Search results for: regression training

Authors: Kantha Siddhanth Gujjari, Shaani Singhal, Robert Andrew Danks, Adrian Praeger

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Background: Trigeminal neuralgia (TN) is a heterogenous pain syndrome characterised by short paroxysms of lancinating facial pain in the distribution of the trigeminal nerve, often triggered by usually innocuous stimuli. TN has a low prevalence of less than 0.1%, of which 80% to 90% is caused by compression of the trigeminal nerve from an adjacent artery or vein. The root entry zone of the trigeminal nerve is most sensitive to neurovascular conflict (NVC), causing dysmyelination. Whilst microvascular decompression (MVD) is an effective treatment for TN with NVC, all patients do not achieve long-term pain relief. Pre-operative scoring systems by Panczykowski and Hardaway have been proposed but have not been externally validated. These pre-operative scoring systems are composite scores calculated according to a subtype of TN, presence and degree of neurovascular conflict, and response to medical treatments. There is discordance in the assessment of NVC identified on pre-operative magnetic resonance imaging (MRI) between neurosurgeons and radiologists. To our best knowledge, the prognostic impact for MVD of this difference of interpretation has not previously been investigated in the form of a composite scoring system such as those suggested by Panczykowski and Hardaway. Aims: This study aims to identify prognostic factors and externally validate the proposed scoring systems by Panczykowski and Hardaway for TN. A secondary aim is to investigate the prognostic difference between a neurosurgeon's interpretation of NVC on MRI compared with a radiologist’s. Methods: This retrospective cohort study included 95 patients who underwent de novo MVD in a single neurosurgical unit in Melbourne. Data was recorded from patients’ hospital records and neurosurgeon’s correspondence from perioperative clinic reviews. Patient demographics, type of TN, distribution of TN, response to carbamazepine, neurosurgeon, and radiologist interpretation of NVC on MRI, were clearly described prospectively and preoperatively in the correspondence. Scoring systems published by Panczykowski et al. and Hardaway et al. were used to determine composite scores, which were compared with the recurrence of TN recorded during follow-up over 1-year. Categorical data analysed using Pearson chi-square testing. Independent numerical and nominal data analysed with logistical regression. Results: Logistical regression showed that a Panczykowski composite score of greater than 3 points was associated with a higher likelihood of pain-free outcome 1-year post-MVD with an OR 1.81 (95%CI 1.41-2.61, p=0.032). The composite score using neurosurgeon’s impression of NVC had an OR 2.96 (95%CI 2.28-3.31, p=0.048). A Hardaway composite score of greater than 2 points was associated with a higher likelihood of pain-free outcome 1 year post-MVD with an OR 3.41 (95%CI 2.58-4.37, p=0.028). The composite score using neurosurgeon’s impression of NVC had an OR 3.96 (95%CI 3.01-4.65, p=0.042). Conclusion: Composite scores developed by Panczykowski and Hardaway were validated for the prediction of response to MVD in TN. A composite score based on the neurosurgeon’s interpretation of NVC on MRI, when compared with the radiologist’s had a greater correlation with pain-free outcomes 1 year post-MVD.

Keywords: de novo microvascular decompression, neurovascular conflict, prognosis, trigeminal neuralgia

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Authors: Mokopane Charles Marakalala

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

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

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Authors: Elabed Saud

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

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

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Authors: Fahad Ibrahim, Raphaël Akamavi

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

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

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Authors: Oluropo Stephen Ilesanmi, Oluwole Ayodele Alejo

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

Keywords: architecture, education, communication, information, technology

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Authors: Taner Ersoz, Filiz Ersoz, Seyma Ozbilge

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In this study, the clients who applied to a bank branch for loan were analyzed through data mining. The study was composed of the information such as amounts of loans received by personal and SME clients working with the bank branch, installment numbers, number of delays in loan installments, payments available in other banks and number of banks to which they are in debt between 2010 and 2013. The client risk profile was examined through Classification and Regression Tree (CART) analysis, one of the decision tree classification methods. At the end of the study, 5 different types of customers have been determined on the decision tree. The classification of these types of customers has been created with the rating of those posing a risk for the bank branch and the customers have been classified according to the risk ratings.

Keywords: client classification, loan suitability, risk rating, CART analysis

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native language identification is one of the growing subfields in natural language processing (NLP). The task of native language identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features, when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL), and then the trained models are evaluated on different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and logistic regression. Results show that content-based features are more accurate and robust than content independent ones when tested within the corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML

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Authors: Udeh Anastasia Ifeoma

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The need to develop the rural areas in developing countries where there have been decades of neglect are on the increase. It is against this background that this paper examined the impact of micro finance contribution to Nigeria’s gross domestic product. Time series data for 12-years period 1999-2010 were collated from Central Bank of Nigeria published annual reports. The least squares (LS) regression was used to analyze the data. The result revealed that microfinance activities have negative and non-significant contribution to gross domestic product in Nigeria. The paper recommends that rural poverty is often a product of poor infrastructural facilities; therefore government should make a conscious effort towards industrializing the rural areas thereby motivating the micro finance institutions to locate their offices and extend credit facilities to rural areas thereby improving rural economic growth.

Keywords: microfinance, rural economic growth, Nigeria, developing countries

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Authors: Aniket Aaba Kadam, Manish Mangesh Panchal, Roushan Ashit Sharma

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This project focuses on the design and development of a lab-scale hybrid rocket motor to accurately determine the regression rate of a fuel/oxidizer combination consisting of solid paraffin and gaseous oxygen (GOX). Hybrid motors offer the advantage of on-demand thrust control over both solid and liquid systems in certain applications. The thermodynamic properties of the propellant combination were calculated using NASA CEA at different chamber pressures and corresponding O/F values to determine initial operating conditions with suitable peak temperatures and optimal O/F values. The project also includes the design of the injector orifice and the determination of the final design configurations of the motor casing, pressure control setup, and valve configuration. This research will be valuable in advancing the understanding of paraffin-based propulsion and improving the performance of hybrid rocket motors.

Keywords: hybrid rocket, NASA CEA, injector, thrust control

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Authors: Ali Farzan

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

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

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Authors: Abdulla D. Alblooshi

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The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

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Authors: Ali Kassem, Ehab Fawzy, Mahmoud Sef el-eslam, Fatma Salah- Eldeen, El zahraa Mohamed

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Introduction: The combination of interferon (INF) and ribavirin is the preferred treatment for chronic hepatitis C viral (HCV) infection. However, nonresponse to this therapy remains common and is associated with several factors such as HCV genotype and HCV viral load in addition to host factors such as sex, HLA type and cytokine polymorphisms. Aim of the work: The aim of this study was to determine predictors of response to (INF) therapy in chronic HCV infected patients treated with INF alpha and ribavirin combination therapy. Patients and Methods: The present study included 110 patients (62 males, 48 females) with chronic HCV infection. Their ages ranged from 20-59 years. Inclusion criteria were organized according to the protocol of the Egyptian National Committee for control of viral hepatitis. Patients included in this study were recruited to receive INF ribavirin combination therapy; 54 patients received pegylated NF α-2a (180 μg) and weight based ribavirin therapy (1000 mg if < 75 kg, 1200 mg if > 75 kg) for 48 weeks and 53 patients received pegylated INF α-2b (1.5 ug/kg/week) and weight based ribavirin therapy (800 mg if < 65 kg, 1000 mg if 65-75 kg and 1200 mg if > 75kg). One hundred and seven liver biopsies were included in the study and submitted to histopathological examination. Hematoxylin and eosin (H&E) stained sections were done to assess both the grade and the stage of chronic viral hepatitis, in addition to the degree of steatosis. Modified hepatic activity index (HAI) grading, modified Ishak staging and Metavir grading and staging systems were used. Laboratory follow up including: HCV PCR at the 12th week to assess the early virologic response (EVR) and at the 24th week were done. At the end of the course: HCV PCR was done at the end of the course and tested 6 months later to document end virologic response (ETR) and sustained virologic response (SVR) respectively. Results One hundred seven patients; 62 males (57.9 %) and 45 females (42.1%) completed the course and included in this study. The age of patients ranged from 20-59 years with a mean of 40.39±10.03 years. Six months after the end of treatment patients were categorized into two groups: Group (1): patients who achieved sustained virological response (SVR). Group (2): patients who didn't achieve sustained virological response (non SVR) including non-responders, breakthrough and relapsers. In our study, 58 (54.2%) patients showed SVR, 18 (16.8%) patients were non-responders, 15 (14%) patients showed break-through and 16 (15 %) patients were relapsers. Univariate binary regression analysis of the possible risk factors of non SVR showed that the significant factors were higher age, higher fasting insulin level, higher Metavir stage and higher grade of hepatic steatosis. Multivariate binary regression analysis showed that the only independent risk factor for non SVR was high fasting insulin level. Conclusion: Younger age, lower Metavir stage, lower steatosis grade and lower fasting insulin level are good predictors of SVR and could be used in predicting the treatment response of pegylated interferon/ribavirin therapy.

Keywords: chronic HCV infection, interferon ribavirin combination therapy, predictors to antiviral therapy, treatment response

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Authors: Huey-Wen Chou, Shuo-Heng Liang

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This study focuses on studying college students’ multitasking with cellphones/laptops during lectures. In-class multitasking behavior is defined as the activities students engaged that are irrelevant to learning. This study aims to understand if students' learning engagement affects students' multitasking as well as to investigate the causes or motivations that contribute to the occurrence of multitasking behavior. Survey data were collected and analyzed by PLS method and multiple regression to test the research model and hypothesis. Major results include: 1. Students' multitasking motivation positively predicts students’ in-class multitasking. 2. Factors affecting multitasking in class, including efficiency, entertainment and social needs, significantly impact on multitasking. 3. Polychronic personality traits will positively predict students’ multitasking. 4. Students' classroom learning engagement negatively predicts multitasking. 5. Course attributes negatively predict student learning engagement and positively predict student multitasking.

Keywords: engagement, monochronic personality, multitasking, learning, personality traits

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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

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

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Rizwan Ali, Hammad Zafar

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The purpose of this research is to investigate the mediation effect of customer satisfaction in the relationship between service quality, corporate image to customer loyalty, in Pakistan banking sector. The population of this research is banking customers and sample size of 210 respondents. This research uses the SPSS, Correlation, ANOVA and regression analysis techniques along with AMOS methods. The service quality and corporate image applied by the banks are not all variables can directly affect customer loyalty, but must first going through satisfaction. Which means that banks must first need to understand what the customer basic needs through variable service quality and corporate image so that the customers feel loyal when the level of satisfaction is resolved. The service quality provided by the banking industry needs to be improved in order to improve customer satisfaction and loyalty of banking services, especially for banks in Pakistan.

Keywords: customer loyalty, service quality, corporate image, customer satisfaction

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Authors: Johnstone Walubengo Wangusi

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

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

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

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

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

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Authors: Ali Adamu

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Teachers’ background characteristics as a correlate of students’ achievement in Mathematics were studied in Gombe State. Pearson Product Moment Correlation Coefficient was used for the analysis. Five Hundred and Twelve (512) students and 20 teachers from 12 schools in Gombe State of Nigeria were used for the study. Students’ Achievement Tests and Mathematics Teachers’ backgrounds were instruments for the study. The findings indicated that teachers’ qualifications, experience of the teacher, and teachers’ personalities had a positive correlation with students’ achievement. Recommendations are made, which include allowing the teachers to go for training as well as the government should ensure recruiting teachers that have experience in the teaching job.

Keywords: achievement-test, teachers’ personality, teaching mathematics, teacher-background

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Authors: Mardianto

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Education and learning are now grown rapidly. Synergy of techonology especially instructional technology in the learning activities are very big influence on the effectiveness of learning and creativity to achieve optimal results. But on the other hand there is a education value that is difficult to be articulated through character-forming technology such as honesty, discipline, hard work, heroism, and so forth. Learning strategy and storytelling from the past until today is still an option for teachers to convey the message of character values. With the material was loaded from the local culture (stories folklore), the combination of learning objectives (build character child) strategy, and traditional methods (storytelling and story), and the preservation of local culture (dig tale folklore) is critical to maintaining the nation's culture. In the context of maintaining the nation's culture, then since the age of the child at the level of government elementary school a necessity. Globalization, the internet and technology sometimes feel can displace the role of the teacher in the learning activities. To the oral tradition is a mainstay of storytelling should be maintained and preserved. This research was conducted at the elementary school in the city of Medan, North Sumatra Indonesia, with a random sampling technique, the 27 class teachers were respondents who were randomly assigned to the Madrasah Ibtdaiyah (Islamic Elementary School) both public and private. Research conducted at the beginning of 2014 refers to a curriculum that is being transformed in the environment ministry Republic Religion Indonesia. The results of this study indicate that; the declining skills of teachers to develop storytelling this can be seen from; 74.07% of teachers have never attended a special training storytelling, 85.19% no longer nasakah new stories, only 22.22% are teachers who incorporate methods of stories in the learning plan. Most teachers are no longer concerned with storytelling, among those experiencing difficulty in developing methods because the story; 66.67% of children are more interested in children's cartoons like Bobo boy, Angrybirds and others, 59.26 children prefer other activities than listening to a story. The teachers hope, folklore books should be preserved, storytelling training should be provided by the government through the ministry of religion, race or competition of storytelling should be scheduled, writing a new script-based populist storytelling should be provided immediately. The teachers’ hope certainly not excessive, by realizing the story method becomes articulation as the efforts of child character development based populist, therefore the local knowledge can be a strong fortress facing society in the era of progress as at present, and future.

Keywords: story telling, local wisdom, education, technology development

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Authors: Aanuoluwapo Olusola Adesanya, Adesina Joseph

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This paper examined the class-size and instructional materials as correlates of pupils learning and academic achievement in primary school. The population of the study comprised 198 primary school pupils in three selected schools in Ogun State, Nigeria. Data were collected through questionnaire and were analysed with the use of multiple regression and ANOVA to analysed the correlation between class-size, instructional materials (independent variables) and learning achievement (dependent variable). The findings revealed that schools having an average class-size of 30 and below with use of instructional materials obtained better results than schools having more than 30 and above. The main score were higher in the school in schools having 30 and below than schools with 30 and above. It was therefore recommended that government, stakeholders and NGOs should provide more classrooms and supply of adequate instructional materials in all primary schools in the state to cater for small class-size.

Keywords: class-size, instructional materials, learning, academic achievement

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Authors: Weidong Xia, Malgorzata Kolotylo, Xuan Tan

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This study examines the key factors that influence general practitioners’ learning and transfer of specialized arthritis knowledge and self-care techniques to patients during normal patient visits. Drawing on the theory of planed behavior and using matched survey data collected from general practitioners before and after training sessions provided by specialized orthopedic physicians, the study suggests that the general practitioner’s intention to use and transfer learned knowledge was influenced mainly by intrinsic motivation, organizational learning culture and absorptive capacity, but was not influenced by extrinsic motivation. The results provide both theoretical and practical implications.

Keywords: empirical study, healthcare knowledge management, patient self-care, physician knowledge transfer

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Authors: Godaye Gobena Gomiole

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The purpose of this study is to determine how principals at Tarcha Town Primary Schools in Ethiopia perceive their instructional leadership responsibilities in curriculum execution. The research was guided by a phenomenological study design. The data was collected through semi-structured interviews. Purposive sampling was used to include twelve principals. The study's conclusions showed that principals fall short of their duties in overseeing instruction. Setting clear objectives for the school and coordinating the curriculum receive less attention from principals. Additionally, they focus less on keeping track of students' progress. It is, therefore, advised that principals take instructional leadership and management training.

Keywords: curriculum execution, instructional leadership, practice, primary school

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Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Abiodun Musbau Lawal, Sunday Samson Babalola, Uzor Friday Ordu

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Issue of employees counterproductive work behavior in government owned organization in emerging economies has continued to be a major concern. This study investigated the factors of pay satisfaction, intent to leave and age as predictors of counterproductive work behavior among non-academic employee in a Nigerian federal government owned university. A sample of 200 non-academic employees completed questionnaires. Hierarchical multiple regression was conducted to determine the contribution of each of the predictor variables on the criterion variable on counterproductive work behavior. Results indicate that age of participants (β = -.18; p < .05) significantly independently predicted CWB by accounting for 3% of the explained variance. Addition of pay satisfaction (β = -.14; p < .05) significantly accounted for 5% of the explained variance, while intent to leave (β = -.17; p < .05) further resulted in 8% of the explained variance in counterproductive work behavior. The importance of these findings with regards to reduction in counterproductive work behavior is highlighted.

Keywords: counterproductive, work behaviour, pay satisfaction, intent to leave

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Authors: Md. Nazmul Haque, Mahinur Rahman

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The objective of the research is to determine the quantity of household waste generated and forecast the future condition of Ward No 24 (Nirala). For performing that, three core issues are focused: (i) the capacity and service area of the dumping stations; (ii) the present waste generation amount per capita per day; (iii) the responsibility of the local authority in the household waste collection. This research relied on field survey-based data collection from all stakeholders and GIS-based secondary analysis of waste collection points and their coverage. However, these studies are mostly based on the inherent forecasting approaches, cannot predict the amount of waste correctly. The findings of this study suggest that Nirala is a formal residential area introducing a better approach to the waste collection - self-controlled and collection system. Here, a forecasting model proposed for waste generation as Y = -2250387 + 1146.1 * X, where X = year.

Keywords: eco-friendly environment, household waste, linear regression, waste management

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Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

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The study attempts to analyze the impact of credit risk management practices of Indian scheduled commercial banks on their non-performing assets (NPAs). The data on credit risk practices was collected by administering a questionnaire to risk managers/executives at different banks. The data on NPAs (from 2012 to 2016) is sourced from Prowess, a database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was estimated using cross-sectional regression method. As expected, the findings suggest that there is a negative relationship between credit risk management and NPA growth in Indian banks. The study has implications for Indian banks given the high level of losses, and the implementation of Basel III norms by the central bank, i.e. Reserve Bank of India (RBI). Evidence on credit risk management in Indian banks, and their relationship with non-performing assets held by them.

Keywords: credit risk, identification, Indian Banks, NPAs, ownership

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Authors: Habibollah Mashhady, Behruz Lotfi, Mohammad Doosti, Moslem Fatollahi

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An exploration of the related literature reveals that all instruction methods aim at training autonomous learners. After the turn of second language pedagogy toward learner-oriented strategies, learners’ needs were more focused. Yet; the historical, social and political aspects of learning were still neglected. The present study investigates the notion of autonomous learning and explains its various facets from a pedagogical point of view. Furthermore; different elements, fields and scopes of autonomous learning will be explored. After exploring different aspects of autonomy, it is postulated that liberatory autonomy is highlighted since it not only covers social autonomy but also reveals learners’ capabilities and human potentials. It is also recommended that learners consider different elements of autonomy such as motivation, knowledge, confidence, and skills.

Keywords: critical pedagogy, social autonomy, academic learning, cultural notions

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Authors: Asror Nigmonov Asqar Ogli, Sitora Inoyatova Amonovna

Abstract:

It has been a decade when the crowdfunding and P2P lending opportunities were created. Today, the market of these modern alternative investments is becoming increasingly complex to navigate. There are overwhelming amount of peer-to-peer lending platforms both in developed and emerging economies. This study looks into this market via the cross country empirical study. In this respect, it tests the effect of various macroeconomic factors on P2P loan lending. Based on the existing literature that largely lacks empirical investigations, it builds regression model that aims to explore the relationship between economy and P2P lending. Though the author found it extremely difficult to compare the findings with earlier studies, this paper had identified certain tendencies in the data and had certain policy implications. However, the paper could not find any significant effect of economic variables on P2P lending. The paper can be considered as a starting point in empirical investigation of P2P lending and highlights room further research based on limitations of the study.

Keywords: peer-to-peer lending, crowdfunding, marketplace lending, alternative finance, fintech

Procedia PDF Downloads 190

Authors: Ezinne K. Okoro, Takahiko Katoh, Yoko Kawamura, Stanley C. Meribe

Abstract:

HIV infection in children is largely as a result of vertical transmission (mother to child transmission [MTCT]). Thus, elimination of mother to child transmission of HIV/AIDS is critical in eliminating HIV infection in children. In Nigeria, drawbacks such as; limited pediatric screening, limited human capital, insufficient advocacy and poor understanding of ART guidelines, have impacted efforts at combating the disease, even as treatment services are free. Prevention of Mother to Child Transmission (PMTCT) program relies on health workers who not only counsel pregnant women on first contact but can competently provide HIV-positive pregnant women with accurate information about the PMTCT program such as feeding techniques and drug adherence. In developing regions like Nigeria where health care delivery faces a lot of drawbacks, it becomes paramount to address these issues of poor PMTCT coverage by conducting a baseline assessment of the knowledge, practices and perceptions related to HIV prevention amongst healthcare workers in Nigeria. A descriptive cross-sectional study was conducted amongst 250 health workers currently employed in health facilities in Abuja, Nigeria where PMTCT services were offered with the capacity to carry out early infant diagnosis testing (EID). Data was collected using a self-administered, pretested, structured questionnaire. This study showed that the knowledge of PMTCT of HIV was poor (30%) among healthcare workers who offer this service day-to-day to pregnant women. When PMTCT practices were analyzed in keeping with National PMTCT guidelines, over 61% of the respondents reported observing standard practices and the majority (58%) had good attitudes towards caring for patients with HIV/AIDS. Although 61% of the respondents reported being satisfied with the quality of service being rendered, 63% reported not being satisfied with their level of knowledge. Predictors of good knowledge were job designation and level of educational attainment. Health workers who were more satisfied with their working conditions and those who had worked for a longer time in the PMTCT service were more likely to observe standard PMTCT practices. With over 62% of the healthcare workers suggesting that more training would improve the quality of service being rendered, this is a strong pointer to stakeholders to consider a ‘healthcare worker-oriented approach’ when planning and conducting PMTCT training for healthcare workers. This in turn will increase pediatric ARV coverage, the knowledge and effectiveness of the healthcare workers in carrying out appropriate PMTCT interventions and culminating in the reduction/elimination of HIV transmission to newborns.

Keywords: attitudes, HIV/AIDS, healthcare workers, knowledge, mother to child transmission, Nigeria, perceptions

Procedia PDF Downloads 199