Search results for: decision support technique

Authors: John Tarus, Zhendong Niu, Bakhti Khadidja

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In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.

Keywords: collaborative filtering, e-learning, ontology, recommender system

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Qinglei Liu, Ali Charkhesht, Tiva Sharifi, Ashkan Bahadoran

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Graphene sheets are promising nanoscale building blocks as a support material for the dispersion of nanoparticles. In this work, a solvothermal method employed to directly grow Co1-xZnxFe2O4 ferrite nanospheres on graphene oxide support that is subsequently reduced to graphene. The samples morphology, structure and crystallography were investigated using field-emission scanning electron microscopy (FE-SEM) and powder X-ray diffraction (XRD). The influences of the Zn2+ content on photocatalytic activity, electrical conductivity and magnetic property of the samples are also investigated. The results showed that Co1-x Znx Fe2 O4 nanoparticles are dispersed on graphene sheets and obtained nanocomposites are soft magnetic materials. In addition the samples showed excellent photocatalytic activity under visible light irradiation.

Keywords: reduced graphene oxide, ferrite, magnetic nanocomposite, photocatalytic activity, solvothermal method

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Authors: Deboraj Muchahary, Amlan Deep Borah Abir J. Mondal, Alak Majumder

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A discrete cosine transform (DCT) is described and a technique to compute it using fast Fourier transform (FFT) is developed. In this work, DCT of a finite length sequence is obtained by incorporating CORDIC methodology in radix-2 FFT algorithm. The proposed methodology is simple to comprehend and maintains a regular structure, thereby reducing computational complexity. DCTs are used extensively in the area of digital processing for the purpose of pattern recognition. So the efficient computation of DCT maintaining a transparent design flow is highly solicited.

Keywords: DCT, DFT, CORDIC, FFT

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Authors: Sithandazile Masuku

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Introduction: Public health approaches to offender mental health are driven by international policies and frameworks in response to the disproportionately large representation of people with mental health problems within the offender pathway compared to the general population. Public health service innovations include mental health courts in the US, restorative models in Singapore and, liaison and diversion services in Australia, the UK, and some other European countries. Mental health nurses are at the forefront of offender health service innovations. In the U.K. context, police custody has been identified as an early point within the offender pathway where nurses can improve outcomes by offering assessments and share information with criminal justice partners. This scope of nursing practice has introduced challenges related to skills and support required for nurses working at the interface of health and the criminal justice system. Parallel literature exploring experiences of nurses working in forensic settings suggests the presence of compassion fatigue, burnout and vicarious trauma that may impede risk harm to the nurses in these settings. Published research explores mainly service-level outcomes including monitoring of figures indicative of a reduction in offending behavior. There is minimal research exploring the experiences of liaison and diversion nurses who are situated away from a supportive clinical environment and engaged in complex autonomous decision-making. Aim: This paper will share qualitative findings (in progress) from a PhD study that aims to explore the experiences of liaison and diversion nurses in one service in the U.K. Methodology: This is a qualitative interview study conducted using an Interpretative Phenomenological Analysis to gain an in-depth analysis of lived experiences. Methods: A purposive sampling technique was used to recruit n=8 mental health nurses registered with the UK professional body, Nursing and Midwifery Council, from one UK Liaison and Diversion service. All participants were interviewed online via video call using semi-structured interview topic guide. Data were recorded and transcribed verbatim. Data were analysed using the seven steps of the Interpretative Phenomenological Analysis data analysis method. Emerging Findings Analysis to date has identified pertinent themes: • Difficulties of meaning-making for nurses because of the complexity of their boundary spanning role. • Emotional burden experienced in a highly emotive and fast-changing environment. • Stress and difficulties with role identity impacting on individual nurses’ ability to be resilient. • Challenges to wellbeing related to a sense of isolation when making complex decisions. Conclusion Emerging findings have highlighted the lived experiences of nurses working in liaison and diversion as challenging. The nature of the custody environment has an impact on role identity and decision making. Nurses left feeling isolated and unsupported are less resilient and may go on to experience compassion fatigue. The findings from this study thus far point to a need to connect nurses working in these boundary spanning roles with a supportive infrastructure where the complexity of their role is acknowledged, and they can be connected with a health agenda. In doing this, the nurses would be protected from harm and the likelihood of sustained positive outcomes for service users is optimised.

Keywords: liaison and diversion, nurse experiences, offender health, staff wellbeing

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Authors: J. Niyitegeka, G. Nshimirimana, A. Silverstein, J. Odhiambo, Y. Lin, T. Nkurunziza, R. Riviello, S. Rulisa, P. Banguti, H. Magge, M. Macharia, J. P. Dushime, R. Habimana, B. Hedt-Gauthier

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In low-resource settings, women needing an emergency cesarean section experiences various delays in both reaching and receiving care that is often linked to poor neonatal outcomes. In this study, we quantified different measures of delays and assessed the association between these delays and neonatal outcomes at three rural district hospitals in Rwanda. This retrospective study included 441 neonates and their mothers who underwent emergency cesarean sections in 2015 at Butaro, Kirehe and Rwinkwavu District Hospitals. Four possible delays were measured: Time from start of labor to district hospital admission, travel time from a health center to the district hospital, time from admission to surgical incision, and time from the decision for the emergency cesarean section to surgical incision. Neonatal outcomes were categorized as unfavorable (APGAR < 7 or death) and favorable (APGAR ≥ 7). We assessed the relationship between each type of delay and neonatal outcomes using multivariate logistic regression. In our study, 38.7% (108 out of 279) of neonates’ mothers labored for 12 to 24 hours before hospital admission and 44.7% (159 of 356) of mothers were transferred from health centers that required 30 to 60 minutes of travel time to reach the district hospital. 48.1% (178 of 370) of caesarean sections started within five hours after admission and 85.2% (288 of 338) started more than thirty minutes after the decision for the emergency cesarean section was made. Neonatal outcomes were significantly worse among mothers with more than 90 minutes of travel time from the health center to the district hospital compared to health centers attached to the hospital (OR = 5.12, p = 0.02). Neonatal outcomes were also significantly different depending on decision to incision intervals; neonates with cesarean deliveries starting more than thirty minutes after decision had better outcomes than those started immediately (OR = 0.32, p = 0.04). Interventions that decrease barriers to access to maternal health care services can improve neonatal outcome after emergency cesarean section. Triaging could explain the inverse relationship between time from decision to incision and neonatal outcome; this must be studied more in the future.

Keywords: Africa, emergency obstetric care, rural health delivery, maternal and child health

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Authors: Gertrude Nkechi Okenwa

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Higher institutions, especially the universities that are saddled with the responsibilities of teaching, learning, research, publications and social services for the production of graduates that are worthy in learning and character, and the creation of up-to-date knowledge and innovations for the total socio-economic and even political development of a given nation. Therefore, the purpose of the study was to identify the teaching, learning techniques used in the Enugu State University of Science and Technology to ensure or ascertain students’ perception on these techniques. To guide the study, survey research method was used. The population for the study was made up of second and final year students which summed up to one hundred and twenty-six students in the faculty of education. Stratified random sampling technique was adopted. A sample size of sixty (60) students was drawn for the study. The instrument used for data collection was questionnaire. To analyze the data, mean and standard deviation were used to answers the research questions. The findings revealed that direct instruction and construction techniques are used in the university. On the whole, it was observed that the students perceived constructivist techniques to be more useful and effective than direct instruction technique. Based on the findings recommendations were made to include diversification of teaching techniques among others.

Keywords: Strategies, Teaching and Learning, Constructive Technique, Direct Instructional Technique

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Authors: Ariane Plaisance, Holly O. Witteman, Patrick Michel Archambault

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Upon admission to an intensive care unit (ICU), all patients should discuss their wishes concerning life-sustaining interventions (e.g., cardiopulmonary resuscitation (CPR)). Without such discussions, interventions that prolong life at the cost of decreasing its quality may be used without appropriate guidance from patients. We employed user-centered design to adapt an existing decision aid (DA) about CPR to create a novel wiki-based DA adapted to the context of a single ICU and tailored to individual patient’s risk factors. During Phase 1, we conducted three weeks of ethnography of the decision-making context in our ICU to identify clinician and patient needs for a decision aid. During this time, we observed five dyads of intensivists and patients discussing their wishes concerning life-sustaining interventions. We also conducted semi-structured interviews with the attending intensivists in this ICU. During Phase 2, we conducted three rounds of rapid prototyping involving 15 patients and 11 other allied health professionals. We recorded discussions between intensivists and patients and used a standardized observation grid to collect patients’ comments and sociodemographic data. We applied content analysis to field notes, verbatim transcripts and the completed observation grids. Each round of observations and rapid prototyping iteratively informed the design of the next prototype. We also used the programming architecture of a wiki platform to embed the GO-FAR prediction rule programming code that we linked to a risk graphics software to better illustrate outcome risks calculated. During Phase I, we identified the need to add a section in our DA concerning invasive mechanical ventilation in addition to CPR because both life-sustaining interventions were often discussed together by physicians. During Phase II, we produced a context-adapted decision aid about CPR and mechanical ventilation that includes a values clarification section, questions about the patient’s functional autonomy prior to admission to the ICU and the functional decline that they would judge acceptable upon hospital discharge, risks and benefits of CPR and invasive mechanical ventilation, population-level statistics about CPR, a synthesis section to help patients come to a final decision and an online calculator based on the GO-FAR prediction rule. Even though the three rounds of rapid prototyping led to simplifying the information in our DA, 60% (n= 3/5) of the patients involved in the last cycle still did not understand the purpose of the DA. We also identified gaps in the discussion and documentation of patients’ preferences concerning life-sustaining interventions (e.g.,. CPR, invasive mechanical ventilation). The final version of our DA and our online wiki-based GO-FAR risk calculator using the IconArray.com risk graphics software are available online at www.wikidecision.org and are ready to be adapted to other contexts. Our results inform producers of decision aids on the use of wikis and user-centered design to develop DAs that are better adapted to users’ needs. Further work is needed on the creation of a video version of our DA. Physicians will also need the training to use our DA and to develop shared decision-making skills about goals of care.

Keywords: ethnography, intensive care units, life-sustaining therapies, user-centered design

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Authors: Marianna De Almeida

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Greek secondary education is a highly selective system with regard to the access of students to Greek universities. Since access from elementary to lower secondary education and afterward to upper secondary education is rather liberal and almost free of selective mechanisms, the basic selection process comes after graduating from upper secondary school into play when students go through a highly selective process for university entry. This structure is responsible for the experience of extreme stress on the part of the candidates during a period of at least two years before the entrance examination leading to a radical change in students' everyday life routines. Instead of the school being an important agent for academic and psychological support, it seems that other agents, such as the informal private preparatory school and the student's families, take on the supportive role.

Keywords: stress, entrance examinations, family support, secondary education

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

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Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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Authors: Serdal Akyüz, Halit Turan, Mehmet Öztürk

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The future security environment will have new battlefield and enemies. The boundaries of battlefield and the identity of enemies cannot be noticed easily. The politicians may not want to lose their soldiers in very risky operations. This approach will pave the way for smart machines like war robots and new drones. These machines will have the decision-making ability and act simultaneously. This ability can change the military targeting process. Military targeting process (MTP) benefits from a wide scope of lethal and non-lethal weapons to reach an intended end-state. This process is now managed by people but in the future smart machines can do it by themselves. At first sight, this development seems useful for humanity owing to decrease the casualties in war. Using robots -which can decide, detect, deliver and asses without human support- for homeland security and against terrorist has very crucial risks and threats. Besides, it can decrease the havoc but also increase the collateral damages. This paper examines the current use of smart war machines, military targeting process and presents a new approach to MTP from lethal autonomy concept's point of view.

Keywords: the autonomous weapon systems, the lethal autonomy, military targeting process (MTP)

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Authors: K.L. Chiu, Johnny K. W. Ho, M. H. Chan, S. H. Cheung, K. H. Chan, S.K. So

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Thermal diffusivity is an important quantity in heat conduction. It measures the rate of heat transfer from the hot side to the cold side of a material. In solid-state materials, thermal diffusivity reveals information related to morphologies and solid quality, as thermal diffusivity can be affected by microstructures. However, thermal diffusivity studies on organic semiconductors are very limited. In this study, scanning photothermal deflection (SPD) technique is used to study the thermal diffusivities of different classes of semiconducting polymers. The reliability of the technique was confirmed by crossing-checking our SPD derived experimental values of different reference materials with their known diffusivities from the literature. To show that thermal diffusivity determination is a potential tool for revealing microscopic properties of organic photovoltaic semiconductors, SPD measurements were applied to various organic semiconducting films with different crystallinities. It is observed that organic photovoltaic semiconductors possess low thermal diffusivity, with values in the range of 0.3mm²/s to 1mm²/s. It is also discovered that polymeric photovoltaic semiconductors with greater molecular planarity, stronger stacking and higher crystallinity would possess greater thermal diffusivities. Correlations between thermal, charge transport properties will be discussed.

Keywords: polymer crystallinity, photovoltaic organic semiconductors, photothermal deflection technique, thermal diffusion

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Authors: Jeon Chi-Ho, Lee Jae-Bin, Shim Chang-Su

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National bridge inventory in Korea shows that the number of old prestressed concrete (PSC) bridgeover 30 years of service life is rapidly increasing. Recently tendon corrosion is one of the most critical issues in the maintenance of PSC bridges. In this paper, mechanical properties of corroded strands, which were removed from old bridges, were evaluated using tensile test. In the result, the equations to express the mechanical behavior of corroded strand were derived and compared to existing equation. For the decision of tendon replacement, it is necessary to evaluate the effect of corrosion level on strength and ductility of the structure. Considerations on analysis of PSC girders were introduced, and decision making on tendon replacement was also proposed.

Keywords: prestressed concrete bridge, tendon, corrosion, strength, ductility

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Authors: Markus Pajones, Theresa Steiner, Matthias Neubauer

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Selecting a logistics location is vital for logistics providers, food retailing and other trading companies since the selection poses an essential factor for economic success. Therefore various location search methods like cost-benefit analysis and others are well known and under usage. The development of a logistics location can be related to considerable negative effects for the eco system such as sealing the surface, wrecking of biodiversity or CO2 and noise emissions generated by freight and commuting traffic. The increasing importance of sustainability demands for taking an informed decision when selecting a logistics location for the future. Sustainability considers economic, ecologic and social aspects which should be equally integrated in the process of location search. Objectives of this paper are to define various methods which support the selection of sustainable logistics locations and to generate knowledge about the suitability, assets and limitations of the methods within the selection process. This paper investigates the role of economical, ecological and social aspects when searching for new logistics locations. Thereby, related work targeted towards location search is analyzed with respect to encoded sustainability aspects. In addition, this research aims to gain knowledge on how to include aspects of sustainability and take an informed decision when searching for a logistics location. As a result, a decomposition of the various location search methods in there components leads to a comparative analysis in form of a matrix. The comparison within a matrix enables a transparent overview about the mentioned assets and limitations of the methods and their suitability for selecting sustainable logistics locations. A further result is to generate knowledge on how to combine the separate methods to a new method for a more efficient selection of logistics locations in the context of sustainability. Future work will especially investigate the above mentioned combination of various location search methods. The objective is to develop an innovative instrument, which supports the search for logistics locations with a focus on a balanced sustainability (economy, ecology, social). Because of an ideal selection of logistics locations, induced traffic should be reduced and a mode shift to rail and public transport should be facilitated.

Keywords: commuting traffic, freight traffic, logistics location search, location search method

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Authors: J. Mano Ranjini

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Each and every child is special, born with a unique talent to explore this world. The word Dyslexia is derived from the Greek language in which “dys” meaning poor or inadequate and “lexis” meaning words or language. Dyslexia describes about a different kind of mind, which is often gifted and productive, that learns the concept differently. The main aim of the study is to bring the positive outcome of the reading level by examining the effectiveness of Visual Auditory Kinesthetic Tactile technique on Reading Level among Dyslexic Children at Helikx Open School and Learning Centre. A Quasi experimental one group pretest post test design was adopted for this study. The Reading Level was assessed by using the Schonell Graded Word Reading Test. Thirty subjects were drawn by using purposive sampling technique and the intervention Visual Auditory Kinesthetic Tactile technique was implemented to the Dyslexic Children for 30 consecutive days followed by the post Reading Level assessment revealed the improvement in the mean score value of reading level by 12%. Multi-sensory (VAKT) teaching uses all learning pathways in the brain (visual, auditory, kinesthetic-tactile) in order to enhance memory and learning and the ability in uplifting emotional, physical and societal dimensions. VAKT is an effective method to improve the reading skill of the Dyslexic Children that ensures the enormous significance of learning thereby influencing the wholesome of the child’s life.

Keywords: visual auditory kinesthetic tactile technique, reading level, dyslexic children, Helikx Open School

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Authors: Logan Carmichael

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As the world’s governments seek to increasingly digitize their service provisions, there exists a subsequent and fully valid concern about the security underpinning these digital governance provisions. Estonia, a small and innovative Baltic nation, has been refining both its digital governance structure and cybersecurity mechanisms for over three decades and has been praised as global ‘best practice’ in both fields. However, the security of the Estonian digital governance system has been ever-evolving and significantly shaped by cybersecurity crises. This paper examines said crises – 2007 cyberattacks on Estonian government, banks, and news media; the 2017 e-ID crisis; the ongoing COVID-19 pandemic; and the 2022 Russian invasion of Ukraine – and how governance decision-making following these crises has shaped the cybersecurity of the digital governance structure in Estonia. This paper employs a blended constructivist and historical institutionalist theoretical approach as a useful means to view governance and decision-making in the wake of cybersecurity incidents affecting the Estonian digital governance structure. Together, these theoretical groundings frame the topics of cybersecurity and digital governance in an Estonian context through a lens of ideation and experience, as well as institutional path dependencies over time and cybersecurity crises as critical junctures to study. Furthermore, this paper takes a qualitative approach, employing discourse analysis, policy analysis, and elite interviewing of Estonian officials involved in digital governance and cybersecurity in order to glean nuanced perspectives into the processes that followed these four crises. Ultimately, the results of this paper will offer insight into how governments undertake policy-driven change following cybersecurity crises to ensure sufficient security of their digitized service provisions. This paper’s findings are informative not only in continued decision-making in the Estonian system but also in other states currently implementing a digital governance structure, for which security mechanisms are of the utmost importance.

Keywords: cybersecurity, digital governance, Estonia, crisis management, governance in crisis

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Authors: Shital Jhunjhunwala, Shweta Saraf

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Research Question: The study, based on a survey, empirically tests the impact of the board’s engagement in the decision-making process on firm outcomes. It also examines the moderating effect of board leadership and board independence on the relationship. Research Findings: Boards’ engagement in the decision-making process is found to be vital for firm performance, wherein effective monitoring by the board outperforms their strategic guidance role in achieving desired outcomes. The separation of CEO and Chairman positively moderates the board’s engagement in protecting stakeholders’ interests, but lack of independence and passive behaviour of independent directors raises concern on the efficacy of independent directors. Theoretical Implications: The study provides the framework for process-oriented corporate governance research, where investigation of boards’ behaviour inside the boardroom develops a deeper understanding of board processes. Practitioner Implications: The study highlights the necessity of developing boards’ focus in a company on monitoring managerial actions. It suggests the need to separate the position of CEO and Chairman for addressing the interest of all stakeholders. It recommends policymakers review the existing mandate on board independence and create alternate monitoring mechanisms for addressing agency conflict.

Keywords: board, decision-making process, engagement, independence, leadership, innovation, stakeholders, firm performance, qualitative, India

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Authors: Chiara Mansanta, Daniela Sani

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The present paper presents the further development of the application of a standard methodology to boost innovation inside real case studies of manufacturing companies. The proposed methodology provides a viable solution for manufacturing companies that have to evaluate new business ideas. The study underlined the concept of entrepreneurship and how a manager can use it to promote innovation inside their companies. Starting from a literature study on entrepreneurship, this paper examines the role of the manager in supporting a company’s development. The empirical part of the study is based on two manufacturing companies that used the proposed methodology to favour entrepreneurship through an alternative approach. The research demonstrated the need for companies to have a structured and well-defined methodology to achieve their goals. The purpose of this article is to understand the significance of business models inside companies and explore how they affect business strategy and innovation management. The idea is to use business models to support entrepreneurs in their decision-making processes, reducing risks and avoiding errors.

Keywords: entrepreneurship, manufacturing companies, solution validation, strategic management

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Authors: Esperanza Garcia-Uceda, Josefina L. Murillo-Luna, M. Pilar Latorre-Martinez, Marta Ferrer-Serrano

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Social entrepreneurship represents an innovation of traditional business models. During the last decade, its important role in contributing to rural and regional development has been widely recognized, due to its capacity to combat the problem of depopulation through the creation of employment. However, the success of this type of innovative business initiatives depends to a large extent on the existence of an adequate ecosystem of support resources. Based on the theoretical framework of the quadruple helix (QH), which highlights the need for collaboration between different interest groups -university, industry, government and civil society- for the development of regional innovations, in this work the network analysis is applied to study the ecosystem of resources to support social entrepreneurship in the rural area of the province of Zaragoza (Spain). It is a quantitative analysis that can be used to measure the interactions between the different actors that make up the quadruple helix, as well as the networks created between the different institutions and support organizations, through the study of the complex networks they form. The results show the importance of the involvement of local governments and the university, as key elements in the development process, but also allow identifying other issues that are susceptible to improvement.

Keywords: ecosystem of support resources, network analysis, quadruple helix, social entrepreneurship

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Authors: Madhu Jain, Rakesh Kumar Meena

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This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

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Authors: Gisele Ragusa, Lilian Leung

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There are essential needs for science, technology, engineering, and math (STEM) workforces nationally. This important need underscores the necessity of increasing numbers of students attending both two-year community colleges and universities, thereby enabling and supporting a larger pool of students to enter the workforce. The greatest number of students in STEM programs attend public higher education institutions, with an even larger majority beginning their academic experiences enrolled in two-year public colleges. Accordingly, this research explores the impact of experiences and academic support practices on two-year (community) college students’ academic achievement in STEM majors with a focus on supporting students who are the first in their families to attend college. This research is a result of three years of iterative trials of differing supports to improve such students’ academic success with a cross-student comparative research methodological structure involving peer-to-peer and faculty academic supports. Results of this research indicate that background experiences and a combination of peer-to-peer and faculty-led academic support practices, including supplementary instruction, peer mentoring, and study skills support, significantly improve students’ academic success in STEM majors. These results confirm the needs that first-generation students have in navigating their college careers and what can be effective in supporting them.

Keywords: higher education policy, student support, two-year colleges, STEM achievement

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Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

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Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Mohammad Anwar, Hamid Ullah Khan, Shah Waliullah

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Recently, environmental education is an essential element in avoiding environmental degradation around the globe that needs new articles and policymakers’ emphasis. Hence, the present article examines the impact of environmental education on environmental knowledge, environmental behavior, and environmental attitudes in Indonesia. The present research also investigated the moderating role of government support in environmental education, environmental knowledge, environmental behavior, and environmental attitude in Indonesia. A questionnaire was used as the primary data collection method. The smart PLS was utilized to test the association among variables and the hypotheses of the study. The results revealed that environmental education had a significant and positive linkage with environmental knowledge, environmental behavior, and environmental attitude in Indonesia. The findings also exposed that government support significantly moderated environmental education, environmental knowledge, and environmental behavior in Indonesia. The findings of this research would provide help to the policymakers in establishing the policies related to environmental education and reducing environmental degradation.

Keywords: environmental education, environmental knowledge, environmental behavior, environmental attitude, government support

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Authors: Liu Yi-Hui, Chiu Fan-Yun, Lin Yu Fang, Jhang Yu Cih, He You Jing

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The demand for care support has been rising with the aging of society and the advancement of medical science and technology. To meet rising demand, the Taiwanese government promoted the “Long Term Care Ten-Year Plan 2.0” in 2017. However, this policy and its related services failed to be fully implemented because of the ignorance of the public, and their lack of desire, fear, or discomfort in using them, which is a major obstacle to the promotion of long-term care services. Given the above context, this research objectives included the following: (1) to understand the current situation and predicament of family caregivers; (2) to reveal the actual use and assistance of government’s long-term care resources for family caregivers; and (3) to explore the support and impact of social capital on family caregivers. A semi-structured in-depth interview with five family caregivers to understand long-term care networks and social capital for family caregivers.

Keywords: family caregivers, long-term care, social capital

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Authors: Filippo Portera

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Usually standard algorithms employ a loss where each error is the mere absolute difference between the true value and the prediction, in case of a regression task. In the present, we present several error weighting schemes that are a generalization of the consolidated routine. We study both a binary classification model for Support Vextor Classification and a regression net for Multylayer Perceptron. Results proves that the error is never worse than the standard procedure and several times it is better.

Keywords: loss, binary-classification, MLP, weights, regression

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Authors: Assem I. El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent Railway Control System (MARCS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, railway control, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Meng Wu, Atif Rahman, Eng Gee, Lim, Jeong Jin Yu, Rong Yan

Abstract:

Context: The COVID-19 pandemic has had a profound impact on mental health, with increased rates of anxiety and depression observed. Social support, a critical factor in mental well-being, has also undergone significant changes during the pandemic. This study aims to explore the relationship between social support, anxiety, and depression during COVID-19, taking into account various demographic and contextual factors. Research Aim: The main objective of this study is to conduct a comprehensive systematic review and meta-analysis to examine the impact of social support on anxiety and depression during the COVID-19 pandemic. The study aims to determine the consistency of these relationships across different age groups, occupations, regions, and research paradigms. Methodology: A scoping review and meta-analytic approach were employed in this study. A search was conducted across six databases from 2020 to 2022 to identify relevant studies. The selected studies were then subjected to random effects models, with pooled correlations (r and ρ) estimated. Homogeneity was assessed using Q and I² tests. Subgroup analyses were conducted to explore variations across different demographic and contextual factors. Findings: The meta-analysis of both cross-sectional and longitudinal studies revealed significant correlations between social support, anxiety, and depression during COVID-19. The pooled correlations (ρ) indicated a negative relationship between social support and anxiety (ρ = -0.30, 95% CI = [-0.333, -0.255]) as well as depression (ρ = -0.27, 95% CI = [-0.370, -0.281]). However, further investigation is required to validate these results across different age groups, occupations, and regions. Theoretical Importance: This study emphasizes the multifaceted role of social support in mental health during the COVID-19 pandemic. It highlights the need to reevaluate and expand our understanding of social support's impact on anxiety and depression. The findings contribute to the existing literature by shedding light on the associations and complexities involved in these relationships. Data Collection and Analysis Procedures: The data collection involved an extensive search across six databases to identify relevant studies. The selected studies were then subjected to rigorous analysis using random effects models and subgroup analyses. Pooled correlations were estimated, and homogeneity was assessed using Q and I² tests. Question Addressed: This study aimed to address the question of the impact of social support on anxiety and depression during the COVID-19 pandemic. It sought to determine the consistency of these relationships across different demographic and contextual factors. Conclusion: The findings of this study highlight the significant association between social support, anxiety, and depression during the COVID-19 pandemic. However, further research is needed to validate these findings across different age groups, occupations, and regions. The study emphasizes the need for a comprehensive understanding of social support's multifaceted role in mental health and the importance of considering various contextual and demographic factors in future investigations.

Keywords: social support, anxiety, depression, COVID-19, meta-analysis

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Authors: Abdel Rahman Khider Hassan

Abstract:

This paper describes a multi-criteria geospatial model for prediction of landslide hazard zonation (LHZ) for Lake Naivasha catchment (Kenya), based on spatial analysis of integrated datasets of location intrinsic parameters (slope stability factors) and external landslides triggering factors (natural and man-made factors). The intrinsic dataset included: lithology, geometry of slope (slope inclination, aspect, elevation, and curvature) and land use/land cover. The landslides triggering factors included: rainfall as the climatic factor, in addition to the destructive effects reflected by proximity of roads and drainage network to areas that are susceptible to landslides. No published study on landslides has been obtained for this area. Thus, digital datasets of the above spatial parameters were conveniently acquired, stored, manipulated and analyzed in a Geographical Information System (GIS) using a multi-criteria grid overlay technique (in ArcGIS 10.2.2 environment). Deduction of landslide hazard zonation is done by applying weights based on relative contribution of each parameter to the slope instability, and finally, the weighted parameters grids were overlaid together to generate a map of the potential landslide hazard zonation (LHZ) for the lake catchment. From the total surface of 3200 km² of the lake catchment, most of the region (78.7 %; 2518.4 km²) is susceptible to moderate landslide hazards, whilst about 13% (416 km²) is occurring under high hazards. Only 1.0% (32 km²) of the catchment is displaying very high landslide hazards, and the remaining area (7.3 %; 233.6 km²) displays low probability of landslide hazards. This result confirms the importance of steep slope angles, lithology, vegetation land cover and slope orientation (aspect) as the major determining factors of slope failures. The information provided by the produced map of landslide hazard zonation (LHZ) could lay the basis for decision making as well as mitigation and applications in avoiding potential losses caused by landslides in the Lake Naivasha catchment in the Kenya Highlands.

Keywords: decision making, geospatial, landslide, multi-criteria, Naivasha

Procedia PDF Downloads 206