Showing papers in "Indian journal of science and technology in 2019"

Predicting University Dropout through Data Mining: A Systematic Literature

Abstract: Objectives: To make a systematic review of literature on the prediction of university student dropout through data mining techniques. Methods/Analysis: The study was developed as a systematic review of the literature of empirical research results regarding the prediction of university dropout. In this phase, the review protocol, the selection requirements for potential studies and the method for analyzing the content of the selected studies were provided. The classification presented in section 3 allowed answering the main research question. What are the aspects considered in the prediction of university student desertion through data mining? Findings: University dropout is a problem which affects universities around the world, with consequences such as reduced enrolment, reduced revenue for the university, and financial losses for the State which funds the studies, and also constitutes a social problem for students, their families, and society in general. Hence the importance of predicting university dropout, that is to say identify dropout students in advance, in order to design strategies to tackle this problem. Novelty /Improvement: This is the first work to perform an integral systematic literature review about university dropout prediction through data mining, with studies from 2006–2018. Keywords: Data Mining, Dropout Factors, Dropout Prediction, Machine Learning, University Student Dropout

Exploiting the Local Optima in Genetic Algorithm using Tabu Search

Abstract: Objectives: To explores the process of selecting retrieval schemes along with their weights, and fusion function for data fusion in information retrieval. Methods/Statistical Analysis: This has been carried out using the hybrid Genetic Algorithm. The fusion function, retrieval schemes and their weights lead to a tremendous combination. Finding an optimal solution from this great combination is entirely based on the exploration. Findings: We used, odd and even point crossover as an exploration tool. This exploration tool suffers a setback of slow convergence. The convergence rate can be improved by merging Tabu search, a best local search, with the genetic algorithm. This Tabu GA is used to select the retrieval schemes, weights and fusion function. The outcome of the experiments conducted over the test data sets namely: 1. adi, 2. cisi, and 3. cranlooks promising. We achieved 6.89% of improvement in performance, and the significance of the result is tested statistically. The convergence rate is also improved. Application/Improvements: We achieved 6.89% of improvement in performance, and the significance of the result is tested statistically. The convergence rate is also improved. Keywords: Genetic Algorithm, Information Retrieval, Odd and Even Point Crossover, Tabu GA, Tabu Search

Measuring Sentences Similarity: A Survey

Abstract: Objective/Methods: This study is to review the approaches used for measuring sentences similarity. Measuring similarity between natural language sentences is a crucial task for many Natural Language Processing applications such as text classification, information retrieval, question answering, and plagiarism detection. This survey classifies approaches of calculating sentences similarity based on the adopted methodology into three categories. Word-to-word based, structurebased, and vector-based are the most widely used approaches to find sentences similarity. Findings/Application: Each approach measures relatedness between short texts based on a specific perspective. In addition, datasets that are mostly used as benchmarks for evaluating techniques in this field are introduced to provide a complete view on this issue. The approaches that combine more than one perspective give better results. Moreover, structure based similarity that measures similarity between sentences’ structures needs more investigation. Keywords: Sentence Representation, Sentences Similarity, Structural Similarity, Word Embedding, Words Similarity

Sentiment Analysis of Students Comment by using Long-Short Term Model

Abstract: Objectives: Teacher’s evaluation in education system is quite important to improve the learning experience ininstitutions. For this purpose, sentiment analysis model is developedto identify the student sentiments from the piece of text. Methods/ Statistical Analysis: Long Short-Term Memory Model (LSTM) is used for analyzing the sentiments expressed by students through textual feedback. For this purpose, dataset has been built through student’s feedback and then divided into 70% and 30% for training and testing. The proposed model has been trained using softmax and adam along with drop out values 0.1 and 0.2. Obtained results showed that our model provides 99%, and 90% accuracy over training and validation with 0.2 and 0.5 losses respectively. Findings: It was found that proposed model provides an efficient way for sentiment analysis for teacher’s evaluation. Model used input as word embedding over the LSTM for mapping the words. Andmoreover, the model is collected significant semantic and syntactic information by implementing pre-trained word vector model. Hence, this model has the prospective to overcome several flaws in traditional methods e.g., bag-of-words, n-gram, Naive Bayes and SVM models where order and information about word is vanished. The experimental results show that the model can achieve state-ofthe-art accuracy on student feedback dataset. Application/Improvements: The study helps for improving the quality of teaching in education system. And moreover,it will be upgrade by increasing the data samples of neutral comments in dataset. Keywords: Course Evaluation, Opinion Mining, Sentiment Analysis, Student’s Feedback, LSTM, RNN

Abusive Language Detection: A Comprehensive Review

Abstract: Objectives: To provide an organised literature on the detection of Abusive language on Twitter using natural language processing (NLP). Methods: In this study, the survey has been conducted on different methods and research conducted on the types of Abusive language used in social media, why it is important? How it has been detected in real time social media platforms and the performance metrics that are used by researchers in evaluating the performance of the detection of abusive language on Twitter by the users. Results: Giving an organised review of past methodologies, including methods, important features and core algorithms, this study arranges and depicts the present condition about this area. The study also talks about the intricacy of hate speech idea which is characterised in numerous stages ad settings. This area of study has an obvious potential for societal effect, especially in digital media and online networks. A crucial step in propelling automatic hate speech detection is the advancement and systemisation of common assets, for example, clarified data sets in numerous dialects, rules, and calculations. Conclusion: This survey study contains all the relevant references related to detection of abusive language on social media using NLP and machine learning methods. Ultimately, it can be as source of references to the other researchers in finding the literatures that are relevant to their research area in the detection of Abusive language on Twitter. Keywords: Abusive Language, Natural Language Processing, Social media analysis, Text Classification and Analysis

Investigation of a Brain Cancer with Interfacing of 3-Dimensional Image Processing

Abstract: 3dimensional image analysis (3-D) provides an effective way to quickly and accurately evaluate complex interactions and functions between neurons. Method of identification based on the neuronal program. Other computerized image processing frameworks, for example, information matching systems, produce comparable rays. For the most part, the issue of brain tissue on the same side of the head heated (heat shock proteins) due to glucose is more than the tissue on the other side of the brain. In this study, causes of brain tumors (cancer) due to the increase in glucose metabolism are still unknown. Our research area focuses on paper tumors and oral tumors that develop slowly on the side of the brain. The objective of the study is to address the above problems associated with brain tissues. Our research focuses on how to reduce the impact of cancer and increase human life with the help of chemotherapy and how to identify the 3dimensional segmentation process. In this research work, the author works on brain cancer and apply a statistical model to the tests and discuss brain tumor images that are created using MATLAB software. It then describes the solution from the medical point of view and application and gives a prediction about the future resulting from the modified technology.

Facial Expression Recognition with Histogram of Oriented Gradients using CNN

Abstract: Objectives: A new method is introduced in this study for Facial expression recognition using FER2013 database consisting seven classes consisting (Surprise, Fear, Angry, Neutral, Sad, Disgust, Happy) in past few decades, Exploration of methods to recognize facial expressions have been active research area and many applications have been developed for feature extraction and inference. However, it is still challenging due to the high-intra class variation. Methods/Statistical Analysis: we deeply analyzed the accuracy of both handcrafted and leaned aspects such as HOG. This study proposed two models; (1) FER using Deep Convolutional Neural Network (FER-CNN) and (2) Histogram of oriented Gradients based Deep Convolutional Neural Network (FER-HOGCNN). the training and testing accuracy of FER-CNN model set 98%, 72%, similarly Losses were 0.02, 2.02 respectively. On the other side, the training and testing accuracy of FER- HOGCNN model set 97%, 70%, similarly Losses were 0.04, 2.04. Findings: It has been found that the accuracy of FER- HOGCNN model is good overall but comparatively not better than Simple FER-CNN. In dataset the quality of images are low and small dimensions, for that reason, the HOG loses some important features during training and testing. Application/Improvements: The study helps for improving the FER System in image processing and furthermore, this work shall be extended in future, and order to extract the important features from images by combining LBP and HOG operator using Deep Learning models. Keywords: Deep Learning, Emotion Recognition, Facial Expression, CNN, FER, HOG

A Taxonomy of Virtualization Security Issues in Cloud Computing Environments

Abstract: Objectives: To identify the main challenges and security issues of virtualization in cloud computing environments. It reviews the alleviation techniques for improving the security of cloud virtualization systems. Methods/ Statistical Analysis: Virtualization is a fundamental technology for cloud computing, and for this reason, any cloud vulnerabilities and threats affect virtualization. In this study, the systematic literature review is performed to find out the vulnerabilities and risks of virtualization in cloud computing and to identify threats, and attacks result from those vulnerabilities. Furthermore, we discover and analyze the effective mitigation techniques that are used to protect, secure, and manage virtualization environments. Findings: Thirty vulnerabilities are identified, explained, and classified into six proposed classes. Furthermore, fifteen main virtualization threats and attacks are defined according to exploited vulnerabilities in a cloud environment. Application/Improvements: A set of common mitigation solutions are recognized and discovered to alleviate the virtualization security risks. These reviewed techniques are analyzed and evaluated according to five specified security criteria. Keywords: Challenges, Cloud Computing, Security, Taxonomy, Virtualization

The Impact of Management of Information Communication Technology (MICT) on Society- International Conference on Communication, Management and Information Technology- ICCMIT 2019, Vienna, Austria

Abstract: The 5th edition of International Conference on Communication, Management and Information TechnologyICCMIT 2019, held in March 2019 at Vienna, Austria has been organized by Universal Society for Applied Research (USAR) Prague, Czech Republic Europe. ICCMIT 2019 covers a wide area of communication, management and information technology with the theme \"Impact of ICT on Society\". Several research outcomes emanated from different continents such as Asia, Europe, Middle East, and America were taken for discussions. More than 100 full papers were submitted for the special issue. After an extensive peer-review process, 23 papers were finally selected for publication. The current special issue consisted of areas viz. knowledge sharing, big data, E-commerce, and IoT challenges. *Author for correspondence 1. Overview of the Conference Discussions In 1 made investigations to uncover the relationship of inspiration to variables of characteristic and outward learning sharing among representatives of Saudi Arabia’s Public Sector. The examination was led on a basic arbitrary example of (400) local officials. The poll was utilized as a primary instrument for this examination. The investigation supposed that there is a connection among inspiration and interior components of information sharIndian Journal of Science and Technology, Vol 12(18), DOI: 10.17485/ijst/2019/v12i18/144599, May 2019 ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 ing, most quite (great relations among representatives, trust, achievement of work and trustworthiness). The investigation likewise found a connection between the techniques for inspiration and the components of outside information sharing, most outstandingly (equity, consolation and backing, worker’s interest in basic leadership, and professional stability). In 2 investigated information sharing among workers of Saudi Arabia’s administration/open part and the most conspicuous strategies (procedures) of sharing their

Multi-Tier Hybrid Feature Selection by Combining Filter and Wrapper for Subset Feature Selection in Cancer Classification

Abstract: Objectives: We have implemented a bio-inspired algorithm, particle swarm optimization method of miRNA subset selection to indentify the irreverent and redundant miRNAs for proper assessment of cancer diagnosis. Methods/Statistical Analysis: In this study we develop a creative multitier framework for subset selection to improve accuracy of caner classification. In the first tier we have used different filter methods to rank miRNAs according to their class relation then using union operator we have created a combinational model (Second tier) which consist of top ranked features of individual filter methods. Here the miRNAs are indentified according to their ranking with the threshold value defined. In third tier (feature pre selection model) improvised competitive swarm optimization algorithm is used to generate feasible optimal subset from the generated weighted miRNA in second tier to detect the biomarker gene for cancer detection. To minimize the gap between exploration and exploitation we have used Mamdani Fuzzy interference system. All selected genes from the fourth tire (feature reselection) is classify with classifier such as KNN. Findings: The objective has successfully achieved by implementing improvised competitive swarm optimization technique. Experimental result demonstrated that the proposed ICSO-KNN performs better than other method like PSO, PCA and PSO-KNN. ICSO-KNN outperformed with less error and larger amount of new solutions. Application/Improvements: We have four tier frameworks as an efficient feature selection algorithm which outperforms better. This approach may help to use any other metaheuristic feature selection to solve multimodal subset problem. Keywords: Filter, Mamdani, Wrapper, ICSO, KNN

Date Fruit Recognition using Feature Extraction Techniques and Deep Convolutional Neural Network

Abstract: Numerous biotechnology software applications are developed to provide computational solutions to complex agricultural problems like identification of diseases and monitoring plant growth. Dates are healthy fruit and its contribution in total G.D.P of Pakistan is approximately 4% in which District Khairpur provides approximately 81% production. Approximately 22 types of Dates are produced in different areas of Pakistan. It is observed that national as well as international emptor are unable to correctly identify the type of dates. Objectives: This study aims to presents a framework for recognition of Dates using Deep Learning technique based on color, shape and size feature extraction methods. Methods: We have established fruit images dataset of 500 images for evaluation purpose likewise 360-dataset. Three types of Dates were selected for experiments like Aseel, Karbalain and Kupro. The range of 500date fruit samples were collected out of which 350 used for training dataset and 150 used for testing purpose. Findings: Experiment performed on the selected samples following the proposed framework. For better accuracy, we have used combination of several hidden layers and 100 epochs which gives the best performance result of 97.2% at 4th epoch. A confusion matrix is used to analyze and measure the results accuracy through which we get 89.2% as a True Positive. Application and Improvements: The outcome will be beneficial for the emptor, researchers and also for automated factory classification. Keywords: Biotechnology Applications, Color Feature Extraction, Confusion Table, Dates

Work Engagement: Trust and Respect to Engage your People

Abstract: Objectives: The purpose of this study is to examine the impact of interpersonal relationships (i.e. respect and felt trust) on work engagement among employees from the manufacturing sector in Jordan represented by a critical Oil and energy supply company; Al-Manaseer Group in Jordan. The study attempts to uncover the impact of procedural justice on employees’ work engagement. Methods/Statistical Analysis: Data collected from 181 respondents were analyzed using SEM/Amos for data analysis, conformity factor analysis, path analysis, regressions and correlations. Findings: Results indicated that respect that employees receive from their managers and employees’ felt trust positively affected their work engagement. Both mediated the relationship between procedural justice and work engagement and felt trust mediated the relationship between respect that employees receive from direct manager/supervisor and job engagement. The results also revealed that procedural justice has a positive effect on perceived respect from their direct manager/supervisor, withan also positive effect on employees’ felt trust. Application/Improvements: Empirical study serves manufacturing organizations and hence its findings may provide a better understanding of the impact of respect, trust and justice on employees’ work engagement. Thus, effective interpersonal relationships may further predict significant organizational consequences that require further research and analysis. Keywords: Felt Trust, Procedural Justice, Respect, Work Engagement

Prompting Cost Overrun Factors during PCP in Construction Projects

Abstract: A construction project involving Public capital normally goes through serious problems and challenges of cost overrun. This issue if addressed at pre-construction planning phase can reduce various problems of budget overrun. Objectives: The aim of this research study is to explore the most critical factors of cost overrun in construction projects of Pakistan during Pre-Construction Planning (PCP) phase. Methods/Statistical Analysis: A structured questionnaire was designed for data collection. A total of 110 questionnaires were distributed among construction firms located in Pakistan which were analyzed statistically to determine significant factors. Statistical Package for the Social Sciences (SPSS) version 24.0 was used to find out the critical factor of cost overrun in construction project of Pakistan during PCP phase through relative importance index method. Findings:The research concludes that top most critical factor of cost overrun during PCP phase of construction projects are, wrong or improper design, inaccurate estimation, variation in scope of work, poor resource management and change of orders. Application/Improvements: This research is a step towards reduction of cost overrun issues in construction projects. Keywords: Cost overrun, Construction Project, Importance Index (RII), Pakistan, Pre-Construction Planning (PCP) Relative

Student Feedback Sentiment Analysis Model using Various Machine Learning Schemes: A Review

Abstract: Objectives: The study has been carried out to present the sentiment analysis model for improving the quality of teaching in academic institutions, particularly at universities. The purpose of this study is to explore the different machine learning techniques to identify its importance as well as to raise interest in this research area. In this regard, the student feedback dataset has been collected at the end of the semester Fall-2018 from both Public and Private sector universities of Karachi, through the Google Survey Forms. The dataset contains valuable information about the quality of teaching and learning. Methods/Statistical Analysis: The model used the Multinomial Naive Bayes, Stochastic Gradient Decent, Support Vector Machine, Random Forest and Multilayer Perceptron Classifier. The result was analyzed through the evaluation metrics i.e. Confusion Matrix, Precision, Recall and F-score. Findings: It is found that the performance of MNB and MLP remained effective as compared to other approaches. It is recommended that MNB and MLP should be used in the research context for the classification of the text. It has great significance for future researchers in sentences and text classification. Application/Improvements: The study helps for improving the quality of teaching in education system. And moreover, it will be upgrade by increasing the data samples of neutral comments in dataset. Keywords: Course Evaluation, Machine Learning, Opinion Mining, Sentiment Analysis, Student Feedback

Implementation of Fourier Transformation with Brain Cancer and CSF Images

Abstract: Objectives: Medicinal images assume a key part in the diagnosis of tumors as well as Cerebrospinal Fluid (CSF) leak. In a similar way, MRI could be the cutting edge regenerative imaging technology, which permits an angle sectional perspective of the body, which gives convenience to specialists to inspect the affected person. In this study, the authors had attempted the strategy to classify MRI images (4-Dimensional) either at the beginning of production to have a tumor or even can be utilized for tumor recognition. The aim of the study is to address the aforementioned problems associated with the brain cancer due to the leakage of CSF. Methods/Findings: This research is to construct the research framework that can identify cancer damage area or be isolated from tumors and non-tumors quiet by using Fourier transformation. Another research tool, based on Fourier Transform, is the main mathematical method for frequency analysis and has extensive engineering and science applications. Because DFT is omnipresent, there has been extensive study of highways for the DFT account and active research has continued. Application: Several fast algorithms are provided by the DFT partitioning method. In this document, we provide DFT with two rapid implementation algorithms to assess their performance. This study helps the detection of brain cancer due to the process of interfacing the 4-D (4 Dimensional) image segmentation process and Fourier transformation. 4-D is followed by MATLAB software modeling techniques to measure the size of brain damage cells deep inside of CSF. These Methods of light fields can be useful for improving the quality of application editing segmentation and light field composite pipeline, as they reduce boundary artefacts. Keywords: Brain Tumor, Cerebrospinal Fluid, Fourier Transformation, Image segmentation, MRI

Wastewater and its Treatment Techniques: An Ample Review

Abstract: The prompt population increment, rapid urbanization of the cities and fast development of the industries leads the generation of much pollution in our atmosphere. Among the other pollutants; water pollution is one of the important issues for addressing seriously. Such pollution not only affects human health but also harmful for agriculture and the earth. Drinking safe and clean water is one of the rising problems around the globe. Various developed countries are utterly working for providing safe and clean water by treating the water. Such countries not only ground water treatment but also proper treatment of wastewater. There are various conventional and non-conventional wastewater treatment techniques. This research work highlights the issues of water, wastewater treatment and few conventional and nonconventional wastewater treatment techniques. More than 50 latest and critical articles relating to the subject area of this research work had been reviewed and also few web blogs has been used to address the challenges in the wastewater treatment. On the basis of reviewed material in this research work, it is concluded that drinking water shortage increased to scary level and needs serious address. Also non-conventional wastewater treatment techniques are more feasible than the conventional techniques. Among the other non-conventional techniques, the constructed wetlands are more beneficial for the wastewater treatment. Keywords: Constructed Wetlands, Conventional and Non-Conventional Treatment Techniques, Wastewater, Wastewater Treatment, Water

Barriers in Adoption of Building Information Modeling in Pakistan’s Construction Industry

Abstract: Building Information Modelling (BIM) is ubiquitous and one of the finest approaches in the construction industry of developing country such as Pakistan’s. But implementation in the mentioned country’s industry has been slow and numerous hindrances have been faced by the construction practitioners up till now. Objectives: This study aims to highlight barriers in adoption of building information modelling in Pakistan’s construction industry. Methods: Current research survey was undertaken in the entire country after a pilot study. Findings: The study revealing the barriers in adoption of BIM. Lack of Skilled personnel, Unwillingness to share Information between Stakeholders, Legal and Security Issues, High Cost of Implementation were the few important factors revealed. Though, the results vary due to the development level difference in every country. Application/ Improvements: Thus, this article adds in the literature the hindrances/barriers faced by the concerned industry and their significance level. Keywords: Barriers, Building Information Modelling (BIM), Construction Projects

Link‐level Performance Modelling for Next-Generation UAV Relay with Millimetre‐Wave Simultaneously in Access and Backhaul

Abstract: Objectives: The ultimate goal of this study is to explore, analyse, and evaluate the use of mm Wave in access and backhaul network simultaneously for the use of UAVs in Next-Generation Wireless Networks (5G). Methods/statistical analysis: Future wireless communication, especially the densified 5G network, will bring numerous innovations to the current telecommunication industry and will support a 100-fold gain in throughput, 100-folds in connection for at least 100 billion devices, and a 10 Gb/s individual user experience capable of extremely low latency and response times. In such scenarios, the use of Unmanned Aerial Vehicle (UAV) as Base Stations (BS) becomes one of the viable options for providing 5G services. Findings: This study analyses and describe the distinctive rich characteristics of mmWave propagation. Indepth literature review has been conducted. End‐to‐end equations have been derived for calculating power received by the end-user while getting coverage through amplify-and-forward UAV relay. Using ray racing simulator, effectiveness of diffracted, reflected, and scattered paths versus direct paths has been shown in tiny wavelength frequency band. Application/improvements: Huge continuous bandwidth availability in mmWave has increased its lucrativeness in radio communication. Smart integration of UAVs in 5G network needs efficient placement mechanism for providing blazingly fast wireless cellular network services. This fundamental study will facilitate further research in exploring UAV-supported 5G network at unparalleled mmWave frequency band. Keywords: Unmanned Aerial Systems (UAS), Unnamed Aerial Vehicle (UAV), Communication Resource Management (CRM), Edge Computing at RAN (EC-RAN), Core Network (CN), Customer Quality Experience (CQX), Free-space Optical Communication (FSO), Aerial Network (AN), Key Point indicator (KPI), Fronthaul (FH), Backhaul (BH)

Efficacy of Different Fungicides and Bio Control Agents Against Fusarium oxysporum, Causal Agent of Potato Dry Rot

Abstract: Objectives: To study the prevalence of potato dry rot in different vegetables markets. To evaluate the effect of Fusarium oxysporum on potato. To study the efficacy of different antagonistic agents and fungicides against mycelia growth of F. oxysporum. Methods/Statistical Analysis: Survey was done from different vegetable markets of Pakistan. Potatoes showing dry rot symptoms were collected and brought to Plant Pathology laboratory. Findings: Antagonistic organisms cause highly significant inhibition in the growth of F. oxysporum which was higher than 60%. Lowest growth of F. oxysporum was found because of an interaction of P. varioti (15.5 mm) and Paecilomyces lilacinus (16.75 mm). Both them cause 82.39% and 80.96% inhibition in the growth of targeted pathogen respectively. Whereas in case of interaction with T. harzianum and Trichoderma polysporum the growth of F. oxysporum was 22.00 mm and 27.75 mm, which is still significantly low as compared to the growth of F. oxysporum 88.00 mm in separate control plates. The growth of pathogen was inhibited by Paecilomyces spp. and mutual inhibition of both antagonist and pathogen at few mm was observed. Whereas, in the case of Trichoderma spp. pathogen and antagonist produce intermingled growth, the growth of the F. oxysporum was ceased and overgrown by antagonist. In-vitro amendment of fungicide in culture media inhibits the colony growth of F. oxysporum. Reduction in colony diameter of F. oxysporum was observed with the application of used antagonistic fungi. Application/ Improvements: These results can be used in the analysis and bio-control methods of Potato dry rot. Keywords: Bio-Control, Dry Rot, Fungicides, Fusarium oxysporum, Potato

Investigation of the Acceptability and Effectiveness of Academic Podcasts to College Students’ Scholastic Performance in Science

Abstract: Objectives: To evaluate the Acceptability and Effectiveness of Academic Podcasts in Science, an experiment was carried out to determine its effects in improving the academic performance of Second Year BSOA and BSBA students of PUPRagay. Methods/Statistical Analysis: The study developed a podcasts as teaching strategy in Biology for Reproduction, Respiratory system, and Heredity and Genetics that was evaluated by 10 science teachers as Jurors; and was laid out in quasi-experimental research design employing pre-test post-test control group, and taught in the following treatments: n1(Control group) -50 students; n2(experimental group) -50 students both with 25 males : 25 female students. Findings: Findings revealed that the researchers-made academic podcasts were Highly Acceptable in terms of objectives, content, language-level, time frame, and assessment; there was a highly significant improvement in the performance of the experimental group (Z = 10.980 > 0.001); and their performance highly differed with the control group (Z = 1.6606 > 0.001). The paper concludes that it can improve the academic performance compared with the students who utilized regular textbooks that can be used to change the shift toward e-learning in the Philippines basic education setting. The facts that improved academic performance of students was observed proves that academic podcasts can be used in teaching college science subjects, which points to more self-paced and self-directed learning which depend highly on the students’ exposure to the said technology. Application/Improvements: Generally, the use of academic podcasts in teaching tertiary science could highly improve students’ retention and comprehension, making them more competitive and knowledgeable of the important science concepts.

Personalized Mobile Learning System to Enhance Language Learning Outcomes

Abstract: Objectives: This study describes the development and evaluation of a personalized mobile language learning system to teach and improve spelling. Methods/Statistical Analysis: The design process consisted of two stages: the first was directed by needs analysis sessions with a focus group of 5 language teachers. Next was analyzing the data collected during the previous phase and applied it to system design. It consists of: a practical component in which a learner can practice a specific spelling rule, and a game component where a learner plays a spelling game and scores her progress. Findings: The system adopts a personalized design approach allowing the instructor, or the parent, to add new spelling rules or new spelling words, which will be automatically embedded into both the practical and game components. The evaluation process involved testing the system on young students in classroom and home settings. Data were collected through observation and interview. Results indicated an overall positive attitude towards using the system. This study hopes to open a channel of communication that will facilitate development of systems that enhance learning outcomes among young learners using mobile gaming technology. Applications: Mobile application, Personalized android app. Keywords: Gasification, Language Teaching, Mobile Assisted Language Learning, Personalized Language Learning, Spelling

A Review on Electrical Characteristics of Nanofluid based Transformer Oil

Abstract: Objectives: To review the electrical property of different nanofluids such as AC/DC and impulse breakdown strength, partial discharge inception characteristic, dielectric loss factor and electrical resistivity. Methods: Dispersion of nanoparticles to host fluid is carried out by single-step and two-step methods to enhance the basic properties of nanofluids such as electrical and thermal conductivity, dielectric constant, denseness and relaxation time constant. Single step method follows the dispersion of nano particles into host fluid directly. In two-step method, dry powders of nano particles are prepared in first stage, which is dispersed to host fluid through magnetic stirrer or ultrasonic methods in second stage. Findings: The nanofluid in transformers can enhance the dielectric strength by almost 15-20% compared to mineral oil. The performance of the nanofluids under heavy electrical stress depends upon the types, volume fraction, shape and size of the nanoparticles dispersed in host fluid. The investigations conducted over the mixture of nanoparticles and transformer oil concludes that the electrical performance of the carrier oil is highly influenced by dispersing the nanoparticles of different varieties, mass and shape. The dispersion of nanoparticles will change the mode of ionization, reduces the formation of the electrons responsible for the breakdown, and thus delay the breakdown time. Applications: The excellent heat transfer and electrical isolation characteristics are the prerequisite of insulating liquids used in power transformers. Because of superior electrical and cooling performance of nanofluid compared to mineral oil at high voltage levels, the dielectric world has recognized the nanofluid as a promising insulating substitute for transformers.

Coolite and LINQ applied in the Development of a Web-based Operations Management System for the Crafting Industry

Abstract: Objective: To develop a Web-based Operations Management System, through technologies such as Coolite and LINQ, to systematically manage processes in the Crafting Industry. Methods/Analysis: As part of the software development methodology, XP (Extreme Programming) was used across all its phases. This allowed to clearly determining the necessary requirements for the development of an accessible, scalable and secure application (Web-based Operations Management System) that could fulfil all the functionalities raised by the stakeholders. Findings: The theoretical-scientific framework that supports the research, as well as the elements that allowed an appropriate development of the application, were established. Applications/Improvement: To improve processes within the Crafting Industry, a Web-based Operations Management System, based on technologies such as Coolite and LINQ, was developed. Inherently and more importantly, the application of these technologies allowed for a more accessible and adaptable user interface. Keywords: Coolite, Crafting Industry, LINQ, Management, Process

Relationship between Globalization and Environmental Degradation in Low Income Countries: An Application of Kuznet Curve

Abstract: Objectives: This study aims to check the impact of globalization and macroeconomic variables on environment degradation in low income countries. This study also tested the existence of Kuznets curve. Methods/Statistical Analysis: Greenhouse gases emission is used as proxy of environment degradation. Panel data was taken from 1996 to 2015 for Zimbabwe, Burkina, Uganda, Tanzania, Malawi, Mali, Guinea, Gambia, Madagascar, Central Africa, Niger, Burundi, Faso, Rwanda, Senegal, Mozambique and Benin. After checking the cross sectional dependence, Cross Sectional Augmented Dickey Fuller (CADF) panel unit root test is used to check the stationary of the variables then Pedroni Panel CoIntegration Test and Fully Modified Ordinary Least Square (FMOLS) are applied. Findings: Co-integration is found among low income countries. Globalization, urban population and renewable energy have positive effect on environment degradation while innovation index has negative effect on greenhouse gases emission. The inverted U shaped relationship is found between environment and globalization which means that globalization decrease environment degradation after reaching at specific level. Application/Improvements: To improve the environment, globalization should be increased continuously because after reaching at certain level, it will decrease the environmental degradation. Keywords: Environment Degradation; Globalization; Innovation Index; Kuznet Curve; Urbanization

Challenges of Implementing an E-learning Platform in an Internet Struggling Province in the Philippines

Abstract: Objectives: The recent improvements in the Philippine internet infrastructure by top internet service providers prompted the researcher to investigate the challenges and determine the level of acceptability in the implementation of an e-learning platform in the College of Computer Studies, Eastern Samar State University, Philippines. Methods/Statistical Analysis: Rapid Application Development model was used to develop and improve the e-learning platform. Descriptive statistics were utilized to analyze its over-all acceptability and a focused group discussion was done to determine the challenges they faced during implementation. Findings: Acceptability resulted in a grand mean of 4.67, interpreted as strongly acceptable. The result implies that the platform adhered to ISO standards in terms of its maintainability, efficiency, reliability, functionality, portability, and usability but a negative finding during the focused group interview was discovered. The interview indicated that a minimal number of students have internet access which impeded them from accessing the platform. Although an alternative locally hosted platform was provided, only a few number of the students can afford to buy devices that are needed to access the system. Application/Improvements: The e-learning platform can be utilized as an alternative learning platform. The system can also make the classroom more flexible by providing students remote access to learning materials Keywords: e-learning, Internet Infrastructure, Struggling

Biomonitoring of Heavy Metal Pollution by Bioluminescent Bacterial Biosensors

Abstract: Objectives: The current study focuses on the isolation of bioluminescent bacteria from the gut of Sea urchin and using its luminescence property as a potential biosensor for detecting chromium toxicity in water. Methodology: Bioluminescent bacteria, JAAKP J2 was isolated from the gut of Pseudoboletia indiana species of Sea urchin collected from Pondicherry university beach. The morphological, biochemical, enzyme profiling and molecular characterization through 16S sequencing were performed to identify the strain. Growth kinetic assays and spectrophotometric analysis under chromium stress condition were performed on bioluminescent strains for luminescence inhibition studies. The bioluminescent bacteria was then immobilized in nutrient agar cubesand used as a biosensor for the detection of hexavalent chromium concentration in water samples. Findings: The morphological, biochemical and molecular characterization revealed that the isolate JAAKP J2 was closely related to Vibrio campbellii. Industrially important enzymes like Protease, Lipase, Agarase, Cellulase, Xylanase and Gelatinase were also screened in this study. The developed biosensor using bioluminescence property of the isolate was able to detect the level of chromium toxicity in water samplesat concentration not more than 9 mg L-1 . Further we have elucidated a possible hypothetical pathway for reduction in luminescence property due to ROS (Reactive oxygen species) caused by hexavalent chromium toxicity in bacteria. Novelty: The study is first of its kind in isolation of bioluminescent strain from sea urchin and using it as a biosensor for heavy metal detection in water. Our study also throws lights on futuristic approach of detecting other heavy metals like lead, zinc, cadmium, mercury in water samples by bacterial luminescence. Keywords: Bioluminescent Bacteria, Biosensor, Chromium Toxicity, Enzyme Profiling, Sea Urchin

Economic Impact Assessment of Climatic Change Sensitivity in Rice-Wheat Cropping System of Pakistan

Abstract: Objectives: To measure the impacts of climate change sensitivity and how it is affecting economic conditions of farmers in current rice wheat cropping system. Methods/Statistical analysis: Cross-sectional data of 210 farmers from the seven different strata were collected from Punjab, Pakistan. Climate data of baseline (1980-2010) and future (2039-2040) under representative concentration pathways 4.5 and 8.5 for five global circulation models were collected from secondary sources. The climate scenarios were used in two crop simulation models, i.e., DSSAT and APSIM. Tradeoff Analysis Model for Multidimensional Impact Assessment (TOA-MD) was used for the economic analysis. Findings: The crop modeling results of the study using different GCMs and RCPs show that there was negative impact of climate change on the yields of both major crops i.e., rice and wheat. The comparison of both CSMs given the insight that the percent losses were higher in APSIM as compared to DSSAT. The economic analysis endorsed the negative impacts of climate change on farming community. The major economic indicators (net returns, per capita income and poverty) of the study area expressed the declining trend in both RCPs (4.5 and 8.5) and all five GSMs. The observed household vulnerability to climate change percentage was more intense in RCP 8.5 as compared to RCP 4.5, however, among GCMs the figures shown higher vulnerability in hot dry climate conditions and lower in cool wet. The poverty of the study area increased with climate change and it was more prominent while using RCP 8.5 as compared with RCP 4.5.The highest increase in poverty was observed using APSIM crop model for hot-dry conditions. Application/Improvements: The study concluded that to ensure food security, poverty alleviation and to minimize climatic risks there is the need to update agronomic practices and develop adaptation strategies. Keywords: Climatic Change Sensitivity, Economic Assessment of Climate Change, Pakistan, TOA-MD, Rice Wheat Cropping System

The Effect of Service Quality and Perceived Price Fairness on Consumer Loyalty through Consumer Satisfaction on Budget Hotel in East Java

Abstract: The purpose of this study was to determine and analyze the influence of service quality and perceived price fairness on consumer loyalty through customer satisfaction in budget hotels in East Java. This study of causality research uses a quantitative approach by testing hypotheses. In this study, the data will be tested using statistical formulas and using Structural Equation Modeling (SEM). The type of data in this study is quantitative data. The data source in this study is primary data. Data was obtained from questionnaires filled by budget hotel customers in East Java through surveys by distributing questionnaires to obtain data from respondents. The scale of data measurement used in this study is the interval scale that is one scale with the other scale has the same distance or size. The data measurement tool used is the Likert Scale. The research population refers to consumers who have stayed at budget hotels in East Java. Sampling is done using non probability sampling withdrawal techniques. The sample size in this study was 200 respondents with characteristics: a minimum age of 21 years and had stayed at a budget hotel in East Java at least more than once in the last 6 months. The results of the study prove that, first, service quality has a positive and significant effect on customer satisfaction (0.87, t-value 2.78). Second, perceived price fairness has a positive and significant effect on customer satisfaction (0.73 with a tvalue of 2.45). Third, customer satisfaction has a positive and significant effect on customer loyalty (0.98 and t value 3.69). Fourth, service quality has a positive and significant effect on customer loyalty through customer satisfaction (0.69 and the t-value is 4.04). Fifth, perceived price fairness has a positive and significant effect on customer loyalty through customer satisfaction (0.77 and the t-value is 2.11). Based on these results it can be concluded that if the budget hotel provides quality services and fair prices to its customers, consumers will be satisfied and eventually will be loyal to the budget hotel. Suggestions are proposed for the consumer loyalty theory learning to continue testing variables that affect consumer loyalty apart from the variables examined in this study, namely: service quality, perceived price fairness, consumer satisfaction, and consumer loyalty. Keywords: Consumer Loyalty, Consumer Satisfaction, Perceived Price Fairness, Service Quality

An Efficient Video Editing Application for Android based Technologies

Abstract: Objective: Smartphone industry is growing day by day.According to studies, maximum smartphone users watch videos on their smartphones.With the time, android operating system is becoming popular due to the applications which are based on android SDKsthat attract the attention of the mobile phone users. Methods: However, with the increase of its popularity video editing in android devices is becoming a complex task for many reasons as well like poor video quality after editing, slow editing process, editing tool crashes while editing etc. There is a need of an attractivetool and an efficient environmentto deal with such complex tasks. Findings: This study discusses the novel and easy-to-use interface of video editing in android devices. The developed tool can perform video encoding which generates number of frames per second. We have applied image processing techniques to add images or text to any frame of video and can apply different effects like covers, sepia, gamma, rotation, snow. Then the tool can regenerate video from the frames produced after editing and application of various effects. Application:The resultant video will be quality conscious and can be generated in multiple formats like MP4, 3GP, and MOV reliably. Keywords: Android Phones, Digital Video, Image Processing, Smartphones, Video Processing, Video Editing

Effects of Parent Attitude on Secondary School Students Academic Performance in Pakistan

Abstract: Objective: Parents played fundamental role for uplifting moral values, shaping personality as well as their academic attainment. Study was conducted to find out effects of parental attitude on students’ academic performance. Methodology: Population of the study comprised on all public and private sector teachers teaching secondary classes and parents of students studying in Sahiwal division educational institutions at secondary level. Sample of the study consisted of 180 respondents (90 teachers and 90 parents) taken from 30 schools selected on random basis. Two types of research instruments (questionnaires and structured interview schedules) were developed and administered for getting required information. Findings: Parents’ positive attitude has positive impacts for uplifting academic performance of the children but their passive attitude becomes the cause of downgrading their academic performance. Their positive attitude provides love, security, simulation, encouragement and opportunities that help children to do well for producing good results. The study concluded that children who perceived their parents as loving, accepting, encouraging and less controlling behavioral and psychological less hostile perform better in school and feel more competent. Improvements: Parents are urging to get more involved in the monitoring, supervision and should provide moral and material support to pave the path for their children’s performance better in their learning. Keywords: Academic Performance, Attitude, Impacts, Loving, Secondary Level