Search results for: algorithm symbol recognition

Authors: Saidu I. R., Shittu S. S.

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As the trend of personal devices accessing corporate data continues to rise through Bring Your Own Device (BYOD) practices, organizations recognize the potential cost reduction and productivity gains. However, the associated security risks pose a significant threat to these benefits. Often, organizations adopt BYOD environments without fully considering the vulnerabilities introduced by human factors in this context. This study presents an enhanced assessment model that evaluates the security posture of employees in BYOD environments using cyber hygiene principles. The framework assesses users' adherence to best practices and guidelines for maintaining a secure computing environment, employing scales and the Euclidean distance formula. By utilizing this algorithm, the study measures the distance between users' security practices and the organization's optimal security policies. To facilitate user evaluation, a simple and intuitive interface for automated assessment is developed. To validate the effectiveness of the proposed framework, design science research methods are employed, and empirical assessments are conducted using five artifacts to analyze user suitability in BYOD environments. By addressing the human factor vulnerabilities through the assessment of cyber hygiene practices, this study aims to enhance the overall security of BYOD environments and enable organizations to leverage the advantages of this evolving trend while mitigating potential risks.

Keywords: security, BYOD, vulnerability, risk, cyber hygiene

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Authors: Arthur C. Tsai, Chii-Shyang Kuo, Vincent S. C. Chien, Michelle Liou, Philip E. Cheng

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Meditation enhances mental abilities and it is an antidote to anxiety. However, very little is known about brain mechanisms and cortico-subcortical interactions underlying meditation-induced anxiety relief. In this study, the changes of phase-amplitude coupling (PAC) in which the amplitude of the beta frequency band were modulated in phase with delta rhythm were investigated after eight-week of meditation training. The study hypothesized that through a concentrate but relaxed mental training the delta-beta coupling in the frontal regions is attenuated. The delta-beta coupling analysis was applied to within and between maximally-independent component sources returned from the extended infomax independent components analysis (ICA) algorithm on the continuous EEG data during mediation. A unique meditative concentration task through relaxing body and mind was used with a constant level of moderate mental effort, so as to approach an ‘emptiness’ meditative state. A pre-test/post-test control group design was used in this study. To evaluate cross-frequency phase-amplitude coupling of component sources, the modulation index (MI) with statistics to calculate circular phase statistics were estimated. Our findings reveal that a significant delta-beta decoupling was observed in a set of frontal regions bilaterally. In addition, beta frequency band of prefrontal component were amplitude modulated in phase with the delta rhythm of medial frontal component.

Keywords: phase-amplitude coupling, ICA, meditation, EEG

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Authors: Elzbieta Sikorska-Simmons

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Dementia is a progressive terminal disease. Despite this recognition, research shows that most family caregivers do not know it, and it is unclear how this knowledge affects the quality of patient care. The aim of this qualitative study of 20 family caregivers for patients with advanced dementia is to examine how the caregiver's knowledge about dementia affects the quality of patient care in the context of healthcare decision-making, advanced care planning, and access to adequate support systems. Knowledge about dementia implies family caregivers' understanding of dementia trajectories, common symptoms/complications, and alternative treatment options (e.g., comfort feeding versus tube feeding). Data were collected in semi-structured interviews with 20 family caregivers. The interviews were conducted in person by the author and designed to elicit rich descriptions of family caregivers' experiences with healthcare decision-making and the management of common symptoms/complications of end-stage dementia as patient healthcare proxies. The study findings suggest that caregivers who recognize that dementia is a terminal disease are less likely to opt for life-extending treatments during the advanced stages. They are also more likely to seek palliative/hospice care, and consequently, they are better able to avoid unnecessary hospitalizations or medical procedures. For example, those who know that dementia is a terminal disease tend to opt for "comfort feeding" rather than "tube feeding" in managing the swallowing difficulties that accompany advanced dementia. In the context of advance care planning, family caregivers who know that dementia is a terminal disease tend to have more meaningful advance directives (e.g., Power of Attorney and Do Not Resuscitate orders). They are better prepared to anticipate common problems and pursue treatments that foster the best quality of patient life and care. Greater knowledge about advanced dementia helps them make more informed decisions that focus on enhancing the quality of patient life rather than just survival. In addition, those who know that dementia is a terminal disease are more likely to establish adequate support systems to help them cope with the complex demands of caregiving. For example, they are more likely to seek dementia-oriented primary care programs that offer house visits or respite services. Based on the study findings, knowledge about dementia as a terminal disease is critical in the optimal management of patient care needs and the establishment of adequate support systems. More research is needed to better understand what caregivers need to know to better prepare them for the complex demands of dementia caregiving.

Keywords: dementia education, family caregiver, management of dementia, quality of care

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Authors: Katalin Gombos, Bence Gálik, Krisztina Ildikó Kalács, Krisztina Gödöny, Ákos Várnagy, József Bódis, Attila Gyenesei, Gábor L. Kovács

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Although non-invasive pre-implantation genetic testing for aneuploidy (NIPGT-A) is potentially appropriate to assess chromosomal ploidy of the embryo, practical application of it in a routine IVF center has not been started in the absence of a recommendation. We developed a comprehensive workflow for a clinically applicable strategy for NIPGT-A based on next-generation sequencing (NGS) technology. We performed MALBAC whole genome amplification and NGS on spent blastocyst culture media of Day 3 embryos fertilized with intra-cytoplasmic sperm injection (ICSI). Spent embryonic culture media of morphologically good quality score embryos were enrolled in further analysis with the blank culture media as background control. Chromosomal abnormalities were identified by an optimized bioinformatics pipeline applying a copy number variation (CNV) detecting algorithm. We demonstrate a comprehensive workflow covering both wet- and dry-lab procedures supporting a clinically applicable strategy for NIPGT-A. It can be carried out within 48 h which is critical for the same-cycle blastocyst transfer, but also suitable for “freeze all” and “elective frozen embryo” strategies. The described integrated approach of non-invasive evaluation of embryonic DNA content of the culture media can potentially supplement existing pre-implantation genetic screening methods.

Keywords: next generation sequencing, in vitro fertilization, embryo assessment, non-invasive pre-implantation genetic testing

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Authors: Giorgi Sulashvili, Vladimer Kekenadze, Olga Khutsishvili, Bela Khotenashvili, Tsiuri Phkhakadze, Besarion Tsikhelashvili

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The article dealt with the South Caucasus is a complex economic policy, which consists of strands: The process of deepening economic integration in the South Caucasus region; deepening economic integration with the EU in the framework of "Neighbourhood policy with Europe" and in line with the Maastricht criteria; the development of bilateral trade and economic relations with many countries of the world community; the development of sufficient conditions for the integration of the South Caucasus region in the world to enter the market. According to the author, to determine the place of Georgia in the regional policy of the South Caucasus, it is necessary to consider two views about Georgia: The first is the view of Georgia, as a part of global economic and political processes and the second look at Georgia, as a country located in the geo-economic and geopolitical space of the South Caucasus. Such approaches reveal the place of Georgia in two dimensions; in the global and regional economies. In the countries of South Caucasus, the tourism has been developing fast and has a great social and economic importance. Tourism influences deeply on the social and economic growth of the regions of the country. Tourism development formulates thousand new jobs, fixes the positions of small and middle businesses, ensures the development of the education and culture of the population. In the countries of South Caucasus, the Tourist Industry can be specified as the intersectoral complex, which consists of travel transport and it’s technical service network, tourist enterprises which are specialized in various types, wide network services. Tourists have a chance to enjoy all of these services. At the transitional stage of shifting to the market economy, tourism is among the priorities in the development of the national economy of our country. It is true that the Georgian tourism faces a range of problems at present, but its recognition and the necessity for its development may be considered as a fact. Besides, we would underline that the revitalization of the Georgian tourism is not only the question of time. This area can bring a lot of benefits as to private firms, as to specific countries. It also has many negative effects were conducted fundamental research and studies to consider both, positive and negative impacts of tourism. In the future such decisions will be taken that will bring, the maximum benefit at minimum cost, in order for tourism to take its place in Georgia it is necessary to understand the role of the tourism sector in the economic structure.

Keywords: transitional stage, national economy, Georgian tourism, positive and negative impacts

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Authors: Syed Asif Hassan, Tabrej Khan

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Multiple sclerosis (MS) is a chronic demyelinating autoimmune disorder, of the central nervous system (CNS). In the present scenario, the current therapies either do not halt the progression of the disease or have side effects which limit the usage of current Disease Modifying Therapies (DMTs) for a longer period of time. Therefore, keeping the current treatment failure schema, we are focusing on screening novel analogues of the available DMTs that specifically bind and inhibit the Sphingosine1-phosphate receptor1 (S1PR1) thereby hindering the lymphocyte propagation toward CNS. The novel drug-like analogs molecule will decrease the frequency of relapses (recurrence of the symptoms associated with MS) with higher efficacy and lower toxicity to human system. In this study, an integrated approach involving ligand-based virtual screening protocol (Ultrafast Shape Recognition with CREDO Atom Types (USRCAT)) to identify the non-toxic drug like analogs of the approved DMTs were employed. The potency of the drug-like analog molecules to cross the Blood Brain Barrier (BBB) was estimated. Besides, molecular docking and simulation using Auto Dock Vina 1.1.2 and GOLD 3.01 were performed using the X-ray crystal structure of Mtb LprG protein to calculate the affinity and specificity of the analogs with the given LprG protein. The docking results were further confirmed by DSX (DrugScore eXtented), a robust program to evaluate the binding energy of ligands bound to the ligand binding domain of the Mtb LprG lipoprotein. The ligand, which has a higher hypothetical affinity, also has greater negative value. Further, the non-specific ligands were screened out using the structural filter proposed by Baell and Holloway. Based on the USRCAT, Lipinski’s values, toxicity and BBB analysis, the drug-like analogs of fingolimod and BG-12 showed that RTL and CHEMBL1771640, respectively are non-toxic and permeable to BBB. The successful docking and DSX analysis showed that RTL and CHEMBL1771640 could bind to the binding pocket of S1PR1 receptor protein of human with greater affinity than as compared to their parent compound (Fingolimod). In this study, we also found that all the drug-like analogs of the standard MS drugs passed the Bell and Holloway filter.

Keywords: antagonist, binding affinity, chemotherapeutics, drug-like, multiple sclerosis, S1PR1 receptor protein

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Authors: Ophir Nave

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In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

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Authors: Sawyer Spurry

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Problem: Palliative care providers at an academic medical center in Maryland stated medical intensive care unit (MICU) patients are often referred late in their hospital stay. The MICU has performed well below the hospital quality performance metric of 80% of patients who expire with expected outcomes should have received a palliative care consult within 48 hours of admission. Purpose: The purpose of this quality improvement (QI) project is to increase palliative care utilization in the MICU through the implementation of a Nurse-Driven PalliativeTriggerTool to prompt the need for specialty palliative care consult. Methods: MICU nursing staff and providers received education concerning the implications of underused palliative care services and the literature data supporting the use of nurse-driven palliative care tools as a means of increasing utilization of palliative care. A MICU population specific criteria of palliative triggers (Palliative Care Trigger Tool) was formulated by the QI implementation team, palliative care team, and patient care services department. Nursing staff were asked to assess patients daily for the presence of palliative triggers using the Palliative Care Trigger Tool and present findings during bedside rounds. MICU providers were asked to consult palliative medicinegiven the presence of palliative triggers; following interdisciplinary rounds. Rates of palliative consult, given the presence of triggers, were collected via electronic medical record e-data pull, de-identified, and recorded in the data collection tool. Preliminary Results: Over 140 MICU registered nurses were educated on the palliative trigger initiative along with 8 nurse practitioners, 4 intensivists, 2 pulmonary critical care fellows, and 2 palliative medicine physicians. Over 200 patients were admitted to the MICU and screened for palliative triggers during the 15-week implementation period. Primary outcomes showed an increase in palliative care consult rates to those patients presenting with triggers, a decreased mean time from admission to palliative consult, and increased recognition of unmet palliative care needs by MICU nurses and providers. Conclusions: Anticipatory findings of this QI project would suggest a positive correlation between utilizing palliative care trigger criteria and decreased time to palliative care consult. The direct outcomes of effective palliative care results in decreased length of stay, healthcare costs, and moral distress, as well as improved symptom management and quality of life (QOL).

Keywords: palliative care, nursing, quality improvement, trigger tool

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Authors: Sungeun Hyun, Sooin Lee, Gyewan Moon

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Work-Family Conflict has been an active research area for the past decades. Work-Family Conflict harms individuals and organizations, it is ultimately expected to bring the cost of losses to the company in the long run. WFC has mainly focused on effects of organizational effectiveness and job attitude such as Job Satisfaction, Organizational Commitment, and Turnover Intention variables. This study is different from consequence variable with previous research. For this purpose, we selected the positive job attitude 'Work Engagement' as a consequence of WFC. This research has its primary research purpose in identifying the negative effects of the Work-Family Conflict, and started out from the recognition of the problem that the research on the direct relationship on the influence of the WFC on Work Engagement is lacking. Based on the COR(Conservation of resource theory) and JD-R(Job Demand- Resource model), the empirical study model to examine the negative effects of WFC with Emotional Exhaustion as the link between WFC and Work Engagement was suggested and validated. Also, it was analyzed how much Positive Psychological Capital may buffer the negative effects arising from WFC within this relationship, and the Mediated Moderation model controlling the indirect effect influencing the Work Engagement by the Positive Psychological Capital mediated by the WFC and Emotional Exhaustion was verified. Data was collected by using questionnaires distributed to 500 employees engaged manufacturing, services, finance, IT industry, education services, and other sectors, of which 389 were used in the statistical analysis. The data are analyzed by statistical package, SPSS 21.0, SPSS macro and AMOS 21.0. The hierarchical regression analysis, SPSS PROCESS macro and Bootstrapping method for hypothesis testing were conducted. Results showed that all hypotheses are supported. First, WFC showed a negative effect on Work Engagement. Specifically, WIF appeared to be on more negative effects than FIW. Second, Emotional exhaustion found to mediate the relationship between WFC and Work Engagement. Third, Positive Psychological Capital showed to moderate the relationship between WFC and Emotional Exhaustion. Fourth, the effect of mediated moderation through the integration verification, Positive Psychological Capital demonstrated to buffer the relationship among WFC, Emotional Exhastion, and Work Engagement. Also, WIF showed a more negative effects than FIW through verification of all hypotheses. Finally, we discussed the theoretical and practical implications on research and management of the WFC, and proposed limitations and future research directions of research.

Keywords: emotional exhaustion, positive psychological capital, work engagement, work-family conflict

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Authors: Prajwal Eachempati, Laurent Muzellec, Ashish Kumar Jha

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We use Facebook as a case study to investigate the complex relationship between the firm’s public discourse (and actions) surrounding data privacy and the performance of a business model based on monetizing user’s data. We do so by looking at the evolution of public discourse over time (2004–2021) and relate topics to revenue and stock market evolution Drawing from archival sources like Zuckerberg We use LDA topic modelling algorithm to reveal 19 topics regrouped in 6 major themes. We first show how, by using persuasive and convincing language that promises better protection of consumer data usage, but also emphasizes greater user control over their own data, the privacy issue is being reframed as one of greater user control and responsibility. Second, we aim to understand and put a value on the extent to which privacy disclosures have a potential impact on the financial performance of social media firms. There we found significant relationship between the topics pertaining to privacy and social media/technology, sentiment score and stock market prices. Revenue is found to be impacted by topics pertaining to politics and new product and service innovations while number of active users is not impacted by the topics unless moderated by external control variables like Return on Assets and Brand Equity.

Keywords: public discourses, data protection, social media, privacy, topic modeling, business models, financial performance

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Bahman Ghorashi

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The immense awareness of the global climate change has compelled traditional fossil fuel companies to develop strategies to reduce their carbon footprint and simultaneously consider the production of various sources of clean energy in order to mitigate the environmental impact of their operations. Similarly, supply chain issues, the scarcity of certain raw materials, energy costs as well as market needs, and changing consumer expectations have forced the traditional chemical industry to reexamine their time-honored modes of operation. This study examines how such transformative change might occur through the applications of agile principles as well as industry 4.0 technologies. Clearly, such a transformation is complex, costly, and requires a total commitment on the part of the top leadership and the entire management structure. Factors that need to be considered include organizational speed of change, a restructuring that would lend itself toward collaboration and the selling of solutions to customers’ problems, rather than just products, integrating ‘along’ as well as ‘across’ value chains, mastering change and uncertainty as well as a recognition of the importance of concept-to-cash time, i.e., the velocity of introducing new products to market, and the leveraging of people and information. At the same time, parallel to implementing such major shifts in the ethos, and the fabric of the organization, the change leaders should remain mindful of the companies’ DNA while incorporating the necessary DNA defying shifts. Furthermore, such strategic maneuvers should inevitably incorporate the managing of the upstream and downstream operations, harnessing future opportunities, preparing and training the workforce, implementing faster decision making and quick adaptation to change, managing accelerated response times, as well as forming autonomous and cross-functional teams. Moreover, the leaders should establish the balance between high-value solutions versus high-margin products, fully implement digitization of operations and, when appropriate, incorporate the latest relevant technologies, such as: AI, IIoT, ML, and immersive technologies. This study presents a summary of the agile principles and the relevant technologies and draws lessons from some of the best practices that are already implemented within the chemical industry in order to establish a roadmap to agility. Finally, the critical role of educational institutions in preparing the future workforce for Industry 4.0 is addressed.

Keywords: agile principles, immersive technologies, industry 4.0, workforce preparation

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

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Authors: Xianwei Zheng, Yuan Yan Tang

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Classical window Fourier transform has been widely used in signal processing, image processing, machine learning and pattern recognition. The related Gabor transform is powerful enough to capture the texture information of any given dataset. Recently, in the emerging field of graph signal processing, researchers devoting themselves to develop a graph signal processing theory to handle the so-called graph signals. Among the new developing theory, windowed graph Fourier transform has been constructed to establish a time-frequency analysis framework of graph signals. The windowed graph Fourier transform is defined by using the translation and modulation operators of graph signals, following the similar calculations in classical windowed Fourier transform. Specifically, the translation and modulation operators of graph signals are defined by using the Laplacian eigenvectors as follows. For a given graph signal, its translation is defined by a similar manner as its definition in classical signal processing. Specifically, the translation operator can be defined by using the Fourier atoms; the graph signal translation is defined similarly by using the Laplacian eigenvectors. The modulation of the graph can also be established by using the Laplacian eigenvectors. The windowed graph Fourier transform based on these two operators has been applied to obtain time-frequency representations of graph signals. Fundamentally, the modulation operator is defined similarly to the classical modulation by multiplying a graph signal with the entries in each Fourier atom. However, a single Laplacian eigenvector entry cannot play a similar role as the Fourier atom. This definition ignored the relationship between the translation and modulation operators. In this paper, a new definition of the modulation operator is proposed and thus another time-frequency framework for graph signal is constructed. Specifically, the relationship between the translation and modulation operations can be established by the Fourier transform. Specifically, for any signal, the Fourier transform of its translation is the modulation of its Fourier transform. Thus, the modulation of any signal can be defined as the inverse Fourier transform of the translation of its Fourier transform. Therefore, similarly, the graph modulation of any graph signal can be defined as the inverse graph Fourier transform of the translation of its graph Fourier. The novel definition of the graph modulation operator established a relationship of the translation and modulation operations. The new modulation operation and the original translation operation are applied to construct a new framework of graph signal time-frequency analysis. Furthermore, a windowed graph Fourier frame theory is developed. Necessary and sufficient conditions for constructing windowed graph Fourier frames, tight frames and dual frames are presented in this paper. The novel graph signal time-frequency analysis framework is applied to signals defined on well-known graphs, e.g. Minnesota road graph and random graphs. Experimental results show that the novel framework captures new features of graph signals.

Keywords: graph signals, windowed graph Fourier transform, windowed graph Fourier frames, vertex frequency analysis

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Aroge Stephen Talabi

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Work is a term that appears to be very common in usage and occurrence the world over. The meanings attached to it and what it implies equally appears to be that common and somewhat similar in description by individuals and groups as derivatives of their contexts. Work is generally seen as the exertion of efforts and the application of knowledge and skills to achieve different purposes comprising of earning a living, making money, prestige, achievement, recognition, companionship and other satisfactions. The paper examined the general meanings of work from the perspectives of various religions. It situated these meanings by drawing on the sociological significance of work among the Yoruba. It established work as social control for a reorientation in peoples approach to work. The Yoruba people of the Western Nigeria share, to a great extent, in common conceptualization and application of work as they believe and understand that their individual and community existence and living are contingent on work participation. The contextual meaning and sociological significance of work as investigated in this paper show that the Yorubas concept of work is daily applied variously in both their material and non-material cultural undertakings to influence individual and group for effective participation in productive ventures for overall social well-being. The Yoruba use all forms of training method which could be adopted by adult educators as pathways to increase individual’s work participation and to improve productivity in work organizations.The paper found out that in the Yoruba socio cultural milieu, the meanings, conceptions and the importance attached to work are used as method of inculcating in members of society the spirit of commitment and hard-work and the advantages thereof. Yoruba contexts of work are geared towards enhancement of commitment, diligence and improved productivity on-the-job behaviour. The paper, therefore, submits that using the Yoruba’s conceptions of work could enhance commitment on the parts of all those engaged in production of goods and services. The paper also suggests that the Yoruba principle and perception and application of work could be used as one of the training techniques in industrial education, which is a major aspect of adult education programmes for inculcating ethics in the workplace. Thus, effort should be made to embrace the Yoruba conception and tenet of work by all stakeholders such as the workers, group (Union), managers and the society at large. Such principles and tenet of work should be included in industrial education curriculum.

Keywords: work, contextual meaning, sociological significance, Yoruba-people, social milieu, productivity

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Authors: T. Asefi, J. Faiz, M. A. Khan

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This paper introduces dual rotor axial flux machines with surface mounted and spoke type ferrite permanent magnets with concentrated windings; they are introduced as alternatives to a generator with surface mounted Nd-Fe-B magnets. The output power, voltage, speed and air gap clearance for all the generators are identical. The machine designs are optimized for minimum mass using a population-based algorithm, assuming the same efficiency as the Nd-Fe-B machine. A finite element analysis (FEA) is applied to predict the performance, emf, developed torque, cogging torque, no load losses, leakage flux and efficiency of both ferrite generators and that of the Nd-Fe-B generator. To minimize cogging torque, different rotor pole topologies and different pole arc to pole pitch ratios are investigated by means of 3D FEA. It was found that the surface mounted ferrite generator topology is unable to develop the nominal electromagnetic torque, and has higher torque ripple and is heavier than the spoke type machine. Furthermore, it was shown that the spoke type ferrite permanent magnet generator has favorable performance and could be an alternative to rare-earth permanent magnet generators, particularly in wind energy applications. Finally, the analytical and numerical results are verified using experimental results.

Keywords: axial flux, permanent magnet generator, dual rotor, ferrite permanent magnet generator, finite element analysis, wind turbines, cogging torque, population-based algorithms

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Authors: Merve Denizci Nazligul

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Dancers seem to have much higher risk levels for the development of eating disorders, compared to non-dancing counterparts. In a remarkably competitive nature of dance environment, perfectionism and emotion regulation difficulties become inevitable risk factors. Moreover, early maladaptive schemas are associated with various eating disorders. In the current study, it was aimed to investigate the mediating role of difficulties with emotion regulation on the relationship between perfectionism and disordered eating behaviors, as well as on the relationship between early maladaptive schemas and disordered eating behaviors. A total of 70 volunteer dancers (n = 47 women, n = 23 men) were recruited in the study (M age = 25.91, SD = 8.9, range 19–63) from the university teams or private clubs in Turkey. The sample included various types of dancers (n = 26 ballets or ballerinas, n =32 Latin, n = 10 tango, n = 2 hiphop). The mean dancing hour per week was 11.09 (SD = 7.09) within a range of 1-30 hours. The participants filled a questionnaire set including demographic information form, Dutch Eating Behavior Questionnaire, Multidimensional Perfectionism Scale, three subscales (Emotional Inhibition, Unrelenting Standards-Hypercriticalness, Approval Seeking-Recognition Seeking) from Young Schema Questionnaire-Short Form-3 and Difficulties in Emotion Regulation Scale. The mediation hypotheses were tested using the PROCESS macro in SPSS. The findings revealed that emotion regulation difficulties significantly mediated the relationship between three distinct subtypes of perfectionism and emotional eating. The results of the Sobel test suggested that there were significant indirect effects of self-oriented perfectionism (b = .06, 95% CI = .0084, .1739), other-oriented perfectionism (b = .15, 95% CI = .0136, .4185), and socially prescribed perfectionism (b = .09, 95% CI = .0104, .2344) on emotional eating through difficulties with emotion regulation. Moreover, emotion regulation difficulties significantly mediated the relationship between emotional inhibition and emotional eating (F(1,68) = 4.67, R2 = .06, p < .05). These results seem to provide some evidence that perfectionism might become a risk factor for disordered eating behaviors when dancers are not able to regulate their emotions. Further, gaining an understanding of how inhibition of emotions leads to inverse effects on eating behavior may be important to develop intervention strategies to manage their disordered eating patterns in risk groups. The present study may also support the importance of using unified protocols for transdiagnostic approaches which focus on identifying, accepting, prompting to express maladaptive emotions and appraisals.

Keywords: dancers, disordered eating, emotion regulation difficulties, perfectionism

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Mengestie Mulugeta Belay, Serebe Abay Gebrie, Biruk Lambbiso Wamisho, Amare Worku

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Background: Low back pain (LBP) related to nursing profession, is a very common public health problem throughout the world. Various risk factors have been implicated in the etiology and LBP is assumed to be of multi-factorial origin as individual, work-related and psychosocial factors can contribute to its development. Objectives: To determine the prevalence and to identify risk factors of LBP among nurses working in Addis Ababa City Public Hospitals, Ethiopia, in the year 2015. Settings: Addis Ababa University, Black-Lion (‘Tikur Anbessa’) Hospital-BLH, is the country’s highest tertiary level referral and teaching Hospital. The three departments in connection with this study: Radiology, Pathology and Orthopedics, run undergraduate and residency programs and receive referred patients from all over the country. Methods: A cross-sectional study with internal comparison was conducted throughout the period October-December, 2015. Sample was chosen by simple random sampling technique by taken the lists of nurses from human resource departments as a sampling frame. A well-structured, pre-tested and self-administered questionnaire was used to collect quantifiable information. The questionnaire included socio-demographic, back pain features, consequences of back pain, work-related and psychosocial factors. The collected data was entered into EpiInfo version 3.5.4 and was analyzed by SPSS. A probability level of 0.05 or less and 95% confidence level was used to indicate statistical significance. Ethical clearance was obtained from all respected administrative bodies, Hospitals and study participants. Results: The study included 395 nurses and gave a response rate of 91.9%. The mean age was 30.6 (±8.4) years. Majority of the respondents were female (285, 72.2%). Nearly half of the participants (n=181, 45.8% (95% CI (40.8%- 50.6%))) were complained low back pain. There was statistical significant association between low back pain and working shift, physical activities at work; sleep disturbance and felt little pleasure by doing things. Conclusion: A high prevalence of low back pain was found among nurses working in Addis Ababa Public Hospitals. Recognition and preventive measures like providing resting periods should be taken to reduce the risk of low back pain in nurses working in Public hospitals.

Keywords: low back pain, risk factors, nurses, public hospitals

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Authors: Amelia Faotusia

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The blue economy concept was coined by Pacific nations in recognition of the importance of sustainably managing their extensive marine territories. This is especially important for major ocean-based economic sectors of Pacific economies, such as coastal tourism. There is an absence of research, however, on the key ways in which the blue economy concept has emerged in discourse and public policy in Pacific countries, as well as how it articulates with coastal tourism. This research helps to fill such a gap with a specific focus on Tonga through the application of a post-positivist research approach to conduct a desktop study of relevant national documents and qualitative interviews with relevant government staff, civil society organizations, and tourism operators. The findings of the research reflect the importance of institutional integration and partnerships for a successful blue economy transition and are presented in the form of two case studies corresponding to two sub-sectors of Tonga’s coastal tourism sector: (i) the whale-watching and swimming industry, and (ii) beach resorts and restaurants. A thematic analysis applied to the interview data of both cases then enabled the identification of key areas and issues for socio-economic policy intervention and recommendations in support of blue economy transitions in Tonga’s coastal tourism sector. Examples of the relevant areas and issues that emerged included the importance of foreign direct investment, local market access, community-based special management areas, as well as the need to address the anthropogenic impacts of tropical cyclones, whale tourism, plastic litter on coastal assets, and ecosystems. Policy and practical interventions in support of addressing such issues include a proposed restructuring of the whale-watching and swimming licensing system; integration of climate resilience, adaptation, and capacity building as priorities of local blue economy interventions; as well as strengthening of the economic sustainability dimension of blue economy policies. Finally, this research also revealed the need for further specificity and research on the influence and value of local Tongan culture and traditional knowledge, particularly within existing customary marine tenure systems, on Tonga’s national and sectoral blue economy policies and transitions.

Keywords: blue economy, coastal tourism, integrated ocean management, ecosystem resilience

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Authors: Muhammad Abubakar Alhassan, Diane Pennington

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Social networking sites have become a space for people to discuss public health issues such as non-suicidal self-injury (NSSI). There are thousands of tweets containing self-harm and self-injury hashtags on Twitter. It is difficult to distinguish between different users who participate in self-injury discussions on Twitter and how their opinions change over time. Also, it is challenging to understand the topics surrounding NSSI discussions on Twitter. We retrieved tweets using #selfham and #selfinjury hashtags and investigated those from the United kingdom. We applied inductive coding and grouped tweeters into different categories. This study used the Latent Dirichlet Allocation (LDA) algorithm to infer the optimum number of topics that describes our corpus. Our findings revealed that many of those participating in NSSI discussions are non-professional users as opposed to medical experts and academics. Support organisations, medical teams, and academics were campaigning positively on rais-ing self-injury awareness and recovery. Using LDAvis visualisation technique, we selected the top 20 most relevant terms from each topic and interpreted the topics as; children and youth well-being, self-harm misjudgement, mental health awareness, school and mental health support and, suicide and mental-health issues. More than 50% of these topics were discussed in England compared to Scotland, Wales, Ireland and Northern Ireland. Our findings highlight the advantages of using the Twitter social network in tackling the problem of self-injury through awareness. There is a need to study the potential risks associated with the use of social networks among self-injurers.

Keywords: self-harm, non-suicidal self-injury, Twitter, social networks

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Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

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Authors: Hassan M. H. Mustafa

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This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

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Authors: Belal Mohamadi Kalesar, Raouf Hasanpour

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Proper placement of Distributed Generation (DG) units such as wind turbine generators in distribution system are still very challenging issue for obtaining their maximum potential benefits because inappropriate placement may increase the system losses. This paper proposes Particle Swarm Optimization (PSO) technique for optimal placement of wind based DG (WDG) in the primary distribution system to reduce energy losses and voltage profile improvement with four different wind levels modeling in year duration. Also, wind turbine is modeled as a DFIG that will be operated at unity power factor and only one wind turbine tower will be considered to install at each bus of network. Finally, proposed method will be implemented on widely used 69 bus power distribution system in MATLAB software environment under four scenario (without, one, two and three WDG units) and for capability test of implemented program it is supposed that all buses of standard system can be candidate for WDG installing (large search space), though this program can consider predetermined number of candidate location in WDG placement to model financial limitation of project. Obtained results illustrate that wind speed increasing in some months will increase output power generated but this can increase / decrease power loss in some wind level, also results show that it is required about 3MW WDG capacity to install in different buses but when this is distributed in overall network (more number of WDG) it can cause better solution from point of view of power loss and voltage profile.

Keywords: wind turbine, DG placement, wind levels effect, PSO algorithm

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Authors: Salah Abdul Hameed Saleh, Ghada Hasan

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The aim of this work is to produce an empirical model for the determination of particulate matter (PM10) concentration in the atmosphere using visible bands of Landsat 8 OLI satellite image over Kirkuk city- IRAQ. The suggested algorithm is established on the aerosol optical reflectance model. The reflectance model is a function of the optical properties of the atmosphere, which can be related to its concentrations. The concentration of PM10 measurements was collected using Particle Mass Profiler and Counter in a Single Handheld Unit (Aerocet 531) meter simultaneously by the Landsat 8 OLI satellite image date. The PM10 measurement locations were defined by a handheld global positioning system (GPS). The obtained reflectance values for visible bands (Coastal aerosol, Blue, Green and blue bands) of landsat 8 OLI image were correlated with in-suite measured PM10. The feasibility of the proposed algorithms was investigated based on the correlation coefficient (R) and root-mean-square error (RMSE) compared with the PM10 ground measurement data. A choice of our proposed multispectral model was founded on the highest value correlation coefficient (R) and lowest value of the root mean square error (RMSE) with PM10 ground data. The outcomes of this research showed that visible bands of Landsat 8 OLI were capable of calculating PM10 concentration with an acceptable level of accuracy.

Keywords: air pollution, PM10 concentration, Lansat8 OLI image, reflectance, multispectral algorithms, Kirkuk area

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Authors: Somya Ranjan Patro, Abhigna Bhatt, Arnab Banerjee

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Inertial amplifier has recently gained increasing attention as a new mechanism for vibration control of structures. Currently, theoretical investigations are undertaken by researchers to reveal its fundamentals and to understand its underline principles in altering the structural response of structures against dynamic loadings. This paper investigates experimental and analytical studies on the dynamic characteristics of hybrid beam inertial amplifier (HBIA). The analytical formulation of the HBIA has been derived by implementing the spectral element method and rigid body dynamics. This formulation gives the relation between dynamic force and the response of the structure in the frequency domain. Further, for validation of the proposed HBIA, the experiments have been performed. The experimental setup consists of a 3D printed HBIA of polylactic acid (PLA) material screwed at the base plate of the shaker system. Two numbers of accelerometers are used to study the response, one at the base plate of the shaker second one placed at the top of the inertial amplifier. A force transducer is also placed in between the base plate and the inertial amplifier to calculate the total amount of load transferred from the base plate to the inertial amplifier. The obtained time domain response from the accelerometers have been converted into the frequency domain using the Fast Fourier Transform (FFT) algorithm. The experimental transmittance values are successfully validated with the analytical results, providing us essential confidence in our proposed methodology.

Keywords: inertial amplifier, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers

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Authors: Mehves Isiklar Ekici, Ceyda Tuna Kirsaclioglu, Zarife Kuloglu, Aydan Kansu

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Malnutrition is an important cause of morbidity and mortality as it accounts for 45% of child deaths under the age of 5 worldwide. Therefore, early recognition and effective treatment of failure to thrive and malnutrition are important. In this study, it was aimed to retrospectively evaluate the nutritional support treatment approaches (nutrition education and diet enrichment / use of enteral nutrition products) applied in children followed up with growth failure without underlying organic causes, and to compare the efficacy of nutritional support treatments. In this study, children aged 1 month to 18 years diagnosed with growth failure who were followed up for at least 12 months between January 2011 and February 2020, were included. Anthropometric measurements at baseline and during follow-up, type of nutritional support therapy and treatment compliance were evaluated based on the retrospective records. 119 children (median age:3.2, 69 girls) were included in the study. Nutrition education and dietary enrichment were provided to 28% of the patients (Group 1). In addition to dietary education and recommendations, enteral nutrition supplements was given in 78% of them (Group 2). Compliance to the treatment rates of the patients in Group 1 and Group 2 were not significantly different at both 6th and 12th month controls. At the end of the follow up children who comply with the treatment in Group 1 had significant increase in weight for age z scores (-1.74 vs 0.05, respectively, p=0.019) and body mass index z scores (-1.47 vs -0.53, respectively, p=0.034) compared with baseline measurements. Similar to Group 1, in Group 2 children with treatment compliance, had a significant increase in weight for age z scores (-2.24 vs. -0.54, respectively, p=0.00) and body mass index z scores (-2.27 vs. -1.06, respectively, p=0.00) compared with baseline measurements. The rate of patients with severe malnutrition decreased from 15% to 12%, for moderate malnutrition decreased from 54% to 33%. Moreover, it was observed that this decrease in the rate of patients with both severe and moderate malnutrition was more prominent in patients under 3 years of age. Although there was a significant increase in anthropometric measurements with treatment in both groups, there was no significant difference in between two groups terms of change in anthropometric measurements (p>0.05), therefore effectiveness. Failure to thrive and malnutrition in infancy and childhood cause health problems that can affect adult life. To conclude, nutritional education - dietary enrichment. recommendations and use of enteral nutrition supplements were both proven beneficial in this study. Researchers are willing to underline that the most important part of the treatment is to include the family to the process to ensure the treatment compliance.

Keywords: enteral nutrition supplements, failure to thrive, malnutrition, nutritional education

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Authors: Disha Batra

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The Industrial Revolution 4.0 is quite different, and a paradigm shift is underway in the media industry. With the advent of automated journalism and social media platforms, newspaper organizations have changed the way news was gathered and reported. The emergence of the fourth industrial revolution in the early 21st century has made the newspapers to adapt the changing technologies to remain relevant. This paper investigates the content of Indian business-papers in the era of the fourth industrial revolution and how these organizations have emerged in the time of convergence. The study is the content analyses of the top three Indian business dailies as per IRS (Indian Readership Survey) 2017 over a decade. The parametric analysis of the different parameters (source of information, use of illustrations, advertisements, layout, and framing, etc.) have been done in order to come across with the distinct adaptations and modifications by these dailies. The paper significantly dwells upon the thematic analysis of these newspapers in order to explore and find out the coverage given to various sub-themes of EBF (economic, business, and financial) journalism. Further, this study reveals the effect of high-speed algorithm-based trading, the aftermath of the fourth industrial revolution on the creative and investigative aspect of delivering financial stories by these respective newspapers. The study indicates a change heading towards an ongoing paradigm shift in the business newspaper industry with an adequate change in the source of information gathering along with the subtle increase in the coverage of financial news stories over the time.

Keywords: business-papers, business news, financial news, industrial revolution 4.0.

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Authors: Hossein Ghadimi, Alireza Alizadeh, Oveis Abedinia, Noradin Ghadimi

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This paper presents an enhanced Honey Bee Mating Optimization (HBMO) to solve the optimal design of multi machine power system stabilizer (PSSs) parameters, which is called the Interactive Honey Bee Mating Optimization (IHBMO). Power System Stabilizers (PSSs) are now routinely used in the industry to damp out power system oscillations. The design problem of the proposed controller is formulated as an optimization problem and IHBMO algorithm is employed to search for optimal controller parameters. The proposed method is applied to multi-machine power system (MPS). The method suggested in this paper can be used for designing robust power system stabilizers for guaranteeing the required closed loop performance over a prespecified range of operating and system conditions. The simplicity in design and implementation of the proposed stabilizers makes them better suited for practical applications in real plants. The non-linear simulation results are presented under wide range of operating conditions in comparison with the PSO and CPSS base tuned stabilizer one through FD and ITAE performance indices. The results evaluation shows that the proposed control strategy achieves good robust performance for a wide range of system parameters and load changes in the presence of system nonlinearities and is superior to the other controllers.

Keywords: power system stabilizer, IHBMO, multimachine, nonlinearities

Procedia PDF Downloads 481