Search results for: leadership training

Authors: B. K. Manjunatha Goud, Aruna Chanu Oinam

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The undergraduate medical curriculum is oriented towards training the students to undertake the responsibilities of a physician. During the training period, adequate emphasis is placed on inculcating logical and scientific habits of thought; clarity of expression and independence of judgment; and ability to collect and analyze information and to correlate them. At Ras Al Khaimah Medical and Health Sciences University (RAKMHSU), Biochemistry a basic medical science subject is taught in the 1st year of 5 years medical course with vertical interdisciplinary interaction with all subjects, which needs to be taught and learned adequately by the students to be related to clinical case or clinical problem in medicine and future diagnostics so that they can practice confidently and skillfully in the community. Based on these facts study was done to know the extent of usage of library resources by the students and the impact of study materials on their preparation for examination. It was a comparative cross sectional study included 100 and 80 1st and 2nd-year students who had successfully completed Biochemistry course. The purpose of the study was explained to all students [participants]. Information was collected on a pre-designed, pre-tested and self-administered questionnaire. The questionnaire was validated by the senior faculties and pre tested on students who were not involved in the study. The study results showed that 80.30% and 93.15% of 1st and 2nd year students have the clear idea of course outline given in course handout or study guide. We also found a statistically significant number of students agreed that they were benefited from the practical session and writing notes in the class hour. A high percentage of students [50% and 62.02%] disagreed that that reading only the handouts is enough for their examination as compared to other students. The study also showed that only 35% and 41% of students visited the library on daily basis for the learning process, around 65% of students were using lecture notes and text books as a tool for learning and to understand the subject and 45% and 53% of students used the library resources (recommended text books) compared to online sources before the examinations. The results presented here show that students perceived that e-learning resources like power point presentations along with text book reading using SQ4R technique had made a positive impact on various aspects of their learning in Biochemistry. The use of library by students has overall positive impact on learning process especially in medical field enhances the outcome, and medical students are better equipped to treat the patient. But it’s also true that use of library use has been in decline which will impact the knowledge aspects and outcome. In conclusion, a student has to be taught how to use the library as learning tool apart from lecture handouts.

Keywords: medical education, learning resources, study guide, biochemistry

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Authors: Naufal Ahmad Rijalul Alam

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This article presents a quality of education for the poor people in Indonesia and the offering of strategy to be done. It also investigates the influence of Islamic Education which stands behind the religious values in developing effort of government to respond the problem with using humanities approaches in medium society. The offering strategy resulted in four agenda: 1) building a shared commitment, 2) encouraging the improvement of the quality of public and private schools, 3) encouraging the use of 'the indicator of disaffection' for gifted children, and 4) encouraging the enlargement of vocational training centers and polytechnics. The conclusion is that the quality of education can be increased with these four agenda, although they are not too easy because it deals with other factors such as the economy, politics, and culture which is happening in the country.

Keywords: quality education, poor people, strategy of Islamic education, medium community

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Authors: Johan Loeckx, Joeri Bultheel

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Recently, the application of deep learning to music has gained popularity. Its true potential, however, has been largely unexplored. In this paper, a new idea for representing the dynamic behavior of music is proposed. A ”forward” conditional RBM takes into account not only preceding but also future samples during training. Though this may sound controversial at first sight, it will be shown that it makes sense from a musical and neuro-cognitive perspective. The model is applied to reconstruct music based upon the first notes and to improvise in the musical style of a composer. Different to expectations, reconstruction accuracy with respect to a regular CRBM with the same order, was not significantly improved. More research is needed to test the performance on unseen data.

Keywords: deep learning, restricted boltzmann machine, music generation, conditional restricted boltzmann machine (CRBM)

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Authors: Juan-Gabriel Cegarra-Navarro, Alexeis Garcia-Perez, Denise Bedford

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This paper provides guidelines for what constitutes a knowledge worker. Many graduates from non-managerial domains adopt, at some point in their professional careers, management roles at different levels, ranging from team leaders through to executive leadership. This is particularly relevant for professionals from an engineering background. Moving from a technical to an executive-level requires an understanding of those behaviour management techniques that can motivate and support individuals and their performance. Further, the transition to management also demands a shift of contextual enablers from tangible to intangible resources, which allows individuals to create new capacities, competencies, and capabilities. In this dynamic process, the knowledge worker becomes that key individual who can help members of the management board to transform information into relevant knowledge. However, despite its relevance in shaping the future of the organization in its transition to the knowledge economy, the role of a knowledge worker has not yet been studied to an appropriate level in the current literature. In this study, the authors review both the contextual enablers and behaviour outputs related to the role of the knowledge worker and relate these to their ability to deal with everyday management issues such as knowledge heterogeneity, varying motivations, information overload, or outdated information. This study highlights that the aggregate of capacities, competences and capabilities (CCCs) can be defined as knowledge structures, the study proposes several contextual enablers and behaviour outputs that knowledge workers can use to work cooperatively, acquire, distribute and knowledge. Therefore, this study contributes to a better comprehension of how CCCs can be managed at different levels through their contextual enablers and behaviour outputs.

Keywords: knowledge workers, capabilities, capacities, competences, knowledge structures

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Authors: Khalid A. Alotaibi

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To assess the students, there are different strategies adopted by teachers and all are important while taking their scope into consideration. Teachers may face some obstacles that prevent them using the assessment for learning. These obstacles can be internal or external. The present study has been collected from two regions (Riyadh and Hotat Bani Tamim) of Saudi Arabia, with sample size of 174 teachers. The results of the study have shown that the significant factors that can prevent teachers using assessment for learning are; the way of introducing the new form of assessment, lack of teachers' training, clarity of the regulations and size of students in the class. Additionally, other elements have also shown in this paper.

Keywords: teachers, assessment, assessment for learning, internal factors and external factors

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Authors: Vo Ngoc Phu, Phan Thi Tuoi

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We have explored different methods of improving the accuracy of sentiment classification. The sentiment orientation of a document can be positive (+), negative (-), or neutral (0). We combine five dictionaries from [2, 3, 4, 5, 6] into the new one with 21137 entries. The new dictionary has many verbs, adverbs, phrases and idioms, that are not in five ones before. The paper shows that our proposed method based on the combination of Term-Counting method and Enhanced Contextual Valence Shifters method has improved the accuracy of sentiment classification. The combined method has accuracy 68.984% on the testing dataset, and 69.224% on the training dataset. All of these methods are implemented to classify the reviews based on our new dictionary and the Internet Movie data set.

Keywords: sentiment classification, sentiment orientation, valence shifters, contextual, valence shifters, term counting

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Authors: E. Sahar

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Civic political knowledge is crucial for the stability of democratic countries. In the USA, Americans have poor knowledge about their constitution and their political systems. Some states such as Florida State suffers from a huge decline in civics comparing to the National Average. This study concerns with using new technologies such as augmented reality to engage students in learning civics in classrooms. This is a participatory study, which engage teachers in the process of designing augmented reality civic games. The researcher used survey to find out the materials that teachers struggle with while teaching civics. Four lessons were found the most difficult to teach for middle school students: SS7C1.1 Enlightenment thinkers, SS7C1.2 influencing documents, SS7C1.7-Weakness of the Articles of Confederation, and Forms and systems of governments. For the limited scope of this study, we focused on “Forms and Systems of governments’ as the main project. Augmented Reality is used to help students to engage in learning civics through building a game that is based on the pedagogy constructivism theory. The resulted project meets the educational requirements for civics, provide students with more knowledge in at stake issues such as migration and citizenship, and help them to build leadership skills while playing in groups. The augmented reality game is also designed to test the students learning for each stage. This study helps to generate insightful implications for the use of augmented reality by educators, researchers, instructional designers, and developers who are interested in integrating technology in teaching civics for students in middle school classrooms.

Keywords: augmented reality, games, civics teaching, Florida middle school

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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: Vania Helena Tonussi Vidal, Ester Eliane Jeunon

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This article aims to analyze the change processes of management related bureaucracy and learning organization model. The theoretical framework was based on Beer and Nohria (2001) model, identified as E and O Theory. Based on this theory the empirical research was conducted in connection with six key dimensions: goal, leadership, focus, process, reward systems and consulting. We used a case study of an educational Institution located in Barbacena, Minas Gerais. This traditional center of technical knowledge for long time adopted the bureaucratic way of management. After many changes in a business model, as the creation of graduate and undergraduate courses they decided to make a deep change in management model that is our research focus. The data were collected through semi-structured interviews with director, managers and courses supervisors. The analysis were processed by the procedures of Collective Subject Discourse (CSD) method, develop by Lefèvre & Lefèvre (2000), Results showed the incremental growing of management model toward a learning organization. Many impacts could be seeing. As negative factors we have: people resistance; poor information about the planning and implementation process; old politics inside the new model and so on. Positive impacts are: new procedures in human resources, mainly related to manager skills and empowerment; structure downsizing, open discussions channel; integrated information system. The process is still under construction and now great stimulus is done to managers and employee commitment in the process.

Keywords: bureaucracy, organizational learning, organizational change, E and O theory

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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: 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: 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: 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: 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: Monsuru Oyenola Popoola, Oladapo Samson Abiola, Wusamotu Alao Adeniji

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The prevalent and incessant abandonment of road construction projects are alarming that it creates several negative effects to social, economic and environmental values of the project. The purpose of this paper is to investigate and determined the various causes and effects of abandoning road construction projects in Nigeria. Likert Scale questionnaire design was used to administered and analysed the data obtained for the stydy. 135 (Nr) questionnaires were completed and retrieved from the respondents, out of 200 (Nr) questionnaires sent out, representing a response rate of 67.5%. The analysis utilized the Relative Importance Index (R.I.I.) method and the results are presented in tabular form. The findings confirms that at least 20 factors were the causes of road projects abandonment in Nigeria with most including Leadership Instability, Improper Project Planning, Inconsistence in government policies and Design, Contractor Incompetence, Economy Instability and Inflation, Delay in remittance of money, Improper financial analysis, Poor risk management, Climatic Conditions, Improper Project Estimates etc. The findings also show that at least eight (8) effect were identified on the system, and these include; Waste of Financial Resources, Loss of economic value, Environmental degradation, Loss of economic value, Reduction in standard of living, Litigation and Arbitration, etc. The reflection is that allocating reasonable finance, developing appropriate and effective implementation plans and monitoring, evaluation and reporting on development project activities by key actors should enhance in resolving the problem of road projects abandonment.

Keywords: road construction, abandonment of road projects, climatic condition, project planning, contractor

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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

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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.

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Authors: Livhuwani Muthelo, R. N. Malema, T. M. Mothiba

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Long term exposure to excessive noise in the mining industry increases the risk of noise induced hearing loss, with consequences for employee’s health, productivity and the overall quality of life. Objective: The objective of this study was to investigate the factors that contribute to Noise Induced Hearing Loss amongst employees at the Platinum mine in the Limpopo Province, South Africa. Study method: A qualitative, phenomenological, exploratory, descriptive, contextual design was applied in order to explore and describe the contributory factors. Purposive non-probability sampling was used to select 10 male employees who were diagnosed with NIHL in the year 2014 in four mine shafts, and 10 managers who were involved in a Hearing Conservation Programme. The data were collected using semi-structured one-on-one interviews. A qualitative data analysis of Tesch’s approach was followed. Results: The following themes emerged: Experiences and challenges faced by employees in the work environment, hearing protective device factors and management and leadership factors. Hearing loss was caused by partial application of guidelines, policies, and procedures from the Department of Minerals and Energy. Conclusion: The study results indicate that although there are guidelines, policies, and procedures available, failure in the implementation of one element will affect the development and maintenance of employees hearing mechanism. It is recommended that the mine management should apply the guidelines, policies, and procedures and promptly repair the broken hearing protective devices.

Keywords: employees, factors, noise induced hearing loss, noise exposure

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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

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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

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Authors: Fahad Ibrahim, Raphaël Akamavi

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Bangladesh has encountered several industrial disasters (e.g. fire and building collapse tragedies) leading to the loss of valuable human lives. Irrespective of various institutions’ making effort to improve the safety situation, industry compliance and safety behaviour have not yet been improved. Hence, one question remains, to what extent does the institutional elements efficient enough to make any difference in improving safety behaviours? Thus, this study explores the relationship between institutional perspective and safety performance. Structural equation modelling results, using survey data from 256 RMG workers’ of 128 garments manufacturing factories in Bangladesh, show that institutional facets strongly influence management safety commitment to induce workers participation in safety activities and reduce workplace accident rates. The study also found that by upholding industrial standards and inspecting the safety situations, institutions facets significantly and directly affect workers involvement in safety participations and rate of workplace accidents. Additionally, workers involvement to safety practices significantly predicts the safety environment of the workplace. Subsequently, our findings demonstrate that institutional culture, norms, and regulations enact play an important role in altering management commitment to set-up a safer workplace environment. As a result, when workers’ perceive their management having high level of commitment to safety, they are inspired to be involved more in the safety practices, which significantly alter the workplace safety situation and lessen injury experiences. Due to the fact that institutions have strong influence on management commitment, legislative members should endorse, regulate, and strictly monitor workplace safety laws to be exercised by the factory owners. Further, management should take initiatives for adopting OHS features and conceive strategic directions (i.e., set up safety committees, risk assessments, innovative training) for promoting a positive safety climate to provide a safe workplace environment. Arguably, an inclusive public-private partnership is recommended for ensuring better and safer workplace for RMG workers. However, as our data were under a cross-sectional design; the respondents’ perceptions might get changed over a period of time and hence, a longitudinal study is recommended. Finally, further research is needed to determine the impact of improvement mechanisms on workplace safety performance, such as how workplace design, safety training programs, and institutional enforcement policies protect the well-being of workers.

Keywords: institutional perspective, management commitment, safety participation, work injury, safety performance, occupational health and safety

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Authors: Oluropo Stephen Ilesanmi, Oluwole Ayodele Alejo

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Architectural education, beyond training the students to become architects, impacts in them the appreciation of the responsibilities relating to public health, safety, and welfare. Architecture is no longer a personal philosophical or aesthetic pursuit by individuals, rather, it has to consider everyday needs of the people and use technology to give a liveable environment. In the present age, architectural education must have to grapple with the recent integration of technology, in particular, facilities offered by information and communication technology. Electronic technologies have moved architecture from the drawing board to cyberspace. The world is now a global village in which new information and methods are easily and quickly available to people at different poles of the globe. It is the position of this paper that in order to remain relevant in the ever-competing forces within the building industry, architectural education must show the impetus to continue to draw from technological advancements associated with the use of computers.

Keywords: architecture, education, communication, information, technology

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Authors: Arati S. Kade, Iftikhar Hussain, Somnath Dadas

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The paper studies resilience and uncertainties among nomadic-pastoral communities in India during large events such as pandemics and attempts to understand that with changing times and increased uncertainties, how nomadic communities historically showed their resilience. A review of the literature was performed concerning nomadism and development relations and conflicts by focusing on structural violence on nomadic communities from the caste class and patriarchy as a framework along with the role of the state. Philosophical views on the anti-nomad bias of political theories by Erik Ringmar, along with the decolonial approach by Linda Smith and debrahmanization by Braj Ranjan Mani were used to analyze criminalization of nomads. Data were collected using in-depth telephonic interviews and news reports published during the COVID-19 lockdown in India. Focusing on historical context of current crises, the paper leads to the discussion on how nomadic communities negotiate with the sedentary society during the COVID-19 pandemic. Findings of the current paper approve the hypotheses that the COVID-19 pandemic followed by lockdown deeply impacted the pastoral production system, building on the continued cycle of marginalization by the state and caste society in India, while traditional knowledge stood the test of time. Be it developmental states or pandemics, the nomadic communities have shown their resilience in a number of ways, such as keeping distance from sedentary society, usage of traditional medicine, and relying on traditional leadership.

Keywords: COVID-19, criminalization, India, nomadism, pandemic, pastoralism, resilience, traditional knowledge

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Authors: Ali Farzan

Abstract:

Classification of data objects or patterns is a major part in most of Decision making systems. One of the popular and commonly used classification methods is Decision Tree (DT). It is a hierarchical decision making system by which a binary tree is constructed and starting from root, at each node some of the classes is rejected until reaching the leaf nods. Each leaf node is a representative of one specific class. Finding the splitting criteria in each node for constructing or training the tree is a major problem. Particle Swarm Optimization (PSO) has been adopted as a metaheuristic searching method for finding the best splitting criteria. Result of evaluating the proposed method over benchmark datasets indicates the higher accuracy of the new PSO based decision tree.

Keywords: decision tree, particle swarm optimization, splitting criteria, metaheuristic

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Johnstone Walubengo Wangusi

Abstract:

Geotechnical engineering is a multidisciplinary field that encompasses the study of soil, rock, and groundwater properties and their interactions with civil engineering structures. This research paper provides an in-depth overview of geotechnical engineering, covering its fundamental principles, applications in civil infrastructure projects, and the challenges faced by practitioners in the field. Through a comprehensive examination of soil mechanics, foundation design, slope stability analysis, and geotechnical site investigation techniques, this paper aims to highlight the importance of geotechnical engineering in ensuring the safety, stability, and sustainability of infrastructure development. Additionally, it discusses emerging trends, innovative technologies, and future directions in geotechnical engineering research and practice.

Keywords: sustainable geotechnical engineering solutions, education and training for future generations geotechnical engineers, integration of geotechnical engineering and structural engineering, use of AI in geotechnical engineering modelling

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

Procedia PDF Downloads 102