two main difficulties were reported: Loneliness and health and emotional concerns. Frequent explanations for the virus's emergence were: scientific or faith reasoning. The most prevalent coping strategies were distraction activities and acceptance. Reducing the use of maladaptive coping strategies has important implications for mental health outcomes. Objectives: COVID-19 has been recognized as a collective, continuous traumatic stressor. The present study examined how individuals experienced, perceived, and coped with this traumatic event during the lockdown in Israel in April 2020. Method: 811 Israelis (71.3% were women; mean age 43.7, SD=13.3)completed an online semi-structured questionnaire consisting two sections: In the first section, participants were asked to report background information. In the second section, they were asked to answer 8 open-ended questions about their experience, perception, and coping with the covid-19 lockdown. Participation was voluntary, and anonymity was assured, they were not offered compensation of any kind. The data were subjected to qualitative content analysis that seeks to classify the participants` answers into an effective number of categories that represent similar meanings. Our content analysis of participants’ answers extended far beyond simple word counts; our objective was to try to identify recurrent categories that characterized participants’ responses to each question. We sought to ensure that the categories regarding the different questions are as mutually exclusive and exhaustive as possible. To ensure robust analysis, the data were initially analyzed by the first author, and a second opinion was then sought from research colleagues. Contribution: The present research expands our knowledge of individuals' experiences, perceptions, and coping mechanisms with continuous traumatic events. Reducing the use of maladaptive coping strategies has important implications for mental health outcomes.Keywords: Covid-19, emotional distress, coping, continuous traumatic event
Procedia PDF Downloads 131740 Creativity, Formative Assessment and Students’ Writing of Subject-Specific Texts
Authors: Per Blomqvist
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This study is part of a larger research project on creativity and writing cultures in upper secondary schools in Sweden, with the purpose of exploring how formative assessment practices can be developed to better support students' writing of subject-specific texts. The purpose of the study is to shed light on how writing has changed over time in the subjects of Social Studies and Swedish, especially regarding changes in the formative assessment practice in relation to students opportunities to take part in creative writing processes that can develop their subject specific-writing. Theoretically, the study is based on concepts and models concerning creativity, writing instructions and formative assessment, especially regarding scaffolding in relation to the development of students' subject-specific writing. The empirical data consists of video recordings of teacher groups' conversations from five upper secondary schools in Sweden, compromising a total of twenty teachers. The conversations were conducted as so-called collective remembering interviews, a method to stimulate the participants' memory through social interaction, and focused on addressing issues on how writing assessment has changed over time. Topic analysis was used to analyze the conversations in order to identify common descriptions and expressions among the teachers in each group. The result highlights two different assessment practices that are described as giving students different opportunities to take part in creative writing processes to develop their writing of subject-specific texts. One of the assessment practices is characterized by teachers focusing on explaining to the students what the grading criteria mean and showing sample texts that correspond to a certain grade. The teachers describe that this assessment practice has led to a formalized, instrumental and product-oriented writing culture that has negative consequences for the student's development of their subject-specific writing, which often lacks independent reasoning, own conclusions and understanding of concepts. The other assessment practice is characterized by students examining text qualities and discussing a variety of sample texts to understand what different texts require. These teachers describe the assessment practice as an exploratory work that leads to more creative writing processes where the students gradually deepen their understanding of subject-specific texts and develop their writing.Keywords: teaching for creativity, writing processes, formative assessment, subject-specific writing
Procedia PDF Downloads 55739 The Effect of Artificial Intelligence on Decoration
Authors: Ashraf Fayz Bekhet Abaskron
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This research is done to create new compositions for designs, finding inspiration from watercolor artworks displayed in SuanSunandha Palace. The researcher made a study in the history of the landmark, its importance, the paintings in the Palace, the types and characteristics of the flowers painted, as well as the artistic elements and principles of designs that went into the paintings. The information obtained led to the creation of six totally new designs. The designs incorporated standard international designs and artistic principles and still kept to the original style of the watercolor paintings in SuanSunandha Palace. Following the paintings, the designs are divided into three categories: Orchids, Roses, and Flowers from literature. The researcher used the components of the flowers including rounded-petal flowers, wavy-edged petals, flowers with pointed petals, leaves, vines, and branches. All of them are represented in the original paintings. Upon the original, the researcher switched these elements and their proportions around to create a more modern design. The original forms are used as references since they contain the characteristics of each flower species. The work created achieved an updated trait and simultaneously reflects the charms and timeless beauty of the watercolor paintings displayed in SuanSunandha Palace, which still exists in today’s world.Keywords: art, craft, design, Oman, weaving watercolor, painting, flower, Suan Sunandhagolden ratio, Fibonacci numbers, textile design, designs
Procedia PDF Downloads 36738 Effect of Different Ground Motion Scaling Methods on Behavior of 40 Story RC Core Wall Building
Authors: Muhammad Usman, Munir Ahmed
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The demand of high-rise buildings has grown fast during the past decades. The design of these buildings by using RC core wall have been widespread nowadays in many countries. The RC core wall (RCCW) buildings encompasses central core wall and boundary columns joined through post tension slab at different floor levels. The core wall often provides greater stiffness as compared to the collective stiffness of the boundary columns. Hence, the core wall dominantly resists lateral loading i.e. wind or earthquake load. Non-linear response history analysis (NLRHA) procedure is the finest seismic design procedure of the times for designing high-rise buildings. The modern design tools for nonlinear response history analysis and performance based design has provided more confidence to design these structures for high-rise buildings. NLRHA requires selection and scaling of ground motions to match design spectrum for site specific conditions. Designers use several techniques for scaling ground motion records (time series). Time domain and frequency domain scaling are most commonly used which comprises their own benefits and drawbacks. Due to lengthy process of NLRHA, application of only one technique is conceivable. To the best of author’s knowledge, no consensus on the best procedures for the selection and scaling of the ground motions is available in literature. This research aims to provide the finest ground motion scaling technique specifically for designing 40 story high-rise RCCW buildings. Seismic response of 40 story RCCW building is checked by applying both the frequency domain and time domain scaling. Variable sites are selected in three critical seismic zones of Pakistan. The results indicates that there is extensive variation in seismic response of building for these scaling. There is still a need to build a consensus on the subjected research by investigating variable sites and buildings heights.Keywords: 40-storied RC core wall building, nonlinear response history analysis, ground motions, time domain scaling, frequency domain scaling
Procedia PDF Downloads 132737 The Impact of Artificial Intelligence on Textiles Technology
Authors: Ramy Kamel Fekrey Gadelrab
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Textile sensors have gained a lot of interest in recent years as it is instrumental in monitoring physiological and environmental changes, for a better diagnosis that can be useful in various fields like medical textiles, sports textiles, protective textiles, agro textiles, and geo-textiles. Moreover, with the development of flexible textile-based wearable sensors, the functionality of smart clothing is augmented for a more improved user experience when it comes to technical textiles. In this context, conductive textiles using new composites and nanomaterials are being developed while considering its compatibility with the textile manufacturing processes. This review aims to provide a comprehensive and detailed overview of the contemporary advancements in textile-based wearable physical sensors, used in the field of medical, security, surveillance, and protection, from a global perspective. The methodology used is through analysing various examples of integration of wearable textile-based sensors with clothing for daily use, keeping in mind the technological advances in the same. By comparing various case studies, it come across various challenges textile sensors, in terms of stability, the comfort of movement, and reliable sensing components to enable accurate measurements, in spite of progress in the engineering of the wearable. Addressing such concerns is critical for the future success of wearable sensors.Keywords: nanoparticles, enzymes, immobilization, textilesconductive yarn, e-textiles, smart textiles, thermal analysisflexible textile-based wearable sensors, contemporary advancements, conductive textiles, body conformal design
Procedia PDF Downloads 49736 Urban Meetings: Graphic Analysis of the Public Space in a Cultural Building from São Paulo
Authors: Thalita Carvalho Martins de Castro, Núbia Bernardi
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Currently, studies evidence that our cities are portraits of social relations. In the midst of so many segregations, cultural buildings emerge as a place to assemble collective activities and expressions. Through theater, exhibitions, educational workshops, libraries, the architecture approaches human relations and seeks to propose meeting places. The purpose of this research is to deepen the discussions about the contributions of cultural buildings in the use of the spaces of the contemporary city, based on the data and measure collected in the master's research in progress. The graphic analysis of the insertion of contemporary cultural buildings seeks to highlight the social use of space. The urban insertions of contemporary cultural buildings in the city of São Paulo (Brazil) will be analyzed to understand the relations between the architectural form and its audience. The collected data describe a dynamic of flows and the permanence in the use of these spaces, indicating the contribution of the cultural buildings, associated with artistic production, in the dynamics of urban spaces and the social modifications of their milieu. Among the case studies, the research in development is based on the registration and graphic analysis of the Praça das Artes (2012) building located in the historical central region of the city, which after a long period of great degradation undergoes a current redevelopment. The choice of this building was based on four parameters, both on the architectural scale and on the urban scale: urban insertion, local impact, cultural production and a mix of uses. For the analysis will be applied two methodologies of graphic analysis, one with diagrams accompanied by texts and another with the active analysis for open space projects using complementary graphic methodologies, with maps, plants, info-graphics, perspectives, time-lapse videos and analytical tables. This research aims to reinforce the debates between the methodologies of form-use spaces and visual synthesis applied in cultural buildings, in order that new projects can structure public spaces as catalysts for social use, generating improvements in the daily life of its users and in the cities where they are inserted.Keywords: cultural buildings, design methodologies, graphic analysis, public spaces
Procedia PDF Downloads 307735 Development of Fuzzy Logic Control Ontology for E-Learning
Authors: Muhammad Sollehhuddin A. Jalil, Mohd Ibrahim Shapiai, Rubiyah Yusof
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Nowadays, ontology is common in many areas like artificial intelligence, bioinformatics, e-commerce, education and many more. Ontology is one of the focus areas in the field of Information Retrieval. The purpose of an ontology is to describe a conceptual representation of concepts and their relationships within a particular domain. In other words, ontology provides a common vocabulary for anyone who needs to share information in the domain. There are several ontology domains in various fields including engineering and non-engineering knowledge. However, there are only a few available ontology for engineering knowledge. Fuzzy logic as engineering knowledge is still not available as ontology domain. In general, fuzzy logic requires step-by-step guidelines and instructions of lab experiments. In this study, we presented domain ontology for Fuzzy Logic Control (FLC) knowledge. We give Table of Content (ToC) with middle strategy based on the Uschold and King method to develop FLC ontology. The proposed framework is developed using Protégé as the ontology tool. The Protégé’s ontology reasoner, known as the Pellet reasoner is then used to validate the presented framework. The presented framework offers better performance based on consistency and classification parameter index. In general, this ontology can provide a platform to anyone who needs to understand FLC knowledge.Keywords: engineering knowledge, fuzzy logic control ontology, ontology development, table of content
Procedia PDF Downloads 300734 [Keynote Talk]: Swiss Scientific Society for Developing Countries: A Concept of Relationship
Authors: Jawad Alzeer
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Cultural setup is varied from country to country and nation to nation, but the ability to adapt successfully to the new cultural setup may pave the way toward the development of cultural intelligence. Overcoming differences may require to build up our personality with the ability to learn, exchange thoughts, and have a constructive dream. Adaptation processes can be accelerated if we effectively utilize our cultural diversity. This can be done through a unified body or society; people with common goals can collectively work to satisfy their values. Narrowing the gap between developed and developing countries is of prime importance. Many international organizations are trying to resolve these issues by rational and peaceful means. Failing to understand the cultural differences, mentalities, strengths and weaknesses of developed and developing countries led to the collapse of many partnerships. Establishment of a neutral body influenced by developed countries intellectuality and developing countries personality may offer a better understanding and reasonable solutions, suggestions, advice that may assist in narrowing gaps and promote-strengthening relationship between developed and developing countries. The key issues, goals, and potential concepts associated with initiating Swiss scientific society for developing countries as a model to facilitate integration of highly skilled scientists are discussed.Keywords: cultural diversity, developing countries, integration, Switzerland
Procedia PDF Downloads 809733 Risk Mitigation of Data Causality Analysis Requirements AI Act
Authors: Raphaël Weuts, Mykyta Petik, Anton Vedder
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Artificial Intelligence has the potential to create and already creates enormous value in healthcare. Prescriptive systems might be able to make the use of healthcare capacity more efficient. Such systems might entail interpretations that exclude the effect of confounders that brings risks with it. Those risks might be mitigated by regulation that prevents systems entailing such risks to come to market. One modality of regulation is that of legislation, and the European AI Act is an example of such a regulatory instrument that might mitigate these risks. To assess the risk mitigation potential of the AI Act for those risks, this research focusses on a case study of a hypothetical application of medical device software that entails the aforementioned risks. The AI Act refers to the harmonised norms for already existing legislation, here being the European medical device regulation. The issue at hand is a causal link between a confounder and the value the algorithm optimises for by proxy. The research identifies where the AI Act already looks at confounders (i.a. feedback loops in systems that continue to learn after being placed on the market). The research identifies where the current proposal by parliament leaves legal uncertainty on the necessity to check for confounders that do not influence the input of the system, when the system does not continue to learn after being placed on the market. The authors propose an amendment to article 15 of the AI Act that would require high-risk systems to be developed in such a way as to mitigate risks from those aforementioned confounders.Keywords: AI Act, healthcare, confounders, risks
Procedia PDF Downloads 261732 IoT and Advanced Analytics Integration in Biogas Modelling
Authors: Rakesh Choudhary, Ajay Kumar, Deepak Sharma
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The main goal of this paper is to investigate the challenges and benefits of IoT integration in biogas production. This overview explains how the inclusion of IoT can enhance biogas production efficiency. Therefore, such collected data can be explored by advanced analytics, including Artificial intelligence (AI) and Machine Learning (ML) algorithms, consequently improving bio-energy processes. To boost biogas generation efficiency, this report examines the use of IoT devices for real-time data collection on key parameters, e.g., pH, temperature, gas composition, and microbial growth. Real-time monitoring through big data has made it possible to detect diverse, complex trends in the process of producing biogas. The Informed by advanced analytics can also help in improving bio-energy production as well as optimizing operational conditions. Moreover, IoT allows remote observation, control and management, which decreases manual intervention needed whilst increasing process effectiveness. Such a paradigm shift in the incorporation of IoT technologies into biogas production systems helps to achieve higher productivity levels as well as more practical biomass quality biomethane through real-time monitoring-based proactive decision-making, thus driving continuous performance improvement.Keywords: internet of things, biogas, renewable energy, sustainability, anaerobic digestion, real-time monitoring, optimization
Procedia PDF Downloads 21731 Determining Fire Resistance of Wooden Construction Elements through Experimental Studies and Artificial Neural Network
Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir
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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.
Procedia PDF Downloads 385730 Design Thinking Activities: A Tool in Overcoming Student Reticence
Authors: Marinel Dayawon
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Student participation in classroom activities is vital in the teaching- learning the process as it develops self-confidence, social relationships and good academic performance of students. It is the teacher’s empathetic manner and creativity to create solutions that encourage teamwork and mutual support while dropping the academic competition within the class that hinder every shy student to walk with courage and talk with conviction because they consider their ideas, weak, as compared to the bright students. This study aimed to explore the different design thinking strategies that will change the mindset of shy students in classroom activities, maximizing their participation in all given tasks while sharing their views through ideation and providing them a wider world through compromise agreement within the members of the group, sensitivity to one’s idea, thus, arriving at a collective decision in the development of a prototype that indicates improvement in their classroom involvement. The study used the qualitative type of research. Triangulation is done through participant observation, focus group discussion and interview, documented through photos and videos. The respondents were the second- year Bachelor of Secondary Education students of the Institute of Teacher Education at Isabela State University- Cauayan City Campus. The result of the study revealed that reticent students when involved in game activities through a slap and tap method, writing their clustered ideas, using sticky notes is excited in sharing ideas as it doesn’t use oral communication. It is also observed after three weeks of using the design thinking strategies; shy students volunteer as secretary, rapporteur or group leader in the team- building activities as it represents the ideas of the heterogeneous group, removing the individual identity of the ideas. Superior students learned to listen to the ideas of the reticent students and involved them in the prototyping process of designing a remediation program for high school students showing reticence in the classroom, making their experience as a benchmark. The strategies made a 360- degrees transformation of the shy students, producing their journal log, in their journey to being open. Thus, faculty members are now adopting the design thinking approach.Keywords: design thinking activities, qualitative, reticent students, Isabela, Philippines
Procedia PDF Downloads 225729 The Impact of Artificial Intelligence on Spare Parts Technology
Authors: Amir Andria Gad Shehata
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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management
Procedia PDF Downloads 65728 Seismic Hazard Prediction Using Seismic Bumps: Artificial Neural Network Technique
Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli
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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.Keywords: earthquake prediction, ANN, seismic bumps
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