Search results for: training courses

Authors: Inyene Nathaniel Nkanta

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The present economic situation in Nigeria, with an increase in inflation rate due to the fall of crude oil prices and post covid-19 crisis, has increased the level of poverty and suffering in Nigeria, particularly the women. Against that backdrop, this research project is initiated to explore ways to empower women through entrepreneurship education and training to ameliorate the poverty level amongst women in Nigeria. A qualitative approach to data collection will be applied in this study and to test the assertions of this research project empirically, this research adopts a case study research method as this will enable me to obtain and probe ways women can be empowered through semi-structured interviews and focus groups. The result of this research project will provide an original perspective on human capital development, most importantly, the need for entrepreneurial education and entrepreneurial literature and practice.

Keywords: women, Nigeria, entrepreneurship education, Economic development, human capital

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Authors: A. Delimitsou, C. Gouedard, E. Konstanta, A. Koletis, S. Patera, E. Manou, K. Spaho, S. Murray

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Background: There remains a lack of International Standard Control Reference materials for Next Generation Sequencing-based approaches or device calibration. We have designed and validated dsDNA biomimetic reference materials for targeted such approaches incorporating proprietary motifs (patent pending) for device/test calibration. They enable internal single-sample calibration, alleviating sample comparisons to pooled historical population-based data assembly or statistical modelling approaches. We have validated such an approach for BRCA Copy Number Variation analytics using iQRS™-CNVSUITE versus Mixed Ligation-dependent Probe Amplification. Methods: Standard BRCA Copy Number Variation analysis was compared between mixed ligation-dependent probe amplification and next generation sequencing using a cohort of 198 breast/ovarian cancer patients. Next generation sequencing based copy number variation analysis of samples spiked with iQRS™ dsDNA biomimetics were analysed using proprietary CNVSUITE software. Mixed ligation-dependent probe amplification analyses were performed on an ABI-3130 Sequencer and analysed with Coffalyser software. Results: Concordance of BRCA – copy number variation events for mixed ligation-dependent probe amplification and CNVSUITE indicated an overall sensitivity of 99.88% and specificity of 100% for iQRS™-CNVSUITE. The negative predictive value of iQRS-CNVSUITE™ for BRCA was 100%, allowing for accurate exclusion of any event. The positive predictive value was 99.88%, with no discrepancy between mixed ligation-dependent probe amplification and iQRS™-CNVSUITE. For device calibration purposes, precision was 100%, spiking of patient DNA demonstrated linearity to 1% (±2.5%) and range from 100 copies. Traditional training was supplemented by predefining the calibrator to sample cut-off (lock-down) for amplicon gain or loss based upon a relative ratio threshold, following training of iQRS™-CNVSUITE using spiked iQRS™ calibrator and control mocks. BRCA copy number variation analysis using iQRS™-CNVSUITE™ was successfully validated and ISO15189 accredited and now enters CE-IVD performance evaluation. Conclusions: The inclusion of a reference control competitor (iQRS™ dsDNA mimetic) to next generation sequencing-based sequencing offers a more robust sample-independent approach for the assessment of copy number variation events compared to mixed ligation-dependent probe amplification. The approach simplifies data analyses, improves independent sample data analyses, and allows for direct comparison to an internal reference control for sample-specific quantification. Our iQRS™ biomimetic reference materials allow for single sample copy number variation analytics and further decentralisation of diagnostics to single patient sample assessment.

Keywords: validation, diagnostics, oncology, copy number variation, reference material, calibration

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Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

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Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

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Authors: Reza Rezaeipour Honarmandzad

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In this paper we propose an ANN for detection and localization of fatigue damage in aircraft structures. We used network of piezoelectric transducers for Lamb-wave measurements in order to calculate damage indices. Data gathered by the sensors was given to neural network classifier. A set of neural network electors of different architecture cooperates to achieve consensus concerning the state of each monitored path. Sensed signal variations in the ROI, detected by the networks at each path, were used to assess the state of the structure as well as to localize detected damage and to filter out ambient changes. The classifier has been extensively tested on large data sets acquired in the tests of specimens with artificially introduced notches as well as the results of numerous fatigue experiments. Effect of the classifier structure and test data used for training on the results was evaluated.

Keywords: ANN, fatigue damage, aircraft structures, piezoelectric transducers, lamb-wave measurements

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Authors: Nighat Ayub, Masood Ahmad

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In this paper, a new voting system is developed and its usability is evaluated. The main feature of this system is the biometric verification of the voter and then a few easy steps to cast a vote. As compared to existing systems available, e.g dual vote, the new system requires no training in advance. The security is achieved via multiple key concept (another part of this project). More than 100 student voters were participated in the election from University of Malakanad, Chakdara, PK. To achieve the reliability, the voters cast their votes in two ways, i.e. paper based and electronic based voting using our new system. The results of paper based and electronic voting system are compared and it is concluded that the voters cast their votes for the intended candidates on the electronic voting system. The voters were requested to fill a questionnaire and the results of the questionnaire are carefully analyzed. The results show that the new system proposed in this paper is more secure and usable than other systems.

Keywords: e-voting, security, usability, authentication

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Authors: Yi-Jiun Chou, Ying-Hsuan Li, Yi-Jung Liu, Hsin-Yu Chiang, Hsuan-Ching Wang

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Background: Patients received therapeutic hypothermia (TH) after resuscitation from cardiac arrest are more dependent on continue and intensive nursing care. It involves many difficult steps, especially achieving target body temperature. To our best knowledge, there is no consensus or recommended standards on nursing practice of TH. Aim: The aim of this study is to increase the completion rate of nursing care at therapeutic hypothermia. Methods: We took five measures: (1) Amendment of nursing standards of therapeutic hypothermia; (2) Amendment of TH checklist items to nursing records; (3) Establishment of monitor procedure; (4) Design each period of TH care reminder cards; (5) Providing in-service training sections of TH for ICU nursing staff. Outcomes: The completion rate of nursing care at therapeutic hypothermia increased from 78.1% to 89.3%. Conclusion: The project team not only increased the completion rate but also improved patient safety and quality of care.

Keywords: therapeutic hypothermia, nursing, critical care, quality of care

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Authors: Pallavi Malhotra

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This paper examines the importance of ethics in cloud computing. In the modern society, cloud computing is offering individuals and businesses an unlimited space for storing and processing data or information. Most of the data and information stored in the cloud by various users such as banks, doctors, architects, engineers, lawyers, consulting firms, and financial institutions among others require a high level of confidentiality and safeguard. Cloud computing offers centralized storage and processing of data, and this has immensely contributed to the growth of businesses and improved sharing of information over the internet. However, the accessibility and management of data and servers by a third party raise concerns regarding the privacy of clients’ information and the possible manipulations of the data by third parties. This document suggests the approaches various stakeholders should take to address various ethical issues involving cloud-computing services. Ethical education and training is key to all stakeholders involved in the handling of data and information stored or being processed in the cloud.

Keywords: IT ethics, cloud computing technology, cloud privacy and security, ethical education

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Ashwani Kumar

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In human beings, eyes play a vital role. A very less research has been done for rehabilitation of blindness for the blind people. This paper discusses the work that helps blind people for recognizing the basic shapes of the objects like circle, square, triangle, horizontal lines, vertical lines, diagonal lines and the wave forms like sinusoidal, square, triangular etc. This is largely achieved by using a digital camera, which is used to capture the visual information present in front of the blind person and a software program, which achieves the image processing operations, and finally the processed image is converted into sound. After the sound generation process, the generated sound is fed to the blind person through headphones for visualizing the imaginary image of the object. For visualizing the imaginary image of the object, it needs to train the blind person. Various training process methods had been applied for recognizing the object.

Keywords: image processing, pixel, pitch, loudness, sound generation, edge detection, brightness

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Authors: E. Hronyecz

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Guaranteeing the independence of the V4 Member States, the protection of their national values and their citizens, and the security of the Central and Eastern European region requires the development of military capabilities in terms of the capabilities of nations. As a result, European countries have begun developing capabilities and forces, within which nations are seeking to strengthen the capabilities of their armies and make their interoperability more effective. One aspect of this is the upgrading of military equipment, personnel equipment, and other human resources. Based on the author's preliminary researches - analyzing the scientific literature, the relevant statistical data and conducting of professional consultations with the experts of the research field – it can clearly claimed for all four states of Visegrad Group that a change of direction in the field of defense has been noticeable since the second half of the last decade. Collective defense came to the forefront again; the military training, professionalism, and radical modernization of technical equipment becoming crucial.

Keywords: armed forces, cooperation, development, Visegrad Group

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Authors: Laidi Maamar, Hanini Salah

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The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

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Authors: Yingxu Wang, Jianhua Lu, Jun Peng, Jiawei Zhang

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The fundamental demand in contemporary intelligent science towards Autonomous AI (AI*) is the creation of unprecedented formal means of Intelligent Mathematics (IM). It is discovered that natural intelligence is inductively created rather than exhaustively trained. Therefore, IM is a family of algebraic and denotational mathematics encompassing Inference Algebra, Real-Time Process Algebra, Concept Algebra, Semantic Algebra, Visual Frame Algebra, etc., developed in our labs. IM plays indispensable roles in training-free AI* theories and systems beyond traditional empirical data-driven technologies. A set of applications of IM-driven AI* systems will be demonstrated in contemporary intelligence science, AI*, and cognitive computers.

Keywords: intelligence mathematics, foundations of intelligent science, autonomous AI, cognitive computers, inference algebra, real-time process algebra, concept algebra, semantic algebra, applications

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Authors: Khadidja Bellifa, Sidi Mohamed Mekelleche

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Phenols and especially halogenated phenols represent a substantial part of the chemicals produced worldwide and are known as aquatic pollutants. Quantitative structure–toxicity relationship (QSTR) models are useful for understanding how chemical structure relates to the toxicity of chemicals. In the present study, the acute toxicities of 45 halogenated phenols to Tetrahymena Pyriformis are estimated using no cost semi-empirical quantum chemistry methods. QSTR models were established using the multiple linear regression technique and the predictive ability of the models was evaluated by the internal cross-validation, the Y-randomization and the external validation. Their structural chemical domain has been defined by the leverage approach. The results show that the best model is obtained with the AM1 method (R²= 0.91, R²CV= 0.90, SD= 0.20 for the training set and R²= 0.96, SD= 0.11 for the test set). Moreover, all the Tropsha’ criteria for a predictive QSTR model are verified.

Keywords: halogenated phenols, toxicity mechanism, hydrophobicity, electrophilicity index, quantitative stucture-toxicity relationships

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Authors: L. K. Shitole

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Usually on the face of it, personality is regarded as the external appearance of an individual. In psychology, the personality is not viewed merely as self or external appears, but it adds much more. Human resources development encompasses the personality development of the students. The student’s development starts right from the childhood and gradually continues right up to the completion of education in professional courses. This paper attempts to find out the role of the educational institutions in shaping the personality of the students from the rural area. Schools and colleges have infrastructural limitations, obtaining good quality and devoted teaching staff poses problems and even outside the school environment there are no private classes which may take care of this deficiency. The researcher has used the standardized test namely “Vyaktitva Shodhika” developed by Gyan Prabodhini, Pune for the students in Daund Taluka. There are 68 objective types of questions in the said questionnaire. Totally a sample size of 4191 students was selected. The sample was quite representative. It is observed that by and large the response indicates that the educational institutions are taking sincere efforts in shaping the personality of the students. In the semi-urban area i.e. at educational institutions of all levels, the performance on this front is excellent and at rest of Daund Taluka there is scope for improvement. Educational institutions of all levels are showing excellent performance in ensuring availability of the requisite infrastructure conducive for the development of the personality of the students. In rest of Daund Taluka there is ample scope for improving the situation. As far as data relating to role of co-curricular activities and sports programs in mental and physical development at various educational institutions is concerned Daund educational institutions have repeated their performance in securing “A” category, while in the rural area of Daund Taluka, there is need to step up the efforts in this regard. In today’s world of knowledge industry, one cannot ignore the importance of education and thereby the personality growth of the students. Accordingly, the educational institutions should undertake consistent research and extension activities in the area of personality development.

Keywords: personality, attitude, infrastructure, quality of education, learning environment, teacher’s contribution, family and society’s role

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Authors: Saeed Ullah Jan, Shafaq, Sumbul

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Anxiety is one of the most common emotions and is a normal reaction to danger or a threat. It is a normal reaction to stress and can be beneficial in some situations. It can alert us to dangers and help us prepare and pay attention. The prime aim of this study was to examine the level of anxiety of Library and Information Science students at the Department of Library and Information Science, Khushal Khan Khattak University Karak. A survey method was used for the completion of this study. The response of male respondents was better than female LIS students at the Department of Library and Information Science, Khushal Khan Khattak University Karak. The librarians should have to focus on the information needs of the university students. Special training needs to be arranged for female students to improve their library usage and readership rate.

Keywords: library-anxiety, library anxiety-students, library anxiety -students-Pakistan, stress

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Authors: Ala Hanetite

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This study aims to investigate the implications of quality management system (QMS) practices in employees' attitudes relating to job involvement, job satisfaction, career satisfaction, and organizational commitment. Design/methodology/approach: This study was accomplished through the use of a questionnaire. Twenty hypotheses related to QMS practices and the employees' attitudes were formulated and tested. Findings: The results indicate that responsibility and teamwork have a significant and positive correlation with job involvement, job satisfaction, career satisfaction, as well as organizational commitment. Ongoing improvement and problem solving have significant implications in organizational commitment. In addition, training and education, as well as customer focus, did not demonstrate any favorable contribution to the employees' attitudes. Originality/value: The study recommends that management should be more committed to the development of quality practices to sustain and enhance employees' positive attitudes toward their job. Such practices are a competitive strategy to attract and retain competent employees.

Keywords: attitudes, employee, quality management system, competitive strategy

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Authors: Ida Zubaidah

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With the advancement of information and communication technologies, in many cases, geographical distance is no longer considered as a main barrier in distance education. Geographical distance, even from a continent to another, between students and their instructor or students and their campus can be connected by the Internet, telephone or any other means of communication technology. Managing distance learning in an archipelagic country like Indonesia, however, has some different stories. Comprising more than 17,000 islands and 6.000 of them inhabited, Indonesia is considered as one of the most archipelagic countries in the world. In some areas or islands that have adequate public transportation and communication facilities the courses can be delivered quite well. In other areas that geographically very remote and dispersed islander, Universitas Terbuka, an open university in Indonesia, has to have very different strategies in overcoming the specific and even emergency situations in learning delivery. This ongoing research paper aims to share experiences of how Universitas Terbuka makes serious and unique efforts in overcoming the barriers and obstacles in providing educational service in part of difficult areas, especially in eastern areas of Indonesia. The data collection methods are observation of sample areas and in-depth interview with the head of regional offices of Universitas Terbuka in eastern Indonesia, staff, and tutors. Conducting educational deliveries in in difficult areas with no regular and adequate transportation has made the regional office have specific strategies in making the learning process run as smooth as possible. Sending a tutor to an area to meet some students and conducting a series of tutorial, which are supposed to be weekly, in several days is one of the strategies. Recruiting local people to manage the students in the area is another strategy. The absence of regular transportation from island to island, high tides, hurricanes, are among the obstacles faced by the regional offices in doing their job. Non geographical barriers such as unavailability of qualified tutor, inadequate tutor payment, are problems as well. The learning process, however, has to be done in any way, otherwise the distance education mission to reach unreachable cannot be achieved.

Keywords: distance education, Terbuka University, difficult area, geographical barrier, learning services

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Authors: Alberto Mora-Vazquez, Nelly Paulina Trejo Guzmán

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This study examines the learning trajectories of twelve language teachers who were former students of a BA in applied linguistics at a Mexican state university. In particular, the study compares the social, academic and professional trajectories of two groups of teachers, six locally raised and educated ones and six repatriated ones from the U.S. Our interest in undertaking this research lies in the wide variety of students’ backgrounds we as professors in the BA program have witnessed throughout the years it has been around. Ever since the academic program started back in 2006, the student population has been made up of students whose backgrounds are highly diverse in terms of English language proficiency level, professional orientations and degree of cross-cultural awareness. Such diversity is further evidenced by the ongoing incorporation of some transnational students who have lived and studied in the United States for a significant period of time before their enrolment in the BA program. This, however, is not an isolated event as other researchers have reported this phenomenon in other TESOL-related programs of Mexican universities in the literature. Therefore, this suggests that their social and educational experiences are quite different from those of their Mexican born and educated counterparts. In addition, an informal comparison of the participation in formal teaching activities of the two groups at the beginning of their careers also suggested that significant differences in teacher training and development needs could also be identified. This issue raised questions about the need to examine the life and learning trajectories of these two groups of student teachers so as to develop an intervention plan aimed at supporting and encouraging their academic and professional advancement based on their particular needs. To achieve this goal, the study makes use of a combination of retrospective life-history research and the analysis of academic documents. The first approach uses interviews for data-collection. Through the use of a narrative life-history interview protocol, teachers were asked about their childhood home context, their language learning and teaching experiences, their stories of studying applied linguistics, and self-description. For the analysis of participants’ educational outcomes, a wide range of academic records, including reports of language proficiency exams results and language teacher training certificates, were used. The analysis revealed marked differences between the two groups of teachers in terms of academic and professional orientations. The locally educated teachers tended to graduate first, to look for further educational opportunities after graduation, to enter the language teaching profession earlier, and to expand their professional development options more than their peers. It is argued that these differences can be explained by their identities, which are made up of the interplay of influences such as their home context, their previous educational experiences and their cultural background. Implications for language teacher trainers and applied linguistics academic program administrators are provided.

Keywords: beginning language teachers, life-history research, Mexican context, transnational students

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Authors: Marina Shurupova, Victor Anisimov, Alexander Latanov

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Background: The cerebellar lesions inevitably provoke oculomotor impairments in patients of different age. Symptoms of subtentorial tumors, particularly medulloblastomas, include static and dynamic coordination disorders (ataxia, asynergia, imbalance), hypo-muscle tonus, disruption of the cranial nerves, and within the oculomotor system - nystagmus (fine or gross). Subtentorial tumors can also affect the areas of cerebellum that control the oculomotor system. The noninvasive eye-tracking technology allows obtaining multiple oculomotor characteristics such as the number of fixations and their duration, amplitude, latency and velocity of saccades, trajectory and scan path of gaze during the process of the visual field navigation. Eye tracking could be very useful in clinical studies serving as convenient and effective tool for diagnostics. The aim: We studied the dynamics of oculomotor system functioning in patients undergoing remission from cerebellar tumors removal surgeries and following neurocognitive rehabilitation. Methods: 38 children (23 boys, 15 girls, 9-17 years old) that have recovered from the cerebellar tumor-removal surgeries, radiation therapy and chemotherapy and were undergoing course of neurocognitive rehabilitation participated in the study. Two tests were carried out to evaluate oculomotor performance - gaze stability test and counting test. The monocular eye movements were recorded with eye tracker ArringtonResearch (60 Hz). Two experimental sessions with both tests were conducted before and after rehabilitation courses. Results: Within the final session of both tests we observed remarkable improvement in oculomotor performance: 1) in the gaze stability test the spread of gaze positions significantly declined compared to the first session, and 2) the visual path in counting test significantly shortened both compared to the first session. Thus, neurocognitive rehabilitation improved the functioning of the oculomotor system in patients following the cerebellar tumor removal surgeries and subsequent therapy. Conclusions: The experimental data support the effectiveness of the utilization of the eye tracking technique as diagnostic tool in the field of neurooncology.

Keywords: eye tracking, rehabilitation, cerebellar tumors, oculomotor system

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Authors: Yumi Okano

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The low level of English proficiency among Japanese people has been a problem for a long time. Japanese non-native English language teachers, under social or ideological constraints, feel a gap between government policy and their language proficiency and cannot maintain high self-esteem. This paper focuses on current Japanese policies and the social context in which teachers are placed and examines the measures necessary for their positive identity formation from a macro-meso-micro perspective. Some suggestions for achieving this are: 1) Teachers should free themselves from the idea of native speakers and embrace local needs and accents, 2) Teachers should be involved in student discussions as facilitators and individuals so that they can be good role models for their students, and 3) Teachers should invest in their classrooms. 4) Guidelines and training should be provided to help teachers gain confidence. In addition to reducing the workload to make more time available, 5) expanding opportunities for investment outside the classroom into the real world is necessary.

Keywords: language teacher identity, native speakers, government policy, critical pedagogy, investment

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Authors: S. A. Naeini, A. Khalili

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Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

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Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam

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In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.

Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data

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Authors: Evuarherhe Veronica Abolo

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The study investigated the programs in Nigerian higher institutions and how they influence unemployment of graduates in the country. The study employed the survey design. The population of the study includes two universities, two polytechnics and two colleges of education in Lagos State. A total of 350 participants, which include graduates and students were sampled for the study. A structured interview schedule and direct observation were used to collect data on the three research questions drawn for the study. The data were analyzed using rating of the structured interview in tables and percentages. The results of the study revealed that Nigerian graduates are not only unemployed but can hardly meet the requirements of available job vacancies due to the stereotype nature in scope, content and methods of the programs in the institutions. Recommendations such as collaboration of companies (end- users) and institutions in the training of students, restructuring of the content and methodology of programs and providing soft loans and other facilities to the young graduates were proffered to reduce the rate of graduates’ unemployment in Nigeria.

Keywords: higher institution, graduate unemployment, soft loan, unemployment

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Authors: Van Nhan Nguyen, Harald Holone

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Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: automatic speech recognition, asr, air traffic control, atc

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Authors: Saead Rostami, Seyyed Hadi Hosseini Alavije, Aliakbar Torabi, Mohammad Bekhradi

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This study is about The effects of different doses of caffeine on young Futsal players. Young futsal players of selected ShahinShahr(a city in Esfahan province, Iran) team are sampled (24 people of 18.3±1.9 year- old). All players are members of youth team playing in Esfahan counties league. Having at least 5 years of experience, 2 practices and 1 match per week and lacking any limitation in the past 6 months are the most important requirements for sampling the players. Next, the study topic, its method, its uses, as ell possible risks are explained to the players. They signed a consent letter to take part in the study. Interest in the use of caffeine as an ergogenic aid has increased since the International Olympic Committee lifted the partial ban on its use. Caffeine has beneficial effects on various aspects of athletic performance, but its effects on training have been neglected. The purpose of this study was to investigate the acute effect of caffeine on testosterone and cortisole in young futsal players.

Keywords: anabolic, catabolic, performance, testosterone cortisol ratio, RAST test

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Authors: Patik Joslin Kenfack, Polyakov Vladimir Mikhailovich

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Machine Learning (ML) systems are trained using human generated data that could be biased by implicitly containing racist, sexist, or discriminating data. ML models learn those biases or even amplify them. Recent research in work on has begun to consider issues of fairness. The concept of fairness is extended to recommendation. A recommender system will be considered fair if it doesn’t under rank items of protected group (gender, race, demographic...). Several metrics for evaluating fairness concerns in recommendation systems have been proposed, which take pairs of items as ‘instances’ in fairness evaluation. It doesn’t take in account the fact that the fairness should be evaluated across a list of items. The paper explores a probabilistic approach that generalize pairwise metric by using a list k (listwise) of items as ‘instances’ in fairness evaluation, parametrized by k. We also explore new regularization method based on this metric to improve fairness ranking during model training.

Keywords: Fairness, Recommender System, Ranking, Listwise Approach

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Authors: Ankita R. Bansal, Naren S. Burade

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Idea is to create a cloud based virtual lab for Deaf Students, “A language acquisition program using Visual Phonics and Cued Speech” using VMware Virtual Lab. This lab will demonstrate students the sounds of letters associated with the Language, building letter blocks, making words, etc Virtual labs are used for demos, training, for the Lingual development of children in their vernacular language. The main potential benefits are reduced labour and hardware costs, faster response times to users. Virtual Computing Labs allows any of the software as a service solutions, virtualization solutions, and terminal services solutions available today to offer as a service on demand, where a single instance of the software runs on the cloud and services multiple end users. VMWare, XEN, MS Virtual Server, Virtuoso, and Citrix are typical examples.

Keywords: visual phonics, language acquisition, vernacular language, cued speech, virtual lab

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Authors: Geeta Goyal

Abstract:

Teaching-learning of English as a second language is a challenge for the learner as well as the teacher. Whereas a student may find it hard and get demotivated while communicating in a language other than mother tongue, a teacher, too, finds it difficult to integrate necessary teaching material in lesson plans to maximize the outcome. Studies reveal that task-based teaching can be useful in diverse contexts in a second language classroom as it helps in creating opportunities for language exposure as per learners' interest and capability levels, which boosts their confidence and learning efficiency. The present study has analysed the impact of various activities carried out in a heterogenous group of second language learners at tertiary level in a semi-urban area in Haryana state of India. Language tasks were specifically planned with a focus on engaging groups of twenty-five students for a period of three weeks. These included language games such as spell-well, cross-naught besides other communicative and interactive tasks like mock-interviews, role plays, sharing experiences, storytelling, simulations, scene-enact, video-clipping, etc. Tools in form of handouts and cue cards were also used as per requirement. This experiment was conducted for ten groups of students taking bachelor’s courses in different streams of humanities, commerce, and sciences. Participants were continuously supervised, monitored, and guided by the respective teacher. Feedback was collected from the students through classroom observations, interviews, and questionnaires. Students' responses revealed that they felt comfortable and got plenty of opportunities to communicate freely without being afraid of making mistakes. It was observed that even slow/timid/shy learners got involved by getting an experience of English language usage in friendly environment. Moreover, it helped the teacher in establishing a trusting relationship with students and encouraged them to do the same with their classmates. The analysis of the data revealed that majority of students demonstrated improvement in their interest and enthusiasm in the class. The study revealed that task-based teaching was an effective method to improve the teaching-learning process under the given conditions.

Keywords: communication skills, English, second language, task-based teaching

Procedia PDF Downloads 78

Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

Abstract:

Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

Procedia PDF Downloads 232

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

Abstract:

Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 67