Search results for: legal training

Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

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Authors: Shawnrece Campbell

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Emotional intelligence as an essential job skill is growing in popularity among human resource professionals and hiring managers. Companies value those who have high emotional intelligence because of their personal competences (self-awareness, self-regulation, motivation) and social competences (empathy, social skills). In implementing any training system to teach emotional intelligence, the best methodologies for acquiring and/or improving these competences should be taken into consideration. This study focuses on how students perceived the art of writing as a tool for self-improvement. During this session, participants will engage in a brief activity designed to help students develop emotional intelligence. As a part of the discussion, participants will learn the results of a junior-level literary seminar conducted to better understand students’ thoughts and views about the effectiveness of writing as a tool for emotional healing. An analysis of qualitative textual data is presented. The outcomes indicated that students found using writing as a tool for emotional intelligence development as highly effective. The findings also revealed that students have positive perceptions of using writing as a self-healing art that leads to increased emotional intelligence and believe that writing courses of this nature enhance students’ appreciation of the value of the liberal arts.

Keywords: emotional intelligence quotient, healing, soft skills, writing

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Authors: Angelika Dorawa, Lena Kreppel

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Writing in the disciplines plays a major role at Universities. On the one hand, lectures look at the substance of assignments and on the other hand, they expect students to meet professional standards of layout and proofreading. However, the integration of writing concepts into the range of subjects is new to German Universities of Applied Sciences, which are focused on technical and scientific contexts. The Westphalian University of Applied Sciences (WH) established a successful program Talente_schreiben (Writing_Talents) that was funded by the Federal Ministry of Education and Research to improve written language skills for first-semester students at the WH. Besides having the main focus on basic language skills on all language levels, we also concentrate on subject-specific programs such as writing in the disciplines and are pioneers in this field in Germany. Since 2013, we started to include learning-to-write programs since first-semester students of Business Law studies must complete a writing assignment in the form and writing style of a legal opinion in order to fulfill their undergraduate degree requirements. To support our students at its best, our course for business lawyers focuses not only on the writing skills per se, but also on teaching both, the content and the particular discourse of the discipline. Hence, a specialist in German studies and a faculty tutor share the experience of processing, producing and reflecting a text. Whereas the German studies specialist refers to the rhetorical context such as orthography, grammar etc., the tutor acts as a guide on the side referring to the course content itself. In our presentation, we want to give an insight of the practice of a business law discipline, the combination of rhetoric and composition and discuss the methodological and didactic approaches.

Keywords: German for business lawyers, talent development, pioneer program, Germany

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Authors: Deanna Ruano-Meas, Laura Shenkman

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Variances are seen in the way healthcare personnel (HCP) don and doff PPE risking contamination to self and others. By standardizing practice, variances in technique decrease, and so does the risk of contamination. To implement this change, the Model for Improvement will be used. A system change will be developed that will outline the role of the organizational leader’s support of HCP in the proper donning and doffing of PPE. Interventions will include environmental surveys to assess the safety and work situation ensuring a permissible environment, plan audits to confirm consistency, and the assessment of PPE wear for standardization. The change will also include an educational plan that will involve instruction of the current guidelines recommended by the Centers for Disease Control and Prevention (CDC) to all pertinent HCP, and the incorporation of PPE education in yearly educational training. The goal is a standardized practice and a reduced risk of contamination through education and organizational support. Personal protective equipment has had recent attention with the coming of the SARS-CoV-2. The realization that proper technique is important to decreasing contamination of pathogens has led to the revising of current processes.

Keywords: donning and doffing, HAI, infection control, PPE

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Authors: Stephen L. Roberts

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This article offers a critical analysis of the rise of syndromic surveillance systems for the advanced detection of pandemic threats within contemporary global health security frameworks. The article traces the iterative evolution and ascendancy of three such novel syndromic surveillance systems for the strengthening of health security initiatives over the past two decades: 1) The Program for Monitoring Emerging Diseases (ProMED-mail); 2) The Global Public Health Intelligence Network (GPHIN); and 3) HealthMap. This article demonstrates how each newly introduced syndromic surveillance system has become increasingly oriented towards the integration of digital algorithms into core surveillance capacities to continually harness and forecast upon infinitely generating sets of digital, open-source data, potentially indicative of forthcoming pandemic threats. This article argues that the increased centrality of the algorithm within these next-generation syndromic surveillance systems produces a new and distinct form of infectious disease surveillance for the governing of emergent pathogenic contingencies. Conceptually, the article also shows how the rise of this algorithmic mode of infectious disease surveillance produces divergences in the governmental rationalities of global health security, leading to the rise of an algorithmic governmentality within contemporary contexts of Big Data and these surveillance systems. Empirically, this article demonstrates how this new form of algorithmic infectious disease surveillance has been rapidly integrated into diplomatic, legal, and political frameworks to strengthen the practice of global health security – producing subtle, yet distinct shifts in the outbreak notification and reporting transparency of states, increasingly scrutinized by the algorithmic gaze of syndromic surveillance.

Keywords: algorithms, global health, pandemic, surveillance

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Authors: Marko Kolaković, Mladen Turuk

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Entrepreneurship is a valuable discipline important for the competitiveness of the European economy. The European Union's economy is constantly changing, and there is an increased demand for special knowledge and skills to help actors cope in a turbulent business environment. By promoting entrepreneurship in education, the citizens of the European Union are encouraged to be enterprising, innovative, and creative in designing solutions to perceived commercial and social problems in the form of offered products and services created as a result of the entrepreneurial process. The European Union has developed a series of guidelines to encourage entrepreneurship in education and training, and it supports entrepreneurship itself through various activities such as Erasmus + and other programs. A number of tools have been developed to support the development of entrepreneurial spirit among the citizens of the European Union. Special emphasis is placed on the methods of developing creativity, critical thinking, and the development of digital competencies. The aim of this paper is to investigate the initiatives of the European Union in the field of entrepreneurship education and to analyze the concept of entrepreneurship education in selected EU member states. Also, an overview of the desired learning outcomes acquired as a result of the successfully completed entrepreneurship education process will be provided.

Keywords: entrepreneurship, entrepreneurial education, EU, croatia

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Authors: Prakash Chandra Subedi

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Family farming is the family based farming activities, where the farmers cultivate their farm themselves and all the members of the family are engaged in farming as per their skill, age, and physical strength. This study was conducted to examine the food sufficiency level of family farmers and, was carried in the four VDCs of Kavrepalanchowk district -Jaisithok Mandan, Mahadevsthan Mandan and Gairi Bisouna Deupur. A total of 115 households determined as the sample size from each of the four VDCs were randomly visited for interview in the study. The size of land holding was found to be very small and fragmented. The quality of soil was fertile and could yield high production if irrigation existed. The labour used patterns were significant number of family labour but due to high youth migration there were labour shortage. The rate of adoption of agri-technology was low but the households adopting insectides/pesticides and chemical fertilizers were found to be high without any knowledge regarding its using techniques. In conclusion, the study highpoint that the crop production and food sufficiency level of the family farmers of the Kavrepalanchowk district is decreasing. Many farmers were leaving their farming and started seeking opportunity to go for foreign employment or engaged in non-agricultural activities in urban areas. If no action is taken timely, there may come situation that we will have to depend on imports for all the food requirements. Thus, the study reveals that the family farming could act as an agent for ensuring food sufficiency for all, if proper policies is promoted to family farmers with legal titles to their land or promoted with sustainable agriculture methods or provided with proper agri-technology or given their share of respect and responsibilities that farming as honorable profession.

Keywords: family farming, technology transfer, crop production, food sufficiency

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Sajedeh Salehi, Marco Giacalone

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This paper examines the role of existing online dispute resolution (ODR) mechanisms and their effects on ameliorating access to justice – as a protected right by Art. 47 of the EU Charter of Fundamental Rights – for consumers in EU. The major focus of this study will be on evaluating ODR as the means of dispute resolution for Business-to-Consumer (B2C) cross-border small claims raised in e-commerce transactions. The authors will elaborate the consequences of implementing ODR methods in the context of recent developments in EU regulatory safeguards on promoting consumer protection. In this analysis, both non-judiciary and judiciary ODR redress mechanisms are considered, however, the significant consideration is given to – obligatory and non-obligatory – judiciary ODR methods. For that purpose, this paper will particularly investigate the impact of the EU ODR platform as well as the European Small Claims Procedure (ESCP) Regulation 861/2007 and their role on accelerating the access to justice for consumers in B2C e-disputes. Although, considerable volume of research has been carried out on ODR for consumer claims, rather less (or no-) attention has been paid to provide a combined doctrinal and empirical evaluation of ODR’s potential in resolving cross-border small e-disputes, in EU. Hence, the methodological approach taken in this study is a mixed methodology based on qualitative (interviews) and quantitative (surveys) research methods which will be mainly based on the data acquired through the findings of the Small Claims Analysis Net (SCAN) project. This project contributes towards examining the ESCP Regulation implementation and efficiency in providing consumers with a legal watershed through using the ODR for their transnational small claims. The outcomes of this research may benefit both academia and policymakers at national and international level.

Keywords: access to justice, consumers, e-commerce, small e-Disputes

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Authors: Jumana Majdi Qutub

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Rationale: Cloud computing has rapidly developed the past few years. Because of the importance of providing protection for personal data used in cloud computing, the role of data protection in promoting trust and confidence in users’ data has become an important policy priority. This research examines key regulatory challenges rose by the growing use and importance of cloud computing with focusing on protection of individuals personal data. Methodology: Describing and analyzing governance challenges facing policymakers and industry in Saudi Arabia, with an account of anticipated governance responses. The aim of the research is to describe and define the regulatory challenges on cloud computing for policy making in Saudi Arabia and comparing it with potential complied issues rose in respect of transported data to EU member state. In addition, it discusses information privacy issues. Finally, the research proposes policy recommendation that would resolve concerns surrounds the privacy and effectiveness of clouds computing frameworks for data protection. Results: There are still no clear regulation in Saudi Arabia specialized in legalizing cloud computing and specialty regulations in transferring data internationally and locally. Decision makers need to review the applicable law in Saudi Arabia that protect information in cloud computing. This should be from an international and a local view in order to identify all requirements surrounding this area. It is important to educate cloud computing users about their information value and rights before putting it in the cloud to avoid further legal complications, such as making an educational program to prevent giving personal information to a bank employee. Therefore, with many kinds of cloud computing services, it is important to have it covered by the law in all aspects.

Keywords: cloud computing, cyber crime, data protection, privacy

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Authors: Hafiz Khubaib Ur Rehman Awan

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Education used to play a central role in the formation and transfiguration of society since early times, owing in part to the centrality of scripture and its study in the human circles. According to the Islamic purpose of education, its pivotal contribution in the society is to produce a balanced growth of the entire persona of an individual through training the spirit, intellect, rational self, feelings, and bodily senses such that faith is infused into the whole personality. The purpose of this study is to attempt the exploration of the development of the Islamic religious curriculum in the Islamic world with an emphasis on Pakistan because this homeland came into existence under the name of Islam. This study persists of necessary historical background on the curricular reform of religious education in Pakistan and their impact on it and the suburban countries. However, the mainstay of this paper bases on reform in the religious education curriculum and the challenges faced by Pakistan and the Islamic world. Some suggestions are positioned at the end for areas of Islamic religious education and the improvement of Islamic curricular reform, especially in Pakistan and generally in Muslim countries.

Keywords: curricula, religious educational institutions, Pakistan, Muslim world, educational, religious , curricula

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Authors: Amedeo D'Angiulli, Kylie Schibli

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Traditionally, children’s brain development research has emphasized the limitative aspects of disability and impairment, electing as an explanatory model the classical clinical notions of brain lesion or functional deficit. In contrast, Positive Educational Neuroscience (PEN) is a new approach that emphasizes strengths and human flourishing related to the brain by exploring how learning practices have the potential to enhance neurocognitive flexibility through neuroplastic overcompensation. This mini-review provides an overview of PEN and shows how it links to the concept of neurocognitive flexibility. We provide examples of how the present concept of neurocognitive flexibility can be applied to special education by exploring examples of neuroplasticity in the learning domain, including: (1) learning to draw in congenitally totally blind children, and (2) music training in children from disadvantaged neighborhoods. PEN encourages educators to focus on children’s strengths by recognizing the brain’s capacity for positive change and to incorporate activities that support children’s individual development.

Keywords: neurocognitive development, positive educational neuroscience, sociocultural approach, special education

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Authors: Svitlana Yermak, Olubukola Aluko

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The purpose of this study was a literature review on the topic of social entrepreneurship, a review of new trends and best practices, the study of existing inclusive business models and their interaction with the principles of the circular economy for possible implementation in the practice of Ukraine in war and post-war times in conditions of scarce resources. Thus, three research questions were identified and substantiated: to determine the characteristics of social entrepreneurship, consider the features in Ukraine and the UK; highlight the criteria for inclusion in social entrepreneurship and its legal support; explore examples of existing inclusive circular business models to illustrate how the two concepts may be combined. A detailed review of the literature selected from the Scopus and Web of Science databases was carried out. The study revealed signs of social entrepreneurship, the main of which are doing business and making a profit, as well as the social orientation of the business, which is prescribed in the constituent documents of the enterprise immediately upon its creation. Considered are the characteristics of social entrepreneurship in the UK and Ukraine. It has been established that in the UK, social entrepreneurship is clearly regulated by the state; there are special legislative norms and support programs, in contrast to Ukraine, where these processes are only partially regulated. The study identified the main criteria for inclusion in inclusive circular business models: economic (sustainability and efficiency, job creation and economic growth, promotion of local development), social (accessibility, equity and fairness, inclusion and participation), and resources in their interconnection. It is substantiated that the resource criterion is especially important for this type of business model. It provides for the efficient and sustainable use of resources, as well as the cyclical nature of resources. And it was concluded that the principles of the circular economy not only do not contradict but, on the contrary, complement and expand the inclusive business models on which social entrepreneurship is based.

Keywords: social entrepreneurship, inclusive business models, circular economy, inclusion criteria

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

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Authors: Uma Maheshwari V., Rajanikanth Aluvalu, Kumar Gautam

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The COVID-19 disease is a highly contagious viral infection with major worldwide health implications. The global economy suffers as a result of COVID. The spread of this pandemic disease can be slowed if positive patients are found early. COVID-19 disease prediction is beneficial for identifying patients' health problems that are at risk for COVID. Deep learning and machine learning algorithms for COVID prediction using X-rays have the potential to be extremely useful in solving the scarcity of doctors and clinicians in remote places. In this paper, a convolutional neural network (CNN) with deep layers is presented for recognizing COVID-19 patients using real-world datasets. We gathered around 6000 X-ray scan images from various sources and split them into two categories: normal and COVID-impacted. Our model examines chest X-ray images to recognize such patients. Because X-rays are commonly available and affordable, our findings show that X-ray analysis is effective in COVID diagnosis. The predictions performed well, with an average accuracy of 99% on training photographs and 88% on X-ray test images.

Keywords: deep CNN, COVID–19 analysis, feature extraction, feature map, accuracy

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Authors: Dariusz Jemielniak

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The near future will bring significant changes to contemporary organizations and management, because of the rapidly increasing role of immaterial goods and knowledge workers. The area of copyright, IP, as well as digital (non-material) goods and media redistribution seems to be one of the major challenges for the economy and society in general, and management and organization studies in particular. The proposed paper shows the views and perceptions of fairness of digital media sharing among Harvard Law School LL.M. students, basing on 50 qualitative interviews and 100 questionnaires. The researcher took an ethnographic approach to the study and joined the 2016 Harvard LL.M. Facebook group, which allowed natural socializing and joining for in-person events and private parties more easily. After making acquaintance with many of the students, the researcher conducted a quantitative questionnaire with 100 respondents, allowing to better understand the respondents perception of fairness in digital files sharing in different contexts (depending on the price of the media, its availability, regional licensing, status of the copyright holder, etc.). Basing on the results of the questionnaire, the researcher followed up with long-term, open ended, loosely structured ethnographic interviews (50 interviews were conducted) to further deepen the understanding of the results. The major finding of the study is that Harvard lawyers, in spite of the highest possible understanding of law, as well as professional standards, generally approve of digital piracy in certain contexts. Interestingly, they are also more likely to approve of it if they work for the government rather than the private sector. The conclusions from this study allow a better understanding of how ‘fairness’ is perceived by the younger generation of law professionals, and also open grounds for a more rational licensing policing.

Keywords: piracy, digital sharing, perception of fairness, legal profession

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Authors: Ssekamanya, Mastura Badzis, Khamsiah Ismail, Dayang Shuzaidah Bt Abduludin

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With rising incidents of school violence worldwide, educators and researchers are trying to understand and find ways to enhance the safety of children at school. The purpose of this study was to investigate the extent to which the demographic variables of gender, age, length of service, position, academic qualification, and school location predicted teachers’ awareness about school safety practices in Malaysian primary schools. A stratified random sample of 380 teachers was selected in the central Malaysian states of Kuala Lumpur and Selangor. Multiple regression analysis revealed that none of the factors was a good predictor of awareness about school safety training, delivery methods of school safety information, and available school safety programs. Awareness about school safety activities was significantly predicted by school location (whether the school was located in a rural or urban area). While these results may reflect a general lack of awareness about school safety among primary school teachers in the selected locations, a national study needs to be conducted for the whole country.

Keywords: school safety awareness, predictors of school safety, multiple regression analysis, malaysian primary schools

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Authors: Heba Elbibas, Esra Gnijeewa, Zedan Hatush

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This paper presents research on occupational safety in construction projects, where the importance of safety management in projects was studied, including the preparation of a safety plan and program for each project and the identification of the responsibilities of each party to the contract. The research consists of two parts: 1-Field visits: which were field visits to three construction projects, including building projects, road projects, and tower installation. The safety level of these projects was evaluated through a checklist that includes the most important safety elements in terms of the application of these items in the projects. 2-Preparation of a questionnaire: which included supervisors and engineers and aimed to determine the level of awareness and commitment of different project categories to safety standards. The results showed the following: i) There is a moderate occupational safety policy. ii) The preparation and storage of maintenance reports are not fully complied with. iii) There is a moderate level of training on occupational safety for project workers. iv) The company does not impose penalties on safety violators permanently. v) There is a moderate policy for equipment and machinery safety. vi) Self-injuries occur due to (fatigue, lack of attention, deliberate error, and emotional factors), with a rate of 82.4%.

Keywords: management, safety, occupational safety, classification

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Authors: Carmen Axisa, Louise Nash, Patrick Kelly, Simon Willcock

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Introduction: Doctors experience high levels of burnout, stress and psychiatric morbidity. This can affect the health of the doctor and impact patient care. Study Aims: To evaluate the effectiveness of a workshop intervention to promote wellbeing for Australian Physician Trainees. Methods: A workshop was developed in consultation with specialist clinicians to promote health and wellbeing for physician trainees. The workshop objectives were to improve participant understanding about factors affecting their health and wellbeing, to outline strategies on how to improve health and wellbeing and to encourage participants to apply these strategies in their own lives. There was a focus on building resilience and developing long term healthy behaviours as part of the physician trainee daily lifestyle. Trainees had the opportunity to learn practical strategies for stress management, gain insight into their behaviour and take steps to improve their health and wellbeing. The workshop also identified resources and support systems available to trainees. The workshop duration was four and a half hours including a thirty- minute meal break where a catered meal was provided for the trainees. Workshop evaluations were conducted at the end of the workshop. Sixty-seven physician trainees from Adult Medicine and Paediatric training programs in Sydney Australia were randomised into intervention and control groups. The intervention group attended a workshop facilitated by specialist clinicians and the control group did not. Baseline and post intervention measurements were taken for both groups to evaluate the impact and effectiveness of the workshop. Forty-six participants completed all three measurements (69%). Demographic, personal and self-reported data regarding work/life patterns was collected. Outcome measures include Depression Anxiety Stress Scale (DASS), Professional Quality of Life Scale (ProQOL) and Alcohol Use Disorders Identification Test (AUDIT). Results: The workshop was well received by the physician trainees and workshop evaluations showed that the majority of trainees strongly agree or agree that the training was relevant to their needs (96%) and met their expectations (92%). All trainees strongly agree or agree that they would recommend the workshop to their medical colleagues. In comparison to the control group we observed a reduction in alcohol use, depression and burnout but an increase in stress, anxiety and secondary traumatic stress in the intervention group, at the primary endpoint measured at 6 months. However, none of these differences reached statistical significance (p > 0.05). Discussion: Although the study did not reach statistical significance, the workshop may be beneficial to physician trainees. Trainees had the opportunity to share ideas, gain insight into their own behaviour, learn practical strategies for stress management and discuss approach to work, life and self-care. The workshop discussions enabled trainees to share their experiences in a supported environment where they learned that other trainees experienced stress and burnout and they were not alone in needing to acquire successful coping mechanisms and stress management strategies. Conclusion: These findings suggest that physician trainees are a vulnerable group who may benefit from initiatives that promote wellbeing and from a more supportive work environment.

Keywords: doctors' health, physician burnout, physician resilience, wellbeing workshop

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Authors: Gergely Horváth

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The study presents the complexity of food safety dividing it into two layers. Beyond the basic layer of requirements, there is a more demanding higher level linked with quality and purity aspects. It would be important to give special prominence to both layers, given that massive illnesses are caused by foods even though officially licensed. Then the study discusses an exciting safety challenge stemming from the risks of genetically modified organisms (GMOs). Furthermore, it features legal case examples that illustrate how certain liability questions are solved or not yet decided in connection with the production of genetically modified crops. In addition, a special kind of land grabbing, more precisely land grabbing from non-GMO farming systems can also be noticed as well as a new phenomenon eroding food sovereignty. Coexistence, the state where organic, conventional, and GM farming systems are standing alongside each other is an unsuitable experiment that cannot be successful, because of biophysical reasons (such as cross-pollination). Agricultural and environmental lawyers both try to find the optimal solution. Agri-environmental measures are introduced as a special subfield of law maintaining also food safety. The important steps of agri-environmental legislation are aiming at the protection of natural values, the environmental media and strengthening food safety as well, practically the quality of agricultural products intended for human consumption. The major findings of the study focus on searching for the appropriate approach capable of solving the security and safety problems of food production. The most interesting concepts of the Hungarian national and EU food law legislation are analyzed in more detail with descriptive, analytic and comparative methods.

Keywords: food law, food safety, food security, GMO, Genetically Modified Organisms, agri-environmental measures

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Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita

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In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during changes in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain equal power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.

Keywords: droop control, droop characteristic, grid-connected inverter, microgrid, power control

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Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Joy Winston James, Abdul Kadher Jilani

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This review article provides a comprehensive overview of social engineering attacks, specifically those executed through the Kali Linux operating system. It aims to present an in-depth analysis of the background and importance of social engineering in cybersecurity, the tools, and techniques used in these attacks, real-world case studies that demonstrate their effectiveness, and ethical considerations that need to be taken into account while using them. The article highlights the Kali Linux tools that are commonly used in social engineering attacks, including SET, Metasploit, and BeEF, and discusses techniques such as phishing, pretexting, and baiting that are crucial in conducting successful social engineering attacks. It further explores real-world case studies that demonstrate the effectiveness of these techniques, emphasizing the importance of implementing effective countermeasures to reduce the risk of successful social engineering attacks. Moreover, the article sheds light on ethical considerations that need to be taken into account while using social engineering tools, emphasizing the importance of using them ethically and legally. Finally, the article provides potential countermeasures such as two-factor authentication, strong password policies, and regular security audits to help individuals and organizations better protect themselves against this growing threat. By understanding the tools and techniques used in social engineering attacks and implementing appropriate countermeasures, individuals and organizations can minimize the risk of successful social engineering attacks and improve their cybersecurity posture. To illustrate the effectiveness of social engineering attacks, we present real-world case studies that demonstrate how easily individuals and organizations can fall prey to these attacks. We also discuss ethical considerations that must be taken into account while using social engineering tools, emphasizing the need for responsible and legal use of these tools.

Keywords: pen testing, hacking, Kali Linux, social engineering

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Authors: Muhammad Umair Ahmed, Aftab Shoukat

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Today the global economy has become one of the key strategies in dealing with environmental issues. To allow for a round economy, organizations have begun to work to improve their sustainability management. The contribution of green resource management to the transformation of the global economy has not been investigated. The purpose of the study was to evaluate the effects of green labor management on the global economy, environmental and economic performance, and the organisation's environmental dignity. We strongly evaluate the different roles of the various processes of green personnel management (i.e., green recruitment, training, and engagement green, as well as green performance management and reward) in organizational operations. We are also investigating the leadership role of CEO Ethical. Our outcome will have a positive impact on the performance of the organization. Green Human Resource Management contributes to the evolution of a roundabout economy without the influence of different external factors such as market demand and commitment. Finally, the results of our research will provide a few aspects for future research, both academic and human.

Keywords: sustainability, green human resource management, circular economy, human capital

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Authors: Faruk Inaltekin, Imran Gurakan

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This paper will aim to discuss the importance of value-added services provided by Science and Technology Parks for entrepreneurship development in Turkey. Entrepreneurship is vital subject for all countries. It has not only fostered economic development but also promoted innovation at local and international levels. To foster high tech entrepreneurship ecosystem, Technopark (Science and Technology Park/STP) concept was initiated with the establishment of Silicon Valley in the 1950s. The success and rise of Silicon Valley led to the spread of technopark activities. Developed economies have been setting up projects to plan and build STPs since the 1960s and 1970s. To promote the establishment of STPs, necessary legislations were made by Ministry of Science, Industry, and Technology in 2001, Technology Development Zones Law (No. 4691) and it has been revised in 2016 to provide more supports. STPs’ basic aim is to provide customers high-quality office spaces with various 'value added services' such as business development, network connections, cooperation programs, investor/customers meetings and internationalization services. For this aim, STPs should help startups deal with difficulties in the early stages and to support mature companies’ export activities in the foreign market. STPs should support the production, commercialization and more significantly internationalization of technology-intensive business and foster growth of companies. Nowadays within this value-added services, internationalization is very popular subject in the world. Most of STPs design clusters or accelerator programs in order to support their companies in the foreign market penetration. If startups are not ready for international competition, STPs should help them to get ready for foreign market with training and mentoring sessions. These training and mentoring sessions should take a goal based approach to working with companies. Each company has different needs and goals. Therefore the definition of ‘success' varies for each company. For this reason, it is very important to create customized value added services to meet the needs of startups. After local supports, STPs should also be able to support their startups in foreign market. Organizing well defined international accelerator program plays an important role in this mission. Turkey is strategically placed between key markets in Europe, Russia, Central Asia and the Middle East. Its population is young and well educated. So both government agencies and the private sectors endeavor to foster and encourage entrepreneurship ecosystem with many supports. In sum, the task of technoparks with these and similar value added services is very important for developing entrepreneurship ecosystem. The priorities of all value added services are to identify the commercialization and growth obstacles faced by entrepreneurs and get rid of them with the one-to-one customized services. Also, in order to have a healthy startup ecosystem and create sustainable entrepreneurship, stakeholders (technoparks, incubators, accelerators, investors, universities, governmental organizations etc.) should fulfill their roles and/or duties and collaborate with each other. STPs play an important role as bridge for these stakeholders & entrepreneurs. STPs always should benchmark and renew services offered to how to help the start-ups to survive, develop their business and benefit from these stakeholders.

Keywords: accelerator, cluster, entrepreneurship, startup, technopark, value added services

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Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

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Authors: Ezayra Dubria, Leonora Yambao

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Mother Tongue–Based Multilingual Education (MTB-MLE) is a salient part of the recent reform in the country’s Education system which is the implementation of the K to 12 Basic Education Program. Its importance is highlighted by the passing of Republic Act 10523, otherwise known as the ‘Enhanced Basic Education Act of 2013’. However, teachers, especially new teachers encounter problems in using mother tongue as medium of instruction. Fortunately, teachers are able to create strategies which address these problems. Specifically, this paper gathered the viewpoints of teachers in using mother tongue and analyzed the different problems and strategies used. The problems encountered by teachers are lack of instructional materials written in mother tongue, especially books, lack of vocabulary, lack of teacher training, and influences of social media to learners. The strategies which address these problems are translation of literary pieces and other instructional materials, vocabulary enrichment through the use of word-of-the-day and picture-word association, remedial class, storytelling, differentiated instruction, explicit teaching, individual and group activities, and utilization of multilingual teaching.

Keywords: mother tongue-based instruction, multilingualism, problems, strategies

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

Procedia PDF Downloads 152