Search results for: decentralized distributed training

Authors: Atya Nur Aisha, Pamoedji Hardjomidjojo, Yassierli

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Motivation is an important aspect which affects employee behavior to achieve performance. Working motivation tend to be unstable, it easily changing. This condition could be affected by individual factors, namely working ability, and organizational factors, such as working condition and incentives system. The purpose of this study was to examine the impact of individual and organizational factors on non-academic staff motivation. A questionnaire was designed and distributed to 150 non-academic staff of a university in Indonesia. Regression analysis was used to identify the relationship. Results revealed that individual working ability and incentives system had a positive impact on non-academic staff motivation (sig 0.001). This study provides information about practical implication for university authorities and theoretical implications for researchers who interested in exploring motivational and employee performance in a higher education context. It was proposed to increase productivity and work motivation of non-academic staff, university authorities should maintain equality and feasibility of incentives system and design a human resource development to improve employee ability.

Keywords: motivation, incentives, working ability, non-academic staff

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Authors: Mona M. Marzouk, Ahmed Elkhateeb, Mona Elshabrawy, Mai M. Farid, Salwa A. Kawashty, EL-Sayed S. Abdel-Hameed, Sameh R. Hussein

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The genus Farsetia Turra belongs to the family Brassicaceae and has approximately 30 accepted species distributed worldwide. Amongst them, Farsetia aegyptia Turra and Farsetia longisiliqua Decne. are two common species characteristic to the Egyptian flora. The present study considers the first characterization of the chemical constituents of F. longisiliqua, aiming to compare with those identified from the medicinal species (F. aegyptia). Additionally, the chemosystematic relationships between the two studied species were evaluated and highlight the medicinal importance for F. longisiliqua. The chemical profiling of their aqueous methanol extracts were carried out using the LC-ESI-MS technique and afforded 54 compounds belonging to different chemical groups. Flavonoids are the major constituents and are represented by 32 compounds (two C-glycosyl flavone, four flavones, and 26 flavonols). Their structural variations and common constituents confirmed the chemosystematic significance of the two species. Moreover, the flavonoid profiles showed major common constituents between the two investigated species, which predicted the medicinal importance of F. longisiliqua.

Keywords: brassicaceae, chemosystematics, farsetia, flavonoids, glucosinolates, LC-ESI-MS

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Authors: Milica Lilic, Marina Rosales Martínez

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Academic research cannot be oblivious to social problems and needs, so projects that have the capacity for transformation and impact should have the opportunity to go beyond the University circles and bring benefit to society. Apart from patents and R&D research contracts, this opportunity can be achieved through entrepreneurship as one of the most direct tools to turn knowledge into a tangible product. Thus, as an example of good practices, it is intended to analyze the case of an institutional entrepreneurship program carried out at the University of Seville, aimed at researchers interested in assessing the business opportunity of their research and expanding their knowledge on procedures for the commercialization of technologies used at academic projects. The program is based on three pillars: training, teamwork sessions and networking. The training includes aspects such as product-client fit, technical-scientific and economic-financial feasibility of a spin-off, institutional organization and decision making, public and private fundraising, and making the spin-off visible in the business world (social networks, key contacts, corporate image and ethical principles). On the other hand, the teamwork sessions are guided by a mentor and aimed at identifying research results with potential, clarifying financial needs and procedures to obtain the necessary resources for the consolidation of the spin-off. This part of the program is considered to be crucial in order for the participants to convert their academic findings into a business model. Finally, the networking part is oriented to workshops about the digital transformation of a project, the accurate communication of the product or service a spin-off offers to society and the development of transferable skills necessary for managing a business. This blended program results in the final stage where each team, through an elevator pitch format, presents their research turned into a business model to an experienced jury. The awarded teams get a starting capital for their enterprise and enjoy the opportunity of formally consolidating their spin-off company at the University. Studying the results of the program, it has been shown that many researchers have basic or no knowledge of entrepreneurship skills and different ways to turn their research results into a business model with a direct impact on society. Therefore, the described program has been used as an example to highlight the importance of knowledge transfer at the University and the role that this institution should have in providing the tools to promote entrepreneurship within it. Keeping in mind that the University is defined by three main activities (teaching, research and knowledge transfer), it is safe to conclude that the latter, and the entrepreneurship as an expression of it, is crucial in order for the other two to comply with their purpose.

Keywords: good practice, knowledge transfer, a spin-off company, university

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: banking system, Data Envelopment Analysis (DEA), Integrated Resilience Engineering (IRE), performance evaluation, perturbation analysis

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Authors: Muhammad Naveed Babur, Maria Liaqat

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Background & Objective: People with disabilities especially neurological disabilities have many unmet health and rehabilitation needs, face barriers in accessing mainstream health-care services, and consequently have poor health. There are not sufficient epidemiological studies from Pakistan which assess barriers to neurorehabilitation and ways to counter it. Objectives: The objective of the study was to determine the challenges and to evaluate the barriers for neuro-rehabilitation services in developing countries. Methods: This is Exploratory sequential qualitative study based on the Panel discussion forum in International rehabilitation sciences congress and national rehabilitation conference 2017. Panel group discussion has been conducted in February 2017 with a sample size of eight professionals including Rehabilitation medicine Physician, Physical Therapist, Speech Language therapist, Occupational Therapist, Clinical Psychologist and rehabilitation nurse working in multidisciplinary/Interdisciplinary team. A comprehensive audio-videography have been developed, recorded, transcripted and documented. Data was transcribed and thematic analysis along with characteristics was drawn manually. Data verification was done with the help of two separate coders. Results: After extraction of two separate coders following results are emerged. General category themes are disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. Barriers identified at the level are high cost, stigma, lengthy course of recovery. Hospital related barriers are lack of social support and individually tailored goal setting processes. Organizational barriers identified are lack of basic diagnostic facilities, lack of funding and human resources. Recommendations given by panelists were investment in education, capacity building, infrastructure, governance support, strategies to promote communication and realistic goals. Conclusion: It is concluded that neurorehabilitation in developing countries need attention in following categories i.e. disease profile, demographic profile, training and education, research, barriers, governance, global funding, informal care, resources and cultural beliefs and public awareness. This study also revealed barriers at the level of patient, hospital, organization. Recommendations were also given by panelists.

Keywords: disability, neurorehabilitation, telerehabilitation, disability

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Authors: Ying Zhao, Xingyan Bin

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Semi-supervised clustering algorithms have been shown effective to improve clustering process with even limited supervision. However, semi-supervised hierarchical clustering remains challenging due to the complexities of expressing constraints for agglomerative clustering algorithms. This paper proposes novel semi-supervised agglomerative clustering algorithms to build a hierarchy based on a known reference tree. We prove that by enforcing distance constraints defined by a reference tree during the process of hierarchical clustering, the resultant tree is guaranteed to be consistent with the reference tree. We also propose a framework that allows the hierarchical tree generation be aware of levels of levels of the agglomerative tree under creation, so that metric weights can be learned and adopted at each level in a recursive fashion. The experimental evaluation shows that the additional cost of our contraint-based semi-supervised hierarchical clustering algorithm (HAC) is negligible, and our combined semi-supervised HAC algorithm outperforms the state-of-the-art algorithms on real-world datasets. The experiments also show that our proposed methods can improve clustering performance even with a small number of unevenly distributed labeled data.

Keywords: semi-supervised clustering, hierarchical agglomerative clustering, reference trees, distance constraints

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Authors: Kamal Upadhyay, Zhou Hua, Yu Rui

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This paper aims to improve the streamline linked with the flow field and cavitation on the valve sleeve. We observed that local pressure fluctuation produces a low-pressure zone, central to the formation of vapor volume fraction within the valve chamber led to air-bubbles (or cavities). Thus, it allows simultaneously to a severe negative impact on the inner surface and lifespan of the valve sleeves. Cavitation reduction is a vitally important issue to pressure control valves. The optimization of the flow field is proposed in this paper to reduce the cavitation of valve sleeves. In this method, the inner wall of the valve sleeve is changed from a cylindrical surface to the conical surface, leading to the decline of the fluid flow velocity and the rise of the outlet pressure. Besides, the streamline is distributed inside the sleeve uniformly. Thus, the bubble generation is lessened. The fluid models are built and analysis of flow field distribution, pressure, vapor volume and velocity was carried out using computational fluid dynamics (CFD) and numerical technique. The results indicate that this structure can suppress the cavitation of valve sleeves effectively.

Keywords: streamline, cavitation, optimization, computational fluid dynamics

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Authors: Rui de Abrantes, André Luiz Silva Forcetto

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Air pollution is a big problem in many cities around the world. Brazilian big cities also have this problem, where millions of people are exposed daily to pollutants levels above the recommended by WHO. Brazil has taken several actions to reduce air pollution, among others, controlling the atmospheric emissions from vehicles, non-road mobile machinery, and motorcycles, but on the other side, there are no emissions controls for locomotives, which are exposing the population to tons of pollutants annually. The rail network is not homogeneously distributed in the national territory; it is denser near the big cities, and this way, the population is more exposed to pollutants; apart from that, the government intends to increase the rail network as one of the strategies for greenhouse gas mitigation, complying with the international agreements against the climate changes. This paper initially presents the estimated emissions from locomotive fleets with no emission control and with emission control equivalent to US Tier 3 from 2028 and for the next 20 years. However, we realized that a program equivalent to phase Tier 3 would not be effective, so we proposed a program in two steps that will avoid the release of more than 2.4 million tons of CO and 531,000 tons of hydrocarbons, 3.7 million tons of nitrogen oxides, and 102,000 tons of particulate matter in 20 years.

Keywords: locomotives, emission control, air pollution, pollutants emission

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: dialogue management, response generation, deep learning, evaluation

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Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

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Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km², and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: watershed simulation, WetSpa, stream flow, flood prediction

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Authors: Donggun Lee, Q-Han Park

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Due to its coarse grid, the Pseudo-Spectral Time Domain (PSTD) method has advantages against the Finite Difference Time Domain (FDTD) method in terms of memory requirement and operation time. However, since the efficiency of parallelization is much lower than that of FDTD, PSTD is not a useful method for a large-scale electromagnetic simulation in a parallel platform. In this paper, we propose the parallelization technique of the hybrid PSTD-FDTD (HPF) method which simultaneously possesses the efficient parallelizability of FDTD and the quick speed and low memory requirement of PSTD. Parallelization cost of the HPF method is exactly the same as the parallel FDTD, but still, it occupies much less memory space and has faster operation speed than the parallel FDTD. Experiments in distributed memory systems have shown that the parallel HPF method saves up to 96% of the operation time and reduces 84% of the memory requirement. Also, by combining the OpenMP library to the MPI library, we further reduced the operation time of the parallel HPF method by 50%.

Keywords: FDTD, hybrid, MPI, OpenMP, PSTD, parallelization

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Authors: Tülin Koldaş, Özlem Çetin Erdoğan, Ahmet Beyarslan

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Brachistinae Föerster, 1862 is a subfamily of the family Braconidae (order Hymenoptera) with about 410 species distributed all around the world. Brachistinae includes the genera, Eubazus Nees von Esenbeck 1814, Foersteria Szépligeti 1896, Chelostes van Achterberg 1990, Triaspis Haliday 1835 and Schizoprymnus Förster 1862. Members of the subfamily live as parasitoids on the families Curculionidae and Apionidae (Coleoptera), which also include very important agricultural pests.  In generally, members of the genus Triaspis are poorly known biologically. The genus is represented by 37 species in the West Palearctic region and 118 species worldwide. Adult specimens of Triaspis were collected from as wide a range of habitats as possible at different altitudes in different parts of Turkey between 1982 and 2010. Samples collected from short plants using standard insect sweeping nets were transferred into tubes containing 70% ethanol and labelled following their preparations according to museum techniques. Seven Triaspis species have been reported from Turkey in this study. Five of these species are new to the fauna of Turkey.

Keywords: Triaspis, Braconidae, Hymenoptera, Turkey, fauna

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Authors: John Chau, Tzvi Aviv

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Cardiometabolic conditions (hypertension, diabetes, and hyperlipidemia) are major public health concerns. Analysis of all prescription records from about 10 million patients at the largest network of pharmacies in Canada reveals small year-over-year increases in the treatment prevalence of cardiometabolic diseases prior to the COVID-19 pandemic. Cardiometabolic treatment rates increase with age and are higher in males than females. Hypertension treatment rates were 24% in males and 19% in females in 2021. Diabetes treatment rates were 10% in males and 7% in females in 2021. Geospatial analysis using patient addresses reveals interesting differences among provinces and neighborhoods in Canada. Using digital surveys distributed among 8,504 Canadian adults, an increase in hypertension awareness with age and female gender was observed. However, 7% of seniors and 6% of middle-aged Canadians reported uncontrolled blood pressure (>140/90 mmHg). In addition, elevated blood pressure (130-139/80-89 mmHg) was reported by 20% of seniors and 14% of middle-aged Canadians.

Keywords: cardiometabolic conditions, diabetes, hypertension, precision public health

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Tania Chalton

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In June 2013, an independent review of the Liverpool Care Pathway (LCP) identified a number of problems with the implementation of the LCP in the UK and recommended that it be replaced by individual care plans for each patient. As a result of the UK findings, in November 2013 the Ministry of Health (MOH) commissioned the Palliative Care Council to initiate a programme of work to investigate an appropriate approach for the care of people in their last days of life in New Zealand (NZ). The Last Days of Life Working Group commenced a process to develop national consensus on the care of people in their last days of life in April 2014. In order to develop its advice for the future provision of care to people in their last days of life, the Working Group (WG) established a comprehensive work programme and as a result has developed a series of working papers. Specific areas of focus included: An analysis of the UK Independent Review findings and an assessment of these findings to the NZ context. A stocktake of services providing care to people in their last days of life, including aged residential care (ARC); hospices; hospitals; and primary care. International and NZ literature reviews of evidence and best practice. Survey of family to understand the consumer perspective on the care of people in their last days of life. Key aspects of care that required further considerations for NZ were: Terminology: clarify terminology used in the last days of life and in relation to death and dying. Evidenced based: including specific review of evidence regarding, spiritual, culturally appropriate care as well as dementia care. Diagnosis of dying: need for both guidance around the diagnosis of dying and communication with family. Workforce issues: access to an appropriate workforce after hours. Nutrition and hydration: guidance around appropriate approaches to nutrition and hydration. Symptom and pain management: guidance around symptom management. Documentation: documentation of the person’s care which is robust enough for data collection and auditing requirements, not ‘tick box’ approach to care. Education and training: improved consistency and access to appropriate education and training. Leadership: A dedicated team or person to support and coordinate the introduction and implementation of any last days of life model of care. Quality indicators and data collection: model of care to enable auditing and regular reviews to ensure on-going quality improvement. Cultural and spiritual: address and incorporate any cultural and spiritual aspects. A final document was developed incorporating all the evidence which provides guidance to the health sector on best practice for people at end of life: “Principles and guidance for the last days of life: Te Ara Whakapiri”.

Keywords: end of life, guidelines, New Zealand, palliative care

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Authors: Mehak Masood

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Education is critical for promoting sustainable development and improving the capacity of people to address environment and development issues. It is also critical for achieving environmental and ethical awareness, values and attitudes, skills and behaviour consistent with sustainable development and for effective public participation in decision-making. In this regard, The British Council Pakistan have conducted a need assessment study conducted during the training sessions with three different groups of educationists belonging to both government and public sectors on the topic of Climate Change and Environmental Education (CCEE). This study aims to review perceptions about climate change and environmental education and analyze its need and importance according to educationists of Pakistan.

Keywords: environmental education, climate change, resilience development, awareness

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Authors: Samar Alarif

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Smart sustainable educational campuses are the latest paradigm of innovation in the education domain. Campuses become a hub for sustainable environmental innovations. University has a vital role in paving the road for digital transformations in the infrastructure domain by preparing skilled engineers and specialists. The open digital platform enables smart campuses to simulate real education experience by managing their infrastructure within the curriculums. Moreover, it allows the engagement between governments, businesses, and citizens to push for innovation and sustainable services. Urban and building information modeling platforms have recently attained widespread attention in smart campuses due to their applications and benefits for creating the campus's digital twin in the form of an open digital platform. Qualitative and quantitative strategies were used in directing this research to develop and validate the UIM/BIM platform benefits for smart campuses FM and its impact on the institution's sustainable vision. The research findings are based on literature reviews and case studies of the TU berlin El-Gouna campus. Textual data will be collected using semi-structured interviews with actors, secondary data like BIM course student projects, documents, and publications related to the campus actors. The study results indicated that UIM/BIM has several benefits for the smart campus. Universities can achieve better capacity-building by integrating all the actors in the UIM/BIM process. Universities would achieve their community outreach vision by launching an online outreach of UIM/BIM course for the academic and professional community. The UIM/BIM training courses would integrate students from different disciplines and alumni graduated as well as engineers and planners and technicians. Open platforms enable universities to build a partnership with the industry; companies should be involved in the development of BIM technology courses. The collaboration between academia and the industry would fix the gap, promote the academic courses to reply to the professional requirements, and transfer the industry's academic innovations. In addition to that, the collaboration between academia, industry, government vocational and training centers, and civil society should be promoted by co-creation workshops, a series of seminars, and conferences. These co-creation activities target the capacity buildings and build governmental strategies and policies to support expanding the sustainable innovations and to agree on the expected role of all the stakeholders to support the transformation.

Keywords: smart city, smart educational campus, UIM, urban platforms, sustainable campus

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Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

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This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed that students experience different types of emotions during the study, and this was found to have a significant effect on their academic performance. A total of one thousand six hundred and seventy-five (1675) students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. Sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: motivation, self-determination, test anxiety, academic performance, and academic engagement

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Ian Christopher Rocha

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This study aimed to determine the association of the quality of life (QOL) of the caregivers of children in need of special protection (CNSP) in child-caring institutions in Metro Manila with the levels of their role overload (RO) and role distress (RD). The CNSP in this study covered the orphaned, abandoned, abused, neglected, exploited, and mentally-challenged children. In this study, the domains of QOL included physical health (PH), psychological health, social health (SH), and living conditions (LC). It also intended to ascertain the association of their personal and work-related characteristics with their RO and RD levels. The respondents of this study were 130 CNSP caregivers in 17 residential child-rearing institutions in Metro Manila. A purposive non-probability sampling was used. Using a quantitative methodological approach, the survey method was utilized to gather data with the use of a self-administered structured questionnaire. Data were analyzed using both descriptive and inferential statistics. Results revealed that the level of RO, the level of RD, and the QOL of the CNSP caregivers were all moderate. Data also suggested that there were significant positive relationships between the RO level and the caregivers’ characteristics, such as age, the number of training, and years of service in the institution. At the same time, the findings revealed that there were significant positive relationships between the RD level and the caregivers’ characteristics, such as age and hours of care rendered to their care recipients. In addition, the findings suggested that all domains of their QOL obtained significant relationships with their RO level. For the correlations of their level of RO and their QOL domains, the PH and the LC obtained a moderate negative correlation with the RO level while the rest of the domains obtained weak negative correlations with RO level. For the correlations of their level of RD and the QOL domains, all domains, except SH, obtained strong negative correlations with the level of RD. The SH revealed to have a moderate negative correlation with RD level. In conclusion, caregivers who are older experience higher levels of RO and RD; caregivers who have more training and years of service experience the higher level of RO; and caregivers who have longer hours of rendered care experience the higher level of RD. In addition, the study affirmed that if the levels of RO and RD are high, the QOL is low, and vice versa. Therefore, the RO and RD levels are reliable predictors of the caregivers’ QOL. In relation, the caregiving situation in the Philippines revealed to be unique and distinct from other countries because the levels of RO and RD and the QOL of Filipino CNSP caregivers were all moderate in contrast with their foreign counterparts who experience high caregiving RO and RD leading to low QOL.

Keywords: quality of life, caregivers, children in need of special protection, physical health, psychological health, social health, living conditions, role overload, role distress

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Authors: Wei-Han Wang, Hsiang-Yu Yu, Mau-Sun Hua

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Theory of Mind (ToM) refers to the ability to infer another’s mental state. With appropriate ToM, one can behave well in social interactions. A growing body of evidence has demonstrated that patients with temporal lobe epilepsy (TLE) may have damaged ToM due to impact on regions of the underlying neural network of ToM. However, the question of whether there is cerebral laterality for ToM functions remains open. This study aimed to examine whether there is cerebral lateralization for ToM abilities in TLE patients. Sixty-seven adult TLE patients and 30 matched healthy controls (HC) were recruited. Patients were classified into right (RTLE), left (LTLE), and bilateral (BTLE) TLE groups on the basis of a consensus panel review of their seizure semiology, EEG findings, and brain imaging results. All participants completed an intellectual test and four tasks measuring basic and advanced ToM. The results showed that, on all ToM tasks; (1)each patient group performed worse than HC; (2)there were no significant differences between LTLE and RTLE groups; (3)the BTLE group performed the worst. It appears that the neural network responsible for ToM is distributed evenly between the cerebral hemispheres.

Keywords: cerebral lateralization, social cognition, temporal lobe epilepsy, theory of mind

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Authors: Alexander Hempfing

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The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.

Keywords: economic integration, industrial organization, input-output economics, network economics, production networks

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Authors: Sang Hee Shin

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The technical improving project is for using the domestic construction technology in the weak soil condition. The improved technology is applied directly under local construction site at OOO, OOO. Existing anchor technology was developed for the case of soft ground as N value 10 or less. In case of soft ground and heavy load, the attachment site per one strand is shortened due to the distributed interval so that the installation site is increased relatively and being economically infeasible. In addition, in case of high tensile load, adhesion phenomenon between wedge and block occurs. To solve these problems, it strengthens the function of the attached strands to treat a ‘bulbing’ on the strands. In the solution for minimizing the internal damage and strengthening the removal function, it induces lubricating action using the film and the attached film, and it makes the buffer structure using wedge lubricating structure and the spring. The technology is performed such as in-house testing and the field testing. The project can improve the reliability of the standardized quality technique. As a result, it intended to give the technical competitiveness.

Keywords: anchor, improving technology, removal anchor, soil reinforcement, weak soil

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Authors: Cynthia Mahadi, Norhafezah Kasmuri

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Water scarcity is a growing issue these days. As a result, saltwater is being considered a limitless supply of fresh water through the desalination process, which is likely to address the worldwide water crisis, including in Malaysia. This study aims to offer the best management practice for controlling brine discharge in Malaysia by comparing environmental regulations on brine waste management in other countries. Then, a survey was distributed to the public to acquire further information about their level of awareness of the harmful effects of brine waste and to find out their perspective on the proposed solutions to ensure the effectiveness of the measures. As a result, it has been revealed that Malaysia still lacks regulations regarding the disposal of brine waste. Thus, a recommendation based on practices in other nations has been put forth by this study. This study suggests that the government and Malaysia's environmental regulatory body should govern brine waste disposal in the Environmental Quality Act 1974. Also, to add the construction of a desalination plant in Schedule 1 of prescribed activities was necessary. Because desalination plants can harm the environment during both construction and operation, every proposal for the construction of a desalination plant should involve the submission of an environmental impact assessment (EIA).

Keywords: seawater desalination, brine waste, environmental impact assessment, fuzzy Delphi method

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Authors: Hassan Gana Abdullahi, Michael A. Fullen, David Oloke

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Drought poses an enormous global threat to sustainable development and is expected to increase with global climate change. Drought and desertification are major problems in Yobe State (north-east Nigeria). This investigation aims to develop a workable framework and management tool for drought mitigation in Yobe State. Mixed methods were employed during the study and additional qualitative information was gathered through Focus Group Discussions (FGD). Data on socio-economic impacts of drought were thus collected via both questionnaire surveys and FGD. In all, 1,040 questionnaires were distributed to farmers in the State and 721 were completed, representing a return rate of 69.3%. Data analysis showed that 97.9% of respondents considered themselves to be drought victims, whilst 69.3% of the respondents were unemployed and had no other means of income, except through rain-fed farming. Developing a viable and holistic approach to drought mitigation is crucial, to arrest and hopefully reverse environment degradation. Analysed data will be used to develop an integrated framework for drought mitigation and management in Yobe State. This paper introduces the socio-economic and environmental effects of drought in Yobe State.

Keywords: drought, climate change, mitigation, management, Yobe State

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Authors: Betül Demirbağ, Nesrin Demir

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As a developmental period, early adulthood has a vital role in romantic relationships in young adult's life. lt's known that in this period, satisfaction of individual needs such as affiliation is essential for well-functioning and to be succeeded in sequent developmental task. Romantic relationships have an expected association with attachment style. But it's needed to get more information about indicators of romantic relationships in different cultural backgrounds. in this research it's aimed to investigate whether there is a relationship between romantic relationship beliefs and Ego identity status and also other possible indicators such as gender, age, socioeconomic status. Participants were undergraduate students training in various programs in Education Faculty in Adiyaman University. As data collection tool, Romantic Relationship Beliefs scale and Ego Identity Process Questionnaire which was adapted into Turkish were used. Results were discussed in the relevant literature.

Keywords: ego identity, romantic relationships, university counseling

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Authors: Ahmed Emad Ahmed

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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

Procedia PDF Downloads 151

Authors: Veronica Botero, Karen Ortiz

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The Faculty of Mines, of the National University of Colombia, Medellín Campus, is a faculty that has 136 years of history and represents one of the most important study centers in the country in the field of engineering and scientific research, as well as a reference at a global, national, and Latin American level in this matter. Despite being a faculty with so many years of history and having trained a large number of graduates under the traditional mechanistic and androcentric paradigm, which reproduces the logic of the traditional scientific method and the differentiated and severe look between subject-object of research among other binarisms, has also been the place where professors and students have become aware of the need to transform this paradigm into engineering, and focus on the sustainability of diversity and the well-being of the natural and social systems that inhabit the territories and has opened possibilities for the implementation of classes that address feminist pedagogical theories and practices. The class: The return of the witches, is an initiative that constitutes an important training exercise that provides students with the study of feminisms, the importance of closing gender gaps and critical readings on the traditional paradigm of engineering. The objective of this article is to present a systematization of the experience of design, implementation and development of this elective class, describing the tensions that arose at the time when a subject of this style was created and proposed in the Department of Geosciences and Environment, from the Faculty of Mines in 2022; the reactions of the groups of students who have taken it and their perceptions and opinions about ecofeminism as proposals for critical analysis and practices in relation to the environment and, above all, how their readings of the world have changed after having studied this subject for a semester. The pedagogical journey and the feminist methodologies that have been designed and adjusted over two years of work will be explained based on the sharing of situated knowledge of the students and the two teachers who teach the course, who pose challenges to the dominant ideology in engineering since one of them is trained in human sciences and feminist studies and the other, although trained in civil engineering and geosciences, is a woman with diverse sexual orientation and is the first professor to have assumed the position of dean in the 135 years of history of the Faculty. The transformations in the life experience of the students are revealing since they affirm that the training process is forceful and powerful to outline a much more qualified and critical professional profile that contributes to the transformation of gender gaps in the country. This class is therefore a challenge in this Faculty of Engineering that still presents a dominant ideology on gender that has not been questioned or challenged before.

Keywords: feminisms, gender equality, gender bias, engineering for life Manifiesto.

Procedia PDF Downloads 53

Authors: Mokopane Charles Marakalala

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Research shows that mobile fraud has grown exponentially in South Africa during the lockdown caused by the COVID-19 pandemic. According to the South African Banking Risk Information Centre (SABRIC), fraudulent online banking and transactions resulted in a sharp increase in cybercrime since the beginning of the lockdown, resulting in a huge loss to the banking industry in South Africa. While the Financial Intelligence Centre Act, 38 of 2001, regulate financial transactions, it is evident that criminals are making use of technology to their advantage. Money-laundering ranks among the major crimes, not only in South Africa but worldwide. This paper focuses on the impact of biometric-based solutions in combatting mobile fraud at the South African Risk Information. SABRIC had the challenges of a successful mobile fraud; cybercriminals could hijack a mobile device and use it to gain access to sensitive personal data and accounts. Cybercriminals are constantly looting the depths of cyberspace in search of victims to attack. Millions of people worldwide use online banking to do their regular bank-related transactions quickly and conveniently. This was supported by the SABRIC, who regularly highlighted incidents of mobile fraud, corruption, and maladministration in SABRIC, resulting in a lack of secure their banking online; they are vulnerable to falling prey to fraud scams such as mobile fraud. Criminals have made use of digital platforms since the development of technology. In 2017, 13 438 instances involving banking apps, internet banking, and mobile banking caused the sector to suffer gross losses of more than R250,000,000. The final three parties are forced to point fingers at one another while the fraudster makes off with the money. A non-probability sampling (purposive sampling) was used in selecting these participants. These included telephone calls and virtual interviews. The results indicate that there is a relationship between remote online banking and the increase in money-laundering as the system allows transactions to take place with limited verification processes. This paper highlights the significance of considering the development of prevention mechanisms, capacity development, and strategies for both financial institutions as well as law enforcement agencies in South Africa to reduce crime such as money-laundering. The researcher recommends that strategies to increase awareness for bank staff must be harnessed through the provision of requisite training and to be provided adequate training.

Keywords: biometric-based solution, investigation, cybercrime, forensic investigation, fraud, combatting

Procedia PDF Downloads 78

Authors: Elabed Saud

Abstract:

This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

Procedia PDF Downloads 704