Search results for: continuous learning

Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: John Peter Dacanay, Edison Ramos, Cristopher James Dicang

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Waste management is a global concern due to increasing waste production from changing consumption patterns and population growth. Proper waste disposal management is a critical aspect of public health and environmental protection. In the healthcare industry, medical waste is generated in large quantities, and if not disposed of properly, it poses a significant threat to human health and the environment. Efficient waste management conserves natural resources and prevents harm to human health, and implementing an effective waste management system can save human lives. The study aimed to assess the level of awareness and practices on waste disposal management, highlighting the understanding of proper disposal, potential hazards, and environmental implications among Medical Technology students. This would help to provide more recommendations for improving waste management practices in healthcare settings as well as for better waste management practices in educational institutions. From the collected data, a female of 21 years of age stands out among the respondents. With the frequency and percentage of medical technology students' knowledge of laboratory waste management being high, it indicates that all respondents demonstrated a solid understanding of proper disposal methods, regulations, risks, and handling procedures related to laboratory waste. That said, the findings emphasize the significance of education and awareness programs in equipping individuals involved in laboratory practices with the necessary knowledge to handle and dispose of hazardous and infectious waste properly. Most respondents demonstrate positive practices or are highly mannered in laboratory waste management, including proper segregation and disposal in designated containers. However, there are concerns about the occasional mixing of waste types, emphasizing the reiteration of proper waste segregation. Students show a strong commitment to using personal protective equipment and promptly cleaning up spills. Some students admit to improper disposal due to rushing, highlighting the importance of time management and safety prioritization. Overall, students follow protocols for hazardous waste disposal, indicating a responsible approach. The school's waste management system is perceived as adequate, but continuous assessment and improvement are necessary. Encouraging reporting of issues and concerns is crucial for ongoing improvement and risk mitigation. The analysis reveals a moderate positive relationship between the respondents' knowledge and practices regarding laboratory waste management. The statistically significant correlation with a p-value of 0.26 (p-value 0.05) suggests that individuals with higher levels of knowledge tend to exhibit better practices. These findings align with previous research emphasizing the pivotal role of knowledge in influencing individuals' behaviors and practices concerning laboratory waste management. When individuals possess a comprehensive understanding of proper procedures, regulations, and potential risks associated with laboratory waste, they are more inclined to adopt appropriate practices. Therefore, fostering knowledge through education and training is essential in promoting responsible and effective waste management in laboratory settings.

Keywords: waste disposal management, knowledge, attitude, practices

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Authors: Saman Kumara, Duminda Guruge, Krishani Jayasinghe

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Introduction: Nutrition strongly influences good health and development in early life. This study, based on a health promotion approach, used a community-based intervention to improve child nutrition. The approach provides the community with control of interventions, thereby building its capacity and empowering individuals and communities. The aim of this research was to reduce stunting, low birth weight and underweight in communities from Anuradhapura District in Sri Lanka, by identifying and addressing the underlying determinants of under-nutrition and strengthening families and communities to address them. Methods: A health promotion intervention was designed and implemented-based on a logical framework developed in collaboration with members of targeted community. Community members’ implements action, so they fully own the process. Members of the community identify and address the most crucial determinants of health including child health and development and monitor the initial results of their action and modify action to optimize outcomes as well as future goals. Group Discussion, group activities, awareness programs, cluster meetings, community tools and sharing success stories were major activities to address determinants. Continuous data collection was planned at different levels. Priority was given to strengthening the ability of families and groups or communities to collect meaningful data and analyze these themselves. Results: Enthusiasm and interest of the mother, happiness of the child/ family, dietary habits, money management, tobacco and alcohol use of fathers, media influences, illnesses in the child or others, hygiene and sanitary practices, community sensitiveness and domestic violence were the major perceived determinants elicited from the study. There were around 1000 well-functioning mothers groups in this district. ‘Happiness calendar’, ‘brain calendar’, ‘money tool’ and ‘stimulation books’ were created by the community members, to address determinants and measure the process. Evaluation of the process has shown positive early results, such as improvement of feeding habits among mothers, innovative ways of providing early stimulation and responsive care, greater involvement of fathers in childcare and responsive feeding. There is a positive movement of communities around child well-being through interactive play areas. Family functioning and community functioning improved. Use of alcohol and tobacco declined. Community money management improved. Underweight was reduced by 40%. Stunting and low birth weight among under-fives also declined within one year. Conclusion: The health promotion intervention was effective in changing the determinants of under-nutrition in early childhood. Addressing the underlying determinants of under-nutrition in early childhood can be recommended for similar contexts.

Keywords: birth-weight, community, determinants, stunting, underweight

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Authors: Sai Sankalp Vemavarapu

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This paper discusses the application of machine learning in the field of transportation engineering for predicting engineering properties of pavement more accurately and efficiently. Predicting the elastic properties aid us in assessing the current road conditions and taking appropriate measures to avoid any inconvenience to commuters. This improves the longevity and sustainability of the pavement layer while reducing its overall life-cycle cost. As an example, we have implemented differential evolution (DE) in the back-calculation of the elastic modulus of multi-layered pavement. The proposed DE global optimization back-calculation approach is integrated with a forward response model. This approach treats back-calculation as a global optimization problem where the cost function to be minimized is defined as the root mean square error in measured and computed deflections. The optimal solution which is elastic modulus, in this case, is searched for in the solution space by the DE algorithm. The best DE parameter combinations and the most optimum value is predicted so that the results are reproducible whenever the need arises. The algorithm’s performance in varied scenarios was analyzed by changing the input parameters. The prediction was well within the permissible error, establishing the supremacy of DE.

Keywords: cost function, differential evolution, falling weight deflectometer, genetic algorithm, global optimization, metaheuristic algorithm, multilayered pavement, pavement condition assessment, pavement layer moduli back calculation

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Authors: M. Ciminello, I. Dimino, S. Ameduri, A. Concilio

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Improving aircraft's efficiency is one of the key elements of Aeronautics. Modern aircraft possess many advanced functions, such as good transportation capability, high Mach number, high flight altitude, and increasing rate of climb. However, no aircraft has a possibility to reach all of this optimized performance in a single airframe configuration. The aircraft aerodynamic efficiency varies considerably depending on the specific mission and on environmental conditions within which the aircraft must operate. Structures that morph their shape in response to their surroundings may at first seem like the stuff of science fiction, but take a look at nature and lots of examples of plants and animals that adapt to their environment would arise. In order to ensure both the controllable and the static robustness of such complex structural systems, a monitoring network is aimed at verifying the effectiveness of the given control commands together with the elastic response. In order to achieve this kind of information, the use of FBG sensors network is, in this project, proposed. The sensor network is able to measure morphing structures shape which may show large, global displacements due to non-standard architectures and materials adopted. Chord -wise variations may allow setting and chasing the best layout as a function of the particular and transforming reference state, always targeting best aerodynamic performance. The reason why an optical sensor solution has been selected is that while keeping a few of the contraindication of the classical systems (like cabling, continuous deployment, and so on), fibre optic sensors may lead to a dramatic reduction of the wires mass and weight thanks to an extreme multiplexing capability. Furthermore, the use of the ‘light’ as ‘information carrier’, permits dealing with nimbler, non-shielded wires, and avoids any kind of interference with the on-board instrumentation. The FBG-based transducers, herein presented, aim at monitoring the actual shape of adaptive trailing edge. Compared to conventional systems, these transducers allow more fail-safe measurements, by taking advantage of a supporting structure, hosting FBG, whose properties may be tailored depending on the architectural requirements and structural constraints, acting as strain modulator. The direct strain may, in fact, be difficult because of the large deformations occurring in morphing elements. A modulation transducer is then necessary to keep the measured strain inside the allowed range. In this application, chord-wise transducer device is a cantilevered beam sliding trough the spars and copying the camber line of the ATE ribs. FBG sensors array position are dimensioned and integrated along the path. A theoretical model describing the system behavior is implemented. To validate the design, experiments are then carried out with the purpose of estimating the functions between rib rotation and measured strain.

Keywords: fiber optic sensor, morphing structures, strain sensor, shape reconstruction

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Modupe Beatrice Adeyinka

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French, as a foreign language in Nigeria, is pronounced to be the second official language and a compulsory subject in the primary school level; hence, colleges of education across the nation are saddled with the responsibility of training teachers for the subject. However, it has been observed that this policy has not been fully implemented, for French teachers in training, do face many challenges, of which translation is chief. In a bid to investigate the major cause of the perceived translation problem, this study examined French translation problems of pre-service teachers in selected colleges of education in the southwest, Nigeria. This study adopted a descriptive survey research design. The simple random sampling technique was used to select four colleges of education in the southwest, where 100 French students were randomly selected by selecting 25 from each school. The pre-service teachers’ French translation problems’ questionnaire (PTFTPQ) was used as an instrument while four research questions were answered and three null hypotheses were tested. Among others, the findings revealed that students do have problems with false friends, though mainly with its interpretation when attempting French-English translation and vice versa; majority of the students make use of French dictionary as a way out and found the material very useful for their understanding of false friends. Teachers were, therefore, urged to attend in-service training where they would be exposed to new and emerging strategies, approaches and methodologies of French language teaching that will make students overcome the challenge of translation in learning French.

Keywords: false friends, French language, pre-service teachers, source language, target language, translation

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Authors: Poteet Frances, Glovinski Ira

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INTRODUCTION: The interoceptive nervous system continuously senses chemical and anatomical changes and helps you recognize, understand, and feel what’s going on inside your body so it is important for energy regulation, memory, affect, and sense of self. A newborn needs predictable routines rather than confusion/chaos to make connections between internal experiences and emotions. AIM: Current legal protocols of removing babies from drug-addicted mothers impact the critical window of bonding. The newborn’s brain is social and the attachment process influences a child’s development which begins immediately after birth through nourishment, comfort, and protection. DESCRIPTION: Our project aims to educate drug-addicted mothers, and medical, nursing, and social work professionals on interoceptive concepts and practices to sustain the mother/newborn relationship. A mother’s interoceptive knowledge predicts children’s emotion regulation and social skills in middle childhood. CONCLUSION: When mothers develop an awareness of their inner bodily sensations, they can self-regulate and be emotionally available to co-regulate (support their newborn during distressing emotions and sensations). Our project has enhanced relationship preservation (mothers understand how their presence matters) and the overall mother/newborn connection.

Keywords: drug-addiction, interoception, legal, mothers, newborn, self-regulation

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

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Authors: Margareta Simina Stanc, Aurel Mototolea, Tiberiu Potarniche

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Sacidava archeological site is located in Dobrudja region, Romania, on a hill on the right bank of the Danube - the Musait point, located at about 5 km north-east from Dunareni village. The place-name documents the fact that, prior to the Roman conquest, in the area, there was a Getic settlement. The location of the Sacidava was made possible by corroborating the data provided by the ancient sources with the epigraphic documents (the milial pillar during the time of Emperor Decius). The tegular findings attest that an infantry unit, cohors I Cilicum milliaria equitata, as well as detachments from Legio V Macedonica and Legio XI Claudia, were confined to Sacidava. During the period of the Dominion, the garrison of the fortification is the host of a cavalry unit: cuneus equitum scutariorum. In the immediate vicinity to the Roman fortress, to the east, were identified two other fortifications: a Getic settlement (4th-1st century B.C.) and an Early Medieval settlement (9th-10th century A.C.). The archaeological material recovered during the research is represented by ceramic forms such as amphoras, jugs, pots, cups, plates, to which are added oil lamps, some of them typologically new at the time of discovery. Local ceramic shapes were also founded, worked by hand or by wheel, considered un-Romanized or in the course of Romanization. During the time of the Principality, Sacidava it represented an important military outpost serving mainly the city of Tropaeum Traiani, controlling also the supply and transport on the Danube limes in the Moesic sector. This role will determine the development of the fortress and the appearance of extramuros civil structures, thus becoming an important landmark during the 5th-6th centuries A.C., becoming a representation of power of the Roman empire in an area of continuous conflict. During recent archaeological researches, faunal remains were recovered, and their analysis allowed to estimate the animal resources and subsistence practices (animal husbandry, hunting, fishing) in the settlement. The methodology was specific to archaeozoology, mainly consisting of anatomical, taxonomical, and taphonomical identifications, recording, and quantification of the data. The remains of domestic mammals have the highest proportion indicating the importance of animal husbandry; the predominant species are Bos taurus, Ovis aries/Capra hircus, and Sus domesticus. Fishing and hunting were of secondary importance in the subsistence economy of the community. Wild boar and the red deer were the most frequently hunted species. Just a few fish bones were recovered. Thus, the ancient city of Sacidava is proving to be an important element of cultural heritage of the south-eastern part of Romania, for whose conservation and enhancement efforts must be made, especially by landscape reconstruction.

Keywords: archaeozoology, landscape reconstruction, limes, military outpost

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Authors: Andreas Stollwitzer, Lara Bettinelli, Josef Fink

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The expansion of the high-speed rail network over the past decades has resulted in new challenges for engineers, including traffic-induced resonance vibrations of railway bridges. Excessive resonance-induced speed-dependent accelerations of railway bridges during high-speed traffic can lead to negative consequences such as fatigue symptoms, distortion of the track, destabilisation of the ballast bed, and potentially even derailment. A realistic prognosis of bridge vibrations during high-speed traffic must not only rely on the right choice of an adequate calculation model for both bridge and train but first and foremost on the use of dynamic model parameters which reflect reality appropriately. However, comparisons between measured and calculated bridge vibrations are often characterised by considerable discrepancies, whereas dynamic calculations overestimate the actual responses and therefore lead to uneconomical results. This gap between measurement and calculation constitutes a complex research issue and can be traced to several causes. One major cause is found in the dynamic properties of the ballasted track, more specifically in the persisting, substantial uncertainties regarding the consideration of the ballasted track (mechanical model and input parameters) in dynamic calculations. Furthermore, the discrepancy is particularly pronounced concerning the damping values of the bridge, as conservative values have to be used in the calculations due to normative specifications and lack of knowledge. By using a large-scale test facility, the analysis of the dynamic behaviour of ballasted track has been a major research topic at the Institute of Structural Engineering/Steel Construction at TU Wien in recent years. This highly specialised test facility is designed for isolated research of the ballasted track's dynamic stiffness and damping properties – independent of the bearing structure. Several mechanical models for the ballasted track consisting of one or more continuous spring-damper elements were developed based on the knowledge gained. These mechanical models can subsequently be integrated into bridge models for dynamic calculations. Furthermore, based on measurements at the test facility, model-dependent stiffness and damping parameters were determined for these mechanical models. As a result, realistic mechanical models of the railway bridge with different levels of detail and sufficiently precise characteristic values are available for bridge engineers. Besides that, this contribution also presents another practical application of such a bridge model: Based on the bridge model, determination equations for the damping factor (as Lehr's damping factor) can be derived. This approach constitutes a first-time method that makes the damping factor of a railway bridge calculable. A comparison of this mathematical approach with measured dynamic parameters of existing railway bridges illustrates, on the one hand, the apparent deviation between normatively prescribed and in-situ measured damping factors. On the other hand, it is also shown that a new approach, which makes it possible to calculate the damping factor, provides results that are close to reality and thus raises potentials for minimising the discrepancy between measurement and calculation.

Keywords: ballasted track, bridge dynamics, damping, model design, railway bridges

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Authors: Shehroz Mukhtar, Maqsood Ahmed, Abdullah Mukhtar, Choudhry Shahid, Waqar Javaid

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Code switching is a common phenomenon, generally observed in multilingual communities across the globe. A critical look at code switching literature reveals that mostly code switching has been studied in classroom in learning and teaching context while code switching outside classroom in settings such as café, hostel and so on have been the least explored areas. Current research investigated the reasons for code switching in the interactive practices of students and their perceptions regarding the same outside the classroom settings. This paper is the study of the common practice that prevails in the Universities of Sialkot that bilinguals mix two languages when they speak in different class room situations. In Pakistani classrooms where Multilingual are in abundance i.e. they can speak two or more than two languages at the same time, the code switching or language combination is very common. The teachers of Sialkot switch from one language to another consciously or unconsciously while teaching English in the class rooms. This phenomenon has not been explored in the Sialkot’s teaching context. In Sialkot private educational institutes does not encourage code-switching whereas the public or government institutes use it frequently. The crux of this research is to investigate and identify the importance of code switching by taking its users in consideration. Survey research method and survey questionnaire will be used to get exact data from teachers and students. We will try to highlight the functions and importance of code switching in foreign language classrooms of Sialkot and will explore why this trend is emerging in Sialkot.

Keywords: code switching, bilingual context, L1, L2

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Authors: Rashmi Gupta

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Rewarding stimuli capture attention involuntarily as a result of an association process that develops quickly during value learning, referred to as the reward or value-driven attentional capture. It is essential to compare reward with punishment processing to get a full picture of value-based modulation in visual attention processing. Hence, the present study manipulated both valence/value (reward as well as punishment) and motivational salience (probability of an outcome: high vs. low) together. Series of experiments were conducted, and there were two phases in each experiment. In phase 1, participants were required to learn to associate specific face stimuli with a high or low probability of winning or losing points. In the second phase, these conditioned stimuli then served as a distractor or prime in a speeded letter search task. Faces with high versus low outcome probability, regardless of valence, slowed the search for targets (specifically the left visual field target) and suggesting that the costs to performance on non-emotional cognitive tasks were only driven by motivational salience (high vs. loss) associated with the stimuli rather than the valence (gain vs. loss). It also suggests that the processing of motivationally salient stimuli is right-hemisphere biased. Together, results of these studies strengthen the notion that our visual attention system is more sensitive to affected by motivational saliency rather than valence, which termed here as motivational-driven attentional capture.

Keywords: attention, distractors, motivational salience, valence

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Authors: Baohua Yu

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In line with wider tends in the expansion of international student mobility, the number of international higher degree research students has grown at a significant rate in recent years. In particular, Australia has become a hub for attracting international higher degree research students from around the world. However, research has identified that international higher degree research students often encounter a wide range of academic and socio-cultural challenges in adapting to their new environment. Moreover, this can have a significant bearing on their levels of satisfaction with their studies. This paper outlines the findings of a mixed method study exploring the experiences and perceptions of international higher degree research students in Australia. Findings revealed that IRHD students’ overall and academic satisfaction in Australia were highly related to each other, and they were strongly influenced by their learning and research, moderately influenced by co-national support and intercultural contact ability. Socio-cultural satisfaction seemed to belong to a different domain from academic satisfaction because it was explained by a different set of variables such as living and adaptation and intercultural contact ability. In addition, the most important issues in terms of satisfaction were not directly related to academic studies. Instead, factors such as integration into the community, interacting with other students, relationships with supervisors, and the provision of adequate desk space were often given the greatest weight. Implications for how university policy can better support international doctoral students are discussed.

Keywords: international higher degree research students, academic adaptation, socio-cultural adaptation, student satisfaction

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Authors: Sachin Jain, Daniel Perez-Astudillo, Dunia A. Bachour, Antonio P. Sanfilippo

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The future of solar energy in Qatar is evolving steadily. Hence, high-quality spatial solar radiation data is of the uttermost requirement for any planning and commissioning of solar technology. Generally, two types of solar radiation data are available: satellite data and ground observations. Satellite solar radiation data is developed by the physical and statistical model. Ground data is collected by solar radiation measurement stations. The ground data is of high quality. However, they are limited to distributed point locations with the high cost of installation and maintenance for the ground stations. On the other hand, satellite solar radiation data is continuous and available throughout geographical locations, but they are relatively less accurate than ground data. To utilize the advantage of both data, a product has been developed here which provides spatial continuity and higher accuracy than any of the data alone. The popular satellite databases: National Solar radiation Data Base, NSRDB (PSM V3 model, spatial resolution: 4 km) is chosen here for merging with ground-measured solar radiation measurement in Qatar. The spatial distribution of ground solar radiation measurement stations is comprehensive in Qatar, with a network of 13 ground stations. The monthly average of the daily total Global Horizontal Irradiation (GHI) component from ground and satellite data is used for error analysis. The normalized root means square error (NRMSE) values of 3.31%, 6.53%, and 6.63% for October, November, and December 2019 were observed respectively when comparing in-situ and NSRDB data. The method is based on the Empirical Bayesian Kriging Regression Prediction model available in ArcGIS, ESRI. The workflow of the algorithm is based on the combination of regression and kriging methods. A regression model (OLS, ordinary least square) is fitted between the ground and NSBRD data points. A semi-variogram is fitted into the experimental semi-variogram obtained from the residuals. The kriging residuals obtained after fitting the semi-variogram model were added to NSRBD data predicted values obtained from the regression model to obtain the final predicted values. The NRMSE values obtained after merging are respectively 1.84%, 1.28%, and 1.81% for October, November, and December 2019. One more explanatory variable, that is the ground elevation, has been incorporated in the regression and kriging methods to reduce the error and to provide higher spatial resolution (30 m). The final GHI maps have been created after merging, and NRMSE values of 1.24%, 1.28%, and 1.28% have been observed for October, November, and December 2019, respectively. The proposed merging method has proven as a highly accurate method. An additional method is also proposed here to generate calibrated maps by using regression and kriging model and further to use the calibrated model to generate solar radiation maps from the explanatory variable only when not enough historical ground data is available for long-term analysis. The NRMSE values obtained after the comparison of the calibrated maps with ground data are 5.60% and 5.31% for November and December 2019 month respectively.

Keywords: global horizontal irradiation, GIS, empirical bayesian kriging regression prediction, NSRDB

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Authors: Renee Moten

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Introduction: Knee pain becomes chronic because the therapy used focuses only on the symptoms of knee pain and not the causes of knee pain. Preventing knee injuries is not in the toolbox of the traditional practitioner. This research was done to show that we must reduce the inflammation (holistically), reduce the swelling and regain flexibility before considering any type of exercise. This method of performing the correct exercise stops the bowing of the knee, corrects the walking gait, and starts to relieve knee, hip, back, and shoulder pain. Method: The holistic method that is used to heal knees is called the Knee Pain Recipe. It’s a six step system that only uses alternative medicine methods to reduce, relieve and restore knee joint mobility. The system is low cost, with no hospital bills, no physical therapy, and no painkillers that can cause damage to the kidneys and liver. This method has been tested on 200 women with knee, back, hip, and shoulder pain. Results: All 200 women reduce their knee pain by 50%, some by as much as 90%. Learning about ankle and foot flexibility, along with understanding the kinetic chain, helps improve the walking gait, which takes the pressure off the knee, hip and back. The knee pain recipe also has helped to reduce the need for a cortisone injection, stem cell procedures, to take painkillers, and surgeries. What has also been noted in the research was that if the women's knees were too far gone, the Knee Pain Recipe helped prepare the women for knee replacement surgery. Conclusion: It is believed that the Knee Pain Recipe, when performed by men and women from around the world, will give them a holistic alternative to drugs, injections, and surgeries.

Keywords: knee, surgery, healing, holistic

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Authors: Javed Iqbal

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The growing need for energy by the human society and depletion of conventional energy sources demands a renewable, safe, infinite, low-cost and omnipresent energy source. One of the most suitable ways to solve the foreseeable world’s energy crisis is to use the power of the sun. Photovoltaic devices are especially of wide interest as they can convert solar energy to electricity. Recently the best performing solar cells are silicon-based cells. However, silicon cells are expensive, rigid in structure and have a large timeline for the payback of cost and electricity. Organic photovoltaic cells are cheap, flexible and can be manufactured in a continuous process. Therefore, organic photovoltaic cells are an extremely favorable replacement. Organic photovoltaic cells utilize sunlight as energy and convert it into electricity through the use of conductive polymers/ small molecules to separate electrons and electron holes. A major challenge for these new organic photovoltaic cells is the efficiency, which is low compared with the traditional silicon solar cells. To overcome this challenge, usually two straightforward strategies have been considered: (1) reducing the band-gap of molecular donors to broaden the absorption range, which results in higher short circuit current density (JSC) of devices, and (2) lowering the highest occupied molecular orbital (HOMO) energy of molecular donors so as to increase the open-circuit voltage (VOC) of applications devices.8 Keeping in mind the cost of chemicals it is hard to try many materials on test basis. The best way is to find the suitable material in the bulk. For this purpose, we use computational approach to design molecules based on our organic chemistry knowledge and determine their physical and electronic properties. In this study, we did DFT calculations with different options to get high open circuit voltage and after getting suitable data from calculation we finally did synthesis of a novel D–π–A–π–D type low band-gap small molecular donor material (ZOPTAN-TPA). The Aarylene vinylene based bis(arylhalide) unit containing a cyanostilbene unit acts as a low-band- gap electron-accepting block, and is coupled with triphenylamine as electron-donating blocks groups. The motivation for choosing triphenylamine (TPA) as capped donor was attributed to its important role in stabilizing the separated hole from an exciton and thus improving the hole-transporting properties of the hole carrier.3 A π-bridge (thiophene) is inserted between the donor and acceptor unit to reduce the steric hindrance between the donor and acceptor units and to improve the planarity of the molecule. The ZOPTAN-TPA molecule features a low HOMO level of 5.2 eV and an optical energy gap of 2.1 eV. Champion OSCs based on a solution-processed and non-annealed active-material blend of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) and ZOPTAN-TPA in a mass ratio of 2:1 exhibits a power conversion efficiency of 1.9 % and a high open-circuit voltage of over 1.0 V.

Keywords: high open circuit voltage, donor, triphenylamine, organic solar cells

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Authors: Sebastian Hiergeist

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It is a common view that Unmanned Aerial Vehicles (UAV) tend to migrate into the civil airspace. This trend is challenging UAV manufacturer in plenty ways, as there come up a lot of new requirements and functional aspects. On the higher application levels, this might be collision detection and avoidance and similar features, whereas all these functions only act as input for the flight control components of the aircraft. The flight control computer (FCC) is the central component when it comes up to ensure a continuous safe flight and landing. As these systems are flight critical, they have to be built up redundantly to be able to provide a Fail-Operational behavior. Recent architectural approaches of FCCs used in UAV systems are often based on very simple microprocessors in combination with proprietary Application-Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) extensions implementing the whole redundancy functionality. In the future, such simple microprocessors may not be available anymore as they are more and more replaced by higher sophisticated System on Chip (SoC). As the avionic industry cannot provide enough market power to significantly influence the development of new semiconductor products, the use of solutions from foreign markets is almost inevitable. Products stemming from the industrial market developed according to IEC 61508, or automotive SoCs, according to ISO 26262, can be seen as candidates as they have been developed for similar environments. Current available SoC from the industrial or automotive sector provides quite a broad selection of interfaces like, i.e., Ethernet, SPI or FlexRay, that might come into account for the implementation of a redundancy network. In this context, possible network architectures shall be investigated which could be established by using the interfaces stated above. Of importance here is the avoidance of any single point of failures, as well as a proper segregation in distinct fault containment regions. The performed analysis is supported by the use of guidelines, published by the aviation authorities (FAA and EASA), on the reliability of data networks. The main focus clearly lies on the reachable level of safety, but also other aspects like performance and determinism play an important role and are considered in the research. Due to the further increase in design complexity of recent and future SoCs, also the risk of design errors, which might lead to common mode faults, increases. Thus in the context of this work also the aspect of dissimilarity will be considered to limit the effect of design errors. To achieve this, the work is limited to broadly available interfaces available in products from the most common silicon manufacturer. The resulting work shall support the design of future UAV FCCs by giving a guideline on building up a redundancy network between SoCs, solely using on board interfaces. Therefore the author will provide a detailed usability analysis on available interfaces provided by recent SoC solutions, suggestions on possible redundancy architectures based on these interfaces and an assessment of the most relevant characteristics of the suggested network architectures, like e.g. safety or performance.

Keywords: redundancy, System-on-Chip, UAV, flight control computer (FCC)

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Authors: Carmen Avilés Palacios, Camilo Muñoz Arenas, Joaquín García Alfonso, Jesús González Arteaga, Alberto Alcalde Calonge

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There is a need for review of the consumption and production models of industrialized states in accordance with the Paris Agreement and the Sustainable Development Goals (1) (OECD, 2016). This constitutes the basis of the bioeconomy (2) that is focused on striking a balance between economic development, social development and environmental protection. Bioeconomy promotes the adequate use and consumption of renewable natural resources (3) and involves developing new products and services adapted to the principles of circular economy: more sustainable (reusable, biodegradable, renewable and recyclable) and with a lower carbon footprint (4). In this context, Urban Forest Innovation Lab (UFIL) grows, an Urban Laboratory for experimentation focused on promoting entrepreneurship in forest bioeconomy (www.uiacuenca.es). UFIL generates local wellness taking sustainable advantage of an endogenous asset, forests. UFIL boosts forest bioeconomy opening its doors of knowledge to pioneers in this field, giving the opportunity to be an active part of a change in the way of understanding the exploitation of natural resources, discovering business, learning strategies and techniques and incubating business ideas So far now, 100 entrepreneurs are incubating their nearly 30 new business plans. UFIL has promoted an ecosystem to connect the rural-urban world that promotes sustainable rural development around the forest.

Keywords: bioeconomy, forestry, innovation, entrepreneurship

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology expansion, synthetic dataset, transformer fine-tuning, concept extraction, DOLCE, BERT, taxonomy, LLM, NER

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Authors: Fabianna Bacil, Zenathan Hasannundin, Clovis Freire

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The green transition opens green windows of opportunity – temporary moments in which there are lower barriers and shorter learning periods for developing countries to enter emerging technologies and catch-up. However, taking advantage of these windows requires capabilities in national sectoral systems to adopt and develop technologies linked to green sectors as well as strong responses to build the required knowledge, skills, and infrastructure and foster the growth of targeted sectors. This paper uses UNCTAD’s frontier technology readiness index to analyse the current position of Latin America and the Caribbean to use, adopt, and adapt frontier technologies, examining the preconditions in the region to take up windows of opportunity that arise with the green transition. The index highlights the inequality across countries in the region, as well as gaps in capabilities dimensions, especially in terms of R&D. Moving to responses, it highlights industrial policies implemented to foster the growth of green technologies, emphasising the essential role played by the state to build and strengthen capabilities and provide infant industry protection that enables the growth of these sectors. Overall, while there are exceptions, especially in the Brazilian case, countries in Latin America and the Caribbean should focus on strengthening their capabilities to be better positioned, especially in terms of knowledge creation, infrastructure, and financing availability.

Keywords: Green technologies, Industrial policy, Latin America, windows of opportunity

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Authors: Hsin-Yi Lo, Huang-Ju Jiun, Yu-Chiao Chu

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Hemodynamic monitoring is an important in the intensive care unit. Advances in medical technology in recent years, more diversification of intensive care equipment, there are many kinds of instruments available for monitoring of hemodynamics, Edwards Lifesciences Hemodynamic Monitoring (FloTrac) is one of them. The recent medical safety incidents in parameters were changed, nurses have not to notify doctor in time, therefore, it is hoped to analyze the current problems and find effective improvement strategies. In August 2021, the survey found that only 74.0% of FloTrac correctness of operation, reasons include lack of education, the operation manual is difficulty read, lack of audit mechanism, nurse doesn't know those numerical changes need to notify doctor, work busy omission, unfamiliar with operation and have many nursing records then omissions. Improvement methods include planning professional nurse education, formulate the secret arts of FloTrac, enacting an audit mechanism, establish FloTrac action learning, make「follow the sun」care map, hold simulated training and establish monitoring data automatically upload nursing records. After improvement, FloTrac correctness of operation increased to 98.8%. The results are good, implement to the ICU of the hospital.

Keywords: hemodynamic monitoring, edwards lifesciences hemodynamic monitoring, multiple strategies, intensive care

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Shital Suresh Borse, Vijayalaxmi Kadroli

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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.

Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN

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Authors: B. Likar, K. Širok

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The paper presents a new method for efficient innovation process management. Even though the innovation management methods, tools and knowledge are well established and documented in literature, most of the companies still do not manage it efficiently. Especially in SMEs the front end of innovation - problem identification, idea creation and selection - is often not optimally performed. Our eMIPS methodology represents a sort of "umbrella methodology"- a well-defined set of procedures, which can be dynamically adapted to the concrete case in a company. In daily practice, various methods (e.g. for problem identification and idea creation) can be applied, depending on the company's needs. It is based on the proactive involvement of the company's employees supported by the appropriate methodology and external experts. The presented phases are performed via a mixture of face-to-face activities (workshops) and online (eLearning) activities taking place in eLearning Moodle environment and using other e-communication channels. One part of the outcomes is an identified set of opportunities and concrete solutions ready for implementation. The other also very important result is connected to innovation competences for the participating employees related with concrete tools and methods for idea management. In addition, the employees get a strong experience for dynamic, efficient and solution oriented managing of the invention process. The eMIPS also represents a way of establishing or improving the innovation culture in the organization. The first results in a pilot company showed excellent results regarding the motivation of participants and also as to the results achieved.

Keywords: creativity, distance learning, front end, innovation, problem

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Authors: Shehroz Mukhtar, Maqsood Ahmed, Abdullah Mukhtar, Choudhry Shahid, Waqar Javaid

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Code switching is a common phenomenon, generally observed in multilingual communities across the globe. A critical look at code-switching literature reveals that mostly code-switching has been studied in the classrooms in learning and teaching contexts, while code-switching outside the classroom in settings such as café, hostels and so on has been the least explored areas. The current research investigated the reasons for code-switching in the interactive practices of students and their perceptions regarding the same outside the classroom settings. This paper is the study of the common practice that prevails in the Universities of Sialkot that bilinguals mix two languages when they speak in different classroom situations. In Pakistani classrooms where Multilingual is in abundance, i.e. they can speak two or more two languages at the same time, code-switching or language combination is very common. The teachers of Sialkot switch from one language to another consciously or unconsciously while teaching English in the classrooms. This phenomenon has not been explored in Sialkot’s teaching context. In Sialkot, private educational institutes do not encourage code-switching, whereas public or government institutes use it frequently. The crux of this research is to investigate and identify the importance of code-switching by taking its users into consideration. The survey research method and survey questionnaire will be used to get exact data from teachers and students. We will try to highlight the functions and importance of code switching in foreign language classrooms of Sialkot and will explore why this trend is emerging in Sialkot.

Keywords: code switching, foreign language classrooms, bilingual context, use of L1, importance of L2.

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Authors: Daodu Joshua Rotimi

Abstract:

This study investigated the Efficacy of Self-Assessment Metacognitive Strategy on Academic performance in Energy Concepts among Upper Basic Science Students in Ankpa, Kogi State, Nigeria. The research design adopted for the study was a Quasi-experimental control group design which employed a pretest, posttest of the experimental and control groups. The population of the study consisted of one hundred and twenty-four (124) JSSII Students; sixty-five (65) for the experimental group and (59) for the control group. The instrument used for the study was the Energy Concept Performance Test (ECPT), with a reliability coefficient of 0.80. Two research questions were answered using descriptive statistics of mean and standard deviation, while two hypotheses were tested using a t-test at P≤0.05 level of significance. The findings of the study revealed that the use of the Self-Assessment Metacognitive Strategy has a positive effect on students’ performance in energy concepts among upper Basic Science Students leading to high academic performance; also, there is no significant difference in the mean Academic Performance scores between Male and Female students taught Energy Concept using Self-Assessment Metacognitive Strategy. Based on the research findings, recommendations were made, which include that Secondary school teachers should be encouraged the use Self-Assessment Metacognitive strategy so as to make the learning process attractive, interactive and enriching to the learners.

Keywords: metacognition, self-assessment, performance, efficacy

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Sukrita Mukherjee, Anindita Chaudhuri

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Soft skills are a crucial aspect for employees, and these skills are not confined to any particular field rather, it guarantees further career growth and job opportunities for employees who are seeking growth. Soft skills are also regarded as personality-specific skills that are observable and are qualitative in nature, which determines an employee’s strengths as a leader. When an employee intends to hold his job, then the person must make effective use of his personal resources, that, in turn, impacts his employability in a positive manner. An employee at his workplace is expected to make effective use of his personal resources. The resources that are to be used by the employee are generally of two types. First type of resources are occupation related, which is related with the educational background of the employee, and the second type of resources are the psychological resources of the employee, such as self-knowledge, career orientation awareness, sense of purpose and emotional literacy, that are considered crucial for an employee in his workplace. The present study is a qualitative study which includes 10 individuals working in IT Sector and Service Industry, respectively. For IT sector, graduate people are considered, and for the Service Industry, individuals who have done a Professional course in order to get into the industry are considered. The emerging themes from the findings after thematic analysis reveal that different aspect of Soft skills such as communication, decision making, constant learning, keeping oneself updated with the latest technological advancement, emotional intelligence are some of the important factors that helps an employee not only to sustain his job, but also grow in his workplace.

Keywords: employabiliy, soft skils, employees, resources, workplace

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Authors: Sukran Acikel, Mehmet Ekmekci, Otgonbayar Namkhai

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Lignite coal fields in western Turkey generally occurs in tensional Neogene basins bordered by major faults. Karacahisar coal field in Mugla province of western Turkey is a large Neogene basin filled with alternation of silisic and calcerous layers. The basement of the basin is composed of mainly karstified carbonate rocks of Mesozoic and schists of Paleozoic age. The basement rocks are exposed at highlands surrounding the basin. The basin fill deposits forms shallow, low yield and local aquifers whereas karstic carbonate rock masses forms the major aquifer in the region. The karstic aquifer discharges through a spring zone issuing at intersection of two major faults. Municipal water demand in Bodrum city, a touristic attraction area is almost totally supplied by boreholes tapping the karstic aquifer. A well field has been constructed on the eastern edge of the coal basin, which forms a ridge separating two Neogene basins. A major concern was raised about the plausible impact of mining activities on groundwater system in general and on water supply well field in particular. The hydrogeological studies carried out in the area revealed that the coal seam is located below the groundwater level. Mining operations will be affected by groundwater inflow to the pits, which will require dewatering measures. Dewatering activities in mine sites have two-sided effects: a) lowers the groundwater level at and around the pit for a safe and effective mining operation, b) continuous dewatering causes expansion of cone of depression to reach a spring, stream and/or well being utilized by local people, capturing their water. Plausible effect of mining operations on the flow of the spring zone was another issue of concern. Therefore, a detailed representative hydrogeological conceptual model of the site was developed on the basis of available data and field work. According to the hydrogeological conceptual model, dewatering of Neogene layers will not hydraulically affect the water supply wells, however, the ultimate perimeter of the open pit will expand to intersect the well field. According to the conceptual model, the coal seam is separated from the bottom by a thick impervious clay layer sitting on the carbonate basement. Therefore, the hydrostratigraphy does not allow a hydraulic interaction between the mine pit and the karstic carbonate rock aquifer. However, the structural setting in the basin suggests that deep faults intersecting the basement and the Neogene sequence will most probably carry the deep groundwater up to a level above the bottom of the pit. This will require taking necessary measure to lower the piezometric level of the carbonate rock aquifer along the faults. Dewatering the carbonate rock aquifer will reduce the flow to the spring zone. All findings were put together to recommend a strategy for safe and effective mining operation.

Keywords: conceptual model, dewatering, groundwater, mining operation

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