bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of IOT for Human Safety on Road
Authors: Et. al. Tripura Pidikiti ,
Published: April 2021

Two wheelers (motor bikes) are most used easy and economic means of transportation and it also has become unsafe because of the tremendous increase of road accidents. When two-wheeler met with an accident, it is difficult to spot the neighborhood of the accident and mammoth loss occurs due to time factor. This paper presents Internet of Things based accident detection and prevention system. This is a novel system divided into four parts: first to identify the accident to send signal to emergency center along with location using Arduino based Global Positioning System and Global System for Mobile Communication and remaining are to warn to prevent the accidents like an accelerometer to determine the velocity and tilt of the vehicle, Infrared sensor to detect any obstacles and an alcohol sensor.
Scope for application of Topological spaces in Data Granulation through a new class of nearly open set Semi* Regular*- Open sets
Authors: Et. al. Basari Kodi K ,
Published: April 2021

The purpose of this paper is to define and study a new class of weaker form of regular*-open sets called semi*- regular*- open sets in topological spaces. Finally we conclude with the scope of this new class of open sets in applications of Data granulation.
Inventory Model with Demand Dependant on Unit Cost- Input Parameters as Triangular Fuzzy Numbers
Authors: Kasthuria R.
Published: April 2021

This paper considers an inventory model in which the shortages are backlogged and the demand is dependent on unit cost. An optimum value for average total cost is calculated by considering various input costs, lot size and maximum inventory under fuzzy environment. The process of defuzzification is done by using the signed distance method. Numerical example and sensitivity analysis is given for calculating both crisp and fuzzy values of the total cost.
Perspective Study of Fluid Dynamics towards Engineering Students: A Short Review
Authors: P Revathy.
Published: April 2021

In this paper we will deal about the importance of the study of the subject Fluid Dynamics in Engineering field. Students are more likely to study Engineering courses in the recent days. Engineering deals with the basic concepts of Mathematics, Physics and Chemistry. Though, Computer Science subject is a pulse to Engineering, the subjects, Mathematics, Physics and Chemistry are heart beat to Engineering courses. In this study, we will discuss where and how Fluid Dynamics stands as a crown to Engineering Field.
A Survey on Machine Learning and Text Processing for Pesticides and Fertilizer Prediction
Authors: Et. al. P.Pandiarajaa ,
Published: April 2021

In the Agriculture sectors the pressure is increased immensely due to the rise in population. In this present year we mainly witness a move from conventional methods to the advanced technology with advent of the technology. Machine Learning and Text Processing have transformed the quality and the quantity of agriculture. The real time monitoring systems along with hybridization of species paved away for resource efficiency. Scientists and researchers across the globe are mainly shifting towards collaborative projects and ideologies to explore this field for saving society. The optimal solution has been provided by racing in the tech industry. This application will be portable, scalable and durable that provides help for initiating new areas in the agriculture field. So, this survey focuses on machine learning methodologies along with Text Processing systems in agriculture. This startup’s private and public sector which is around the world that provides smart and sustainable solutions are briefly discussed. Based on agriculture this scenario, limitations, applications, development and future parameters are also briefly explained. The greatest challenge for the future agriculture lies in making agriculture research and extension more demand driven and client oriented. In addition, laboratory analysis has been undertaken to assess the nitrogen status and the soil carbon of fresh paddy soils and the used paddy soils as well as saplings. During the first season of 2011 the data collected on pests, disease incidence and severity and yield are being compiled for analysis. Therefore, integrated research to develop a bottom up participatory technology extension approach using new technologies is suggested for sustainable development in agriculture.
Enhancing the Authentication Scheme to Auditing the Cloud Storage and Security
Authors: Et. al. K. Deepa,
Published: April 2021

Cloud computing has become a reality with new IT infrastructure based on several techniques such as distributed computing, virtualization, etc. Besides the many benefits that they can offer, cloud computing also comes with the difficulty of protecting data security. This paper first explores the basic concepts and analyzes the main aspects of data security about cloud computing. We then look at each problem, discussing its nature and existing solutions, if any. In particular, we will pay special attention to protecting data confidentiality/integrity/availability, data access, and monitoring, and complying with rules and obligations to ensure data security and confidentiality. With the fast advancement of organizing and portable gadgets, we are confronting a dangerous incensement of swarm sourced information. Existing frameworks as a rule depend on a confided in server to total the spatio fleeting publicly supported information and after that apply differential security component to bother the total insights previously distributing to give solid protection ensure. We propose a Modified appropriated specialist based protection saving structure, called MDADP that presents another dimension of various operators between the clients and the untrusted server.
Onion Yield Prediction Based on Machine Learning
Authors: Et. al. A. Selvi,
Published: April 2021

Indian economy is mostly based on agriculture but the price of each vegetables and fruits varies in day today life. In recent days, the price of onion is increasing wisely, to predict the future price of onion by using past data and also the water level need for a particular crop using current dataset and also by using climate changes. Using Machine learning, collect the dataset of weather report and past and current priceof vegetables (e.g. onion) and water level prediction of plants. By analyzing these dataset the price of vegetables and the water level required for particular plant on particular day according to the climate change are analyzed and predicted. By using machine learning algorithm like Support vector machine, stemming, and tokenization. This will be helpful for the cultivators to crop a plant according to the weather and it will be useful when the water level needed for the particular plant is known previously. And these will also help to bring customer and farmer will gain more. The water level will also help to enhance the harvest yield and also will produce good crops all the time. The cultivator will gain more and the harvesting will also be more when compared to other systems.
A novel framework for synthesizing nested queries in SQL from business requirements language
Authors: Et. al. Mathew George,
Published: April 2021

Different methods and systems were proposed in the past for translating Natural Language (NL) statements in to Structured Query Language (SQL) queries. Translating statements resultingin‘nested’queries havealways been a challenge and was not effectively handled. This work proposes a framework for translating requirement statementsresulting inthe construction of nested Queries. While translating nested scenarios; often thereis a need to create sub-queriesthat execute inpipeline orin parallel or both operating together.Lambda Calculus is found to be effective in representing the intermediate expressions and helps in performing the transformations that are needed in translating specific predicates into SQL, but its inflexibility in combining parallel computations is a constraint. To represent clauses that are in parallel or arein pipeline,and to perform the required transformationson theintermediate expressions involving these,more advancedprogramming constructs are needed.This work recommends the use of advanced language constructs and adoptsfunctional programming techniques for performing the required transformation at the intermediate language level.
Analysis and Visualisation of Research Trends in Carbon Nano Tubes: A General Review
Authors: Kumar Raman
Published: April 2021

Carbon nanotubes are made up of carbon atoms, with each carbon atom covalently bonded to three other carbon atoms. The bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “Carbon Nanotubes”.  All published articles related to “Carbon Nanotubes” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps.This article had set the objective to consolidate the scientific literature regarding the “Carbon Nanotubes”and also to find out the trends related to the same.The most active journals in this research domain were Journal of Computational and Theoretical Nano Science; Journal of Physical Society of Japan and Journal of Power Sourceswith the highest publications, citations, and co-authorship links. The most active countries were India and Japan. The leading organizations were the Chinese Academy of Sciences, China, and the Islamic Azad University of Iran.The most active authors who had made valuable contributions related to Nanomaterial were Li X, Ajiki H, and Ando T.
Implementation and Analysis of Sentimental Analysis on Facial Expression Using HAAR Cascade Methods
Authors: Anand Dr. Darpan
Published: April 2021

The sentimental analysis is phenomenon of exploring, analyzing and organizing human feelings. It is a process of extracting feelings of human faro pictures. It involves the separation of image into various characters such as face, background, etc. It uses lips and eye shape for extracting human feelings. It uses numerous of applications such as Pycharm Numpy ,Open CV, Python,etc. Its main objective is to find out the moods of human such as happy , sad ,etc. This report generates the emotional state of human being as well as different emotion of human in different situation.
Wireless Sensor Network routing for Life Time Maximization Using ANFIS Based Decision with Low Power Consumption
Authors: Et. al. N. Srinivas Rao,
Published: April 2021

Wireless sensor networks (WSNs) allocate thousands of cheap micro-sensor nodes to a hundreds to more than thousands of nodes in the reserved areas. In the WSN, sensor nodes control storage resources, calculating energy of nodes, power resources of nodes, and additional resources information on a sensor network. These micro-sensor nodes are key components of the Internet of Things (). WSNs are pre-arranged in clusters or groups to protect the ability for efficient data communication. Strong routing methods are required to maintain long network life and achieve high power usage. In this work, the new energy efficient ANFIS-based routing system for WSN enabled  to improve network performance. The proposed ANFIS-based routing involves a novel distributed clustering mechanism that activates the local configuration of local node energy equally across all sensors. A new technique for replacing clusters and rotating nodes with a centroid-based cluster head (CH) to distribute loads. The simulation results show that the proposed program will surpass conventional methods with 78% improvement over the lifetime of the network and 26% improvement in performance.
Generating Matrices and Fibonacci-Like Numbers
Authors: Sivaraman Dr. R.
Published: April 2021

Among several classes of interesting numbers, Fibonacci numbers plays a significant role and these numbers very often turns up in several branches of Science, Engineering and Technology. Considering two by two square matrices whose entries are Fibonacci and Fibonacci like sequence numbers, we investigate the integral powers of such matrices and prove interesting results concerning them. Finally, the limiting cases of entries of nth power of such matrices are derived.
An Optimized Approach for Image Segmentation on Mobile Devices
Authors: Et. al. Hemantkumar R. Turkar,
Published: April 2021

Now a day’s image segmentation is widely used in many multimedia applications. We have introduced the optimized approach for image segmentation based on clustering for use on smart devices. The proposed optimized approach is based on the combination of partitioning of images using quad-tree and Ant Colony Optimization. This approach utilizes the strong ability of ACO i.e global optimization. The proposed optimized algorithm is evaluated on images of standard data set and its performance is compared with existing clustering algorithms. The qualitative and quantitative analysis has been performed to measure the efficacy of the optimized approach over conventional existing algorithms. This procedure obtains better quality results than existing clustering algorithms.
Feature Extraction In Gene Expression Dataset Using Multilayer Perceptron
Authors: Et. al. Nageswara Rao Eluri,
Published: April 2021

Numerous amount of gene expression datasets that are publicly available have accumulated since decades. It is hence essential to recognize and extract the instances in terms of quantitative and qualitative means.In this study, Keras is utilized to model the multilayer perceptron (MLP) to extract the features from the given input gene expression dataset. The MLP extracts the features from the test datasets after its initial training with the top extracted features from the training classifiers. Finally with the top extracted features, the MLP is fine tuned to extract optimal features from the gene expression datasets namely Gene Expression database of Normal and Tumor tissues 2 (GENT2). The experimental results shows that the proposed model achieves better feature selection than other methods in terms of accuracy, f-measure, precision and recall.
A Bibliometric Analysis and Visualisation of Research Trends in Toxicity of knee Implants
Authors: Singh Divya
Published: April 2021

Several metals are used for Knee implants. Toxicity of metals may lead to toxicity of knee implants. This bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “toxicity of knee implants”. All published articles related to “toxicity of knee implants” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps. This article had set the objective to consolidate the scientific literature regarding “toxicity of knee implants” and also to find out the trends related to the same. The most active journal in this research domain was Biomaterials. The most active country was the United States of America. The leading organization engaged in research regarding the toxicity of knee implants were the Indian Institute of Science, Bengaluru, India, University of Leeds, United Kingdom, and the Beihang University of China. The most active authors were Hallab N.J. and Jacobs J.J.
A Bibliometric Analysis and Visualisation of Research Trends in Allergy of Steel-implants
Authors: Ranjan Nishant
Published: April 2021

Steel is one of the most used metals for implants. The bibliometric analysis had been conducted to understand the active authors, organizations, journals, and countries involved in the research domain of “Allergy of steel-implants”. All published articles related to “Allergy of steel-implants” from “Scopus”, were analyzed using the VOS viewer to develop analysis tables and visualization maps. This article had set the objective to consolidate the scientific literature regarding “Allergy of steel-implants” and also to find out the trends related to the same. The most active journals in this research domain were the Contact Dermatitis, Injury, and Journal of Paediatric Surgery. The most active country was the United States of America. The leading organization engaged in the research regarding allergy of steel-implants were University Hospital in Munich and Ludwig- Maximilian University of Germany. The most active authors who had made valuable contributions related to the allergy of steel implants were Summer B. and Thomas P.
Organizational Effectiveness in both Private and Publish Sectors in Iraqi Kurdistan, the role of Organization Culture and Leadership will be investigated
Authors: Hassan Sardar
Published: April 2021

This study explores the organizational effectiveness in both private and public sector organizations in Iraqi Kurdistan and examines whether organizational culture types and leadership styles influence organizational effectiveness. For that reason, a deep literature review was developed on that past studies. By using Competing Values Model (CVM) data were collected and measured. In order to answer the research questions and test hypotheses independently a sample of 272 managers form distinct organizations in both sectors are chosen for this research and correlation coefficient test and regression analysis methods are used to test the relation. Moreover, organizational culture and leadership style were regressed on organizational effectiveness. Thus, the managers’ perception data indicate organizational effectiveness can be predicted by both organizational culture types and leadership style. Therefore, this author can conclude there is a positive relation between variables. The finding also shows that both independent variables can impact organizational effectiveness in public sector, while only leadership style can predict the dependent variable in private sector. At the end, some recommendations were proposed and further research in these areas was strongly advised
A Secure Methodology to Detect and Prevent Ddos and Sql Injection Attacks
Authors: Et. al. Leelavathy S,
Published: April 2021

As most of the applications host on cloud, Security is a major concern for the data owners. The cloud environment has to be secure and protect data owner data from cloud attacks. In this project work, we study about securing firewall against client side attacks namely Denial of firewall and SQL injection attacks. Denial of firewall is nothing but overloading the firewall by bursting n number of requests through vulnerable scripts. SQL injection attack is defined as bypassing the security protocols by malicious scripts. Thus we proposed to design and develop a web application to detect and prevent denial of firewall and SQL injection attacks.

The denial of firewall attack can be performed using Java environment based servers and prevention can be performed using Digital Signature Algorithm (DSA) in which filter based approach and software puzzle based approach are performed to detect the malicious script based requests. Once the Deep Packet Inspection (DPI): filter based approach and software puzzle based approach are find satisfactory only the request would be processed. If the request is find malicious automatically the requested IP address would be blocked. Various type of SQL injection attacks namely SQL login bypass, Blind injection, SQL sleep attack, Data fetching attack are analysed and performed. The SQL injection attack can be prevented using PREPARE statements. This statements are created to make the SQL queries more efficient and render security benefits. This statement provides effective prevention mechanism against SQL injection attacks. Thus our proposed solution, provides high security against firewall attacks namely denial of firewall and SQL injection securing the data owner files and preventing compromising of firewall
Biometric Based User Authentication and Privacy Preserving In Cloud Environment
Authors: Et. al. Jaichandran R ,
Published: April 2021

Cloud technology provides advantage of storage services for individuals and organizations thus making file access easy and simple irrespective of location. The major concern is the security while the file is been outsourced. Maintaining integrity, file unchanged, gaining confidentiality during file outsourced plays an important role. In this paper, we propose identity based data outsourcing technique to provide data security during authorization and storage. For data authorization we propose finger print based authentication. The fingerprint based authentication is performed using Minutae Map algorithm (MM). For data security we convert the data owner files to hash values using SHA algorithm. Finally in the cloud storage stage, data security and data availability is addressed using multiple cloud storage system.
Automated Bird Species Recognition System Based on Image Processing and Svm Classifier
Authors: Et. al. Chandra. B,
Published: April 2021

Here, in this study we can learn about Bird species recognition. In forest areas cameras are fixed at various locations which capture images periodically. From those images the birds living in such dense forest areas can be identified. It would be useful if we can able to classify the species of birds with the help of those images. But that is not an easy task because of the variations in the light effects, illumination and camera viewpoints. So we need to involve image processing techniques for preprocessing the captured image and also deep learning techniques are to be implemented for classifying the images. For classification purpose training is to be done with the help of image data set. Here we propose a method of discriminating birds by means of the ratio of the distance between eye and beak to that of the beak width. By combining this mythology with image processing and SVM classification technique a new bird species recognition algorithm is proposed. The proposed new methodology will improve the accuracy in classifying.
Comparing the Performance of Algorithm with Relevant Features for Histological Categorization of Lung Cancer
Authors: Et. al. V. NishaJenipher ,
Published: April 2021

Due to increasing cancer cases around the world, Lung cancer has become the favorite topic of research for a long period of time. The actual reason is due to the increasing rate of new cases across the globe. Therefore, many researchers used prediction or classification algorithm to identify the factors that contribute to the increase of this deadly disease. Two models were built namely WRF and RF. RF model provides the result of features selected by a predominant feature selection method whereas WRF model provides result of all features without performing any selection process. A comparison is made to inform the importance of selecting the feature for classification or prediction algorithm. The accuracy provided by WRF model is higher than RF model which highlights the importance of selecting the feature for classification algorithm.
Using Open Remote Sensing Data to build an Agriculture Big Data System
Authors: Et. al. Ancy Stephen,
Published: April 2021

Landsat, MODIS, and Sentinel satellites are continuously producing multispectral sensor data with different spatial, temporal, and radiometric resolutions. This raw sensor data is calibrated and processed further, and additional data products are derived, which greatly reduces the burden for downstream applications from preprocessing these data. These petabyte-scale datasets are available to anyone free of charge. Remote sensing plays a key role in modern Agriculture. We can extract information about Soil, Weather, Water, and vegetation from these datasets. By processing historical remote sensing data, we can build temporal profiles of soil, weather, water, and agricultural conditions of the land. Deep learning and Spatio-temporal data mining algorithms can be applied to this data to extract hidden information. Having access to all this information via an agriculture information system, farmers will understand their land better and they will be empowered to make better decisions on a day-to-day activity. Although it looks simple from the surface, collecting, analyzing, and deriving insights from these sensor data and other data products from a multitude of sources is a big data and high-performance computing challenge. In this paper, we discuss the current open datasets and how these datasets can be used to solve various problems in agriculture. Also, we discuss implementing a cloud-based scalable agricultural information system which provides actionable insights to farmers.
Comparative study of Existing Models for Online Social Network
Authors: Attri Vikas
Published: April 2021

Today, Online Social Networks becomes the first choice for businesses to broadcast their campaigns for branding, publicity, strategies, advertising, marketing, social influence and so many other areas. Social Network is a platform for communicating with social actors and Social Media is used by companies for broadcasting information. Online Social Network  used by businesses for number of purposes but the primary concern is build new social connections that helps to target most audiences for successful campaign purposes. In OSNs sites the social objects are represented by nodes and the term edge used for connection between nodes under the graph theory. Today Social Network sites have becomes most exploded as compared to traditional sites because of impact of so many influence models over traditional models.Some of popular websites of OSN such as MySpace, Facebook, Flickr, YouTube, Google Video, Orkut, LinkedIn, Live Journal and BlogSpot have great impact on customer when targeting the sales marketing funnel for businesses. Adjacent users sometimes called engaged users tend to have more trust level as compared to random pairs users on the social media sites. Already have so much research that helps to calculate the trust factor using influence modeling. So influence models play a vital role to predict the behavior of the customer that helps to fulfill the goal of the business. The key contribution of this work is study of online social networking models.
Impact Analysis of Machine Learning Techniques for COVID-19 Diagnosis: A Critical Review
Authors: Et. al. Anshul,
Published: April 2021

COVID-19 virus belongs to the severe acute respiratory syndrome (SARS) family raised a situation of health emergency in almost all the countries of the world. Numerous machine learning and deep learning based techniques are used to diagnose COVID positive patients using different image modalities like CT SCAN, X-RAY, or CBX, etc. This paper provides the works done in COVID-19 diagnosis, the role of ML and DL based methods to solve this problem, and presents limitations with respect to COVID-19 diagnosis.
Threshold Modeling of Basic Statistical Methods for Effective Motion Detection in Video Surveillance
Authors: Et. al. Surender Singh,
Published: April 2021

This paper empirical investigates two basic statistical methods namely Adaptive Median and Adaptive Mean for motion detection in video surveillance for the optimization of parameters namely threshold and the refresh rate of background frame used in these methods. Experimentation shows that the optimum choice of parameters majorly affects the quality of motion detection. The performance of methods for different parameters is measured using precision, recall  and f1-score. PR curves are also drawn which are based on precision and recall values to show the effect of different parameters. Test data includes six data sets from different scenarios of ‘CDNet2012’. Experimental results verify that for every method there are fixed values of parameters with slight variations which gives better result of object motion. These parameter values can be used or adapted for future experimentation on these methods with respect to each scenario.
Level of Awareness of Social Media Users on Cyber Security: Case Study among Students of University Tun Hussein Onn Malaysia
Authors: Et. al. Shahidah Hamzah,
Published: April 2021

The vast development of modern technology has resulted in a great impact on the life of children today and extended to teenagers group. This research was conducted to identify the level of awareness of university students on cybercrime. For this research purpose, the respondents involved were among the students of Universiti Tun Hussein Onn Malaysia, Pagoh campus. The total number of respondents that was targetted for this research was around 100 people. The instrument used was in quantitative form using questionnaire given to the respondents. The research outcome found that the level of university students’ awareness towards cyber security is at moderate level. Therefore, many proactive steps need to be implemented by the stakeholders so that issues that are relevant to cybercrime can be reduced and later be rid of.
Symptoms of Depression among Teenagers in Malaysia
Authors: Et. al. Intan Farhana Saparudin,
Published: April 2021

Depression is a psychiatric disorder that involves emotional disorders that often occur in Malaysian teenagers. Depression will cause a person to feel sad, tired, and angry, lose interest to do daily activities and tend to kill themselves. Depression can occur in male and female teenagers. It is often a sad feeling that occurs in a long period so that it can reach a period of two weeks. Symptoms of depression can be seen from the angle, cognitive, behavioural and physiology associated with each other in their daily lives. Teenagers are also not spared to face depression. In a variety of emotions facing teenagers, they face a variety of emotions that make them depressed and will result in depression. The objective of this article is to identify the symptoms of depression suffered by teenagers. To identify the objective of the content analysis method is done. The findings show that there are some symptoms of depression that cause discomfort and disrupt teenagers to function normally. The implication of the study giving knowledge about the symptoms of depression among teenagers and the kinds of treatment often used which are through counselling and psychotherapy.
The Link between Participation, Leadership, Social Capital and Personal Psychology with Economic Empowerment among Women Smallholder Groups in Malaysia
Authors: Ani Fauziah binti
Published: April 2021

Many developing countries turn to women groups as a way to empower women of similar socioeconomic backgrounds. In this regard, this research was conducted to study the relationship between the level of participation, leadership, social capital, personal psychology and economic empowerment among members of women smallholder groups. A total of 433 members of women smallholder groups involved in economic development activities were selected from four Peninsular Malaysia states covering four regions: south, east, west, and north. Through utilizing questionnaires, the results of this analysis were obtained and analysed with the Pearson Product Moment Correlation -SPSS. The findings show that these four independent variables are related moderately and highly to economic empowerment. Based on the study findings, it is possible to improve the economic empowerment of women smallholder groups by paying attention to those four variables.
Outsourcing Provider Selection Model in Public Sector
Authors: Et.al Glory Urekwere Orlu
Published: April 2021

In recent times, decision outsourcing IT activities in the public sector is fast evolving in the world at large. This fact has been considered as a high level of strategic measure used in different industries particularly in the public sector where internal IT expertise is found wanting in the area of implementing IT activities to improve the performance growth of the public sector. Although outsourcing IT activities are beneficial to IT Practitioners, Decision-makers, and heads of departments, but the fact remains that choosing the right IT Provider is still a challenge that is inevitable to be avoided as they continue to make the mistake of choosing the wrong IT Provider during outsourcing provider selection. This study considered mainly the approach undertaken towards achieving the key objective of this paper which is the development of the proposed model that can support IT practitioners in outsourcing selection practices. However, this paper considered an appropriate technique that can be implemented in an uncertain and complex situation.  Having reviewed thoroughly five existing techniques used in the prior researchers’ work, in-depth understanding on this justified that, fuzzy logic and its particular tools used Fuzzy Inference Systems (FIS) was found to be considered efficient and suitable for outsourcing selection practices in an uncertain and complex situation. Also, a pilot study and empirical study were conducted to ascertain the validity of the instruments (questionnaire data).  The pilot study consists of 33 respondents while the empirical study consists of 133 respondents.  Finally, the reliability test was carried out to determine the validity and reliability of the six influential factors selected, thereafter the proposed model was developed. The application of the developed Decision Outsourcing Selection Model (DOSM) will aid the IT Practitioners in their decision outsourcing Selection practices.
An Optimized DiscretizationApproach using k-Means Bat Algorithm
Authors: Et.al Rozlini Mohamed
Published: April 2021

This study has proposed arelatively new discretization approach using k-means and Bat algorithm in preparation phase of classification problem. In essence, bat algorithm is applied to find the best search space solution. Eventually, the best search space solution is utilized to produce cluster centroid. The cluster centroid is very useful to determine appropriate breakpoint for discretization. The proposed discretization approach is applied in the experiments with continuous datasets. Decision Tree, k-Nearest Neighbours and Naïve Bayes classifiers are used in the experiments. The proposed discretization approach is evaluated against other existing approaches: K-Means algorithm, hybrid K-Means with Particle Swarm Optimization (PSO) and hybrid K-Means with Whale Optimization Algorithm (WOA).The classification performance is evaluated in terms of accuracy, recall, f-measure and receiver operating characteristic curve (ROC).  To test the performance of the proposed algorithm, nine benchmark continuous datasets are used. The proposed algorithm show the better results compare to other approaches. The proposed algorithm performs better in discretization to solve classification problems.
Construct-Inference-Process (CIP) Framework for UX Model Building and EvaluationOver Time
Authors: Et.al Azham Hussain
Published: April 2021

This paper used a literature review strategy to investigate the approaches used in building user experience (UX) models and in evaluating UX over time. The paper reports that there is no uniform and consensus approach in the strategies used in developing user experience models and in evaluating UX over time. Researchers adopt divergent ways in building UX models and evaluating UX. This makes the development of a common approach difficult. It is also shown that there are three frequently employed approaches in the development of UX models and in the evaluation of UX over time. The three approaches are the construct, inference and process (CIP) approaches. The first two are associated with UX model development while the third is associated with UX evaluation over time utilizing the developed model. Researchers seldom use the three approaches combined together due to the rare use of longitudinal research in UX domain. Consequently, this paper strongly recommends and proposes the use of the combination of the three approaches to build UX models and to employ the developed model in evaluating UX over time.
Quality Facetsof a UX LMS Affective Model for the Design and Evaluation of Learning Management Systems
Authors: Et.al Azham Hussain
Published: April 2021

This study looked into extant literature to elicit a mapping relationship for the affective component of Bloom’s learning taxonomy and a theoretical affective model for the design and evaluation of the affective experiences of users of and learners on learning management system (LMS) platforms. The study found that no prior affective model exists specifically for the design and evaluation of the affective experiences of LMS users. The study then mapped the affective component of the Bloom’s taxonomy of learning with the conceptual affective model and captured corresponding suitable quality facets/dimensions that influence and contribute to the model. This model is particularly appropriate for the design and evaluation of the affectivity of LMS platforms.
Quality Attributes for UX Design and Evaluation
Authors: Et.al Azham Hussain
Published: April 2021

This paperutilizeda literature survey method to find out the quality attributes (or design factors) that impact on or contribute to user experience in extant literature. The results indicate that there areten dimensions that model UX.Each of these dimensions has associated quality attributes that contribute to it and influence the UX of interactive applications. The study therefore proposes the use of these dimensions and the related quality attributes in the development and modeling of the UX of interactive systems. Furthermore, these dimensions and attributes can be utilized in the design and evaluation of interactive digital artifacts.
The Effectiveness of Blended Project Based Learning Model in Power Electrics Practicum Course
Authors: Et.al Aswardi
Published: April 2021

This research was conducted since the students‘ learning outcomes on Electrics practicum learning process are not optimal and leads to the demand of active and innovative learning model. This research was performed using experimental method of one group posttest design. During the study, experimental class used Blended-project based learning (BPjBL) model. The research samples were the university students who enrolled in Power Electrics Practicum course in Electrics Engineering Major in Faculty of Engineering of UNP. The instrument used was the learning test outcomes. The research result proved that BPjBL learning model was classically effective and able to improve the students’ learning outcomes in Power Electrics practicum course.
Fuzzy-Based Trust Model to Evaluate Customer Trust towards Online SNSs Sellers
Authors: Et.al Ramona Ramli
Published: April 2021

The rapid growth of Social Networking Sites (SNSs) as business platforms for individual or small sellers recognised trust as the main important role in determining the successful execution of their business operation.Current trust modelfocused in business sellers by considering website as one of the trust factors.  However, these model are not applicable for SNSs environment. Based on the identified factors affecting trust in SNSs environment, this paper proposeda fuzzy-based trust model to evaluate customers‘ trust based on their perception and experiences.The evaluation model was then tested to validate its efficiency in evaluating trust level.
Towards Clasification Exploration in Spatial Crowdsourcing Domain: A Systematic Literature Review
Authors: Et.al Shirley Salimun
Published: April 2021

Today, spatial crowdsourcing concept has been widely applied in various fields. The increasing ofmobile user and adoption of social network has catalyst spatial crowdsourcing growth. It has madevarious types of data to be easily collected and transmitted from different geographical location.However, the massive amounts of task in spatial area bring challenges for the online system tomanage especially when the task is heterogeneous, and the interactions are dynamic. Such scenario

has alerted the researchers to understand different types of information in order to make taskassignment reliable and efficient.This study investigates current state of task assignment for spatialcrowdsourcing. It basically, aims to identify several issues like trend in publication and crowdcomputing areas that studies task assignment in crowdsourcing. We used Systematic LiteratureReview (SLR) method for analysing the trends and significance of task classification for betterdynamic crowd-computing.
Test Suite Reduction and Prioritization Framework in Regression Testing
Authors: Et.al Samaila Musa
Published: April 2021

Most of the test cases minimization reduced test cases during regression testing   to generate new test suite to cover the same software requirements.The objective of this paper is to present new framework that integrate the idea of minimization and prioritization.Hence, reduction and prioritization able to reduce test cases based on the statements covered by the previous test cases to avoid redundancy.Beginning from the reduction of the test cases, followed by  weighted prioritizationaccording to their usefulness.The  framework was tested using sample test suite and the results obtained shown increases on the average percentage  of faults detection (APFD). Future plan is to test on the larger size of test suite.
5E Learning Cycle: Enhancing Student Active Learning in Strategy and Marketing Analysis Class
Authors: Et.al Yaty Sulaiman
Published: April 2021

5E learning cycle is proposed to be a good choice for students’ learning and has brought a positive impact on students learning education theoretically and practically. This method of learning is a student’s centre oriented learning model which solely prioritize on students own experiences, creates active participation and built creative critical thinking skills. The elements of 5E learning cycle are engagement, exploration, explanation, elaboration, and evaluation. Research here intended to identify students’ perceptions of 5E learning cycles in their learning activity and to explore the impact of 5E learning cycles towards student’s active learning. The study was conducted at Universiti Utara Malaysia. This study uses qualitative approach with classroom action research. The discussion is based on the information gauged from 42 undergraduate students who enrolled in BPMM3043 Strategy and Marketing Analysis class in UUM. Data had been collected qualitatively from various sources such as students’ reflections, lecturer’s reflections, peer feedback, lecturer’s feedback, and focus group interview. The results showed that the 5E learning cycle mayenhanced students active learning in Strategy and Marketing Analysis class.
Chaotic Identification of Hourly and Daily Water Level Time Series Data in Different Areas of Elevation at Pahang River
Authors: Et.al Adib Mashuri
Published: April 2021

This study focused on chaotic analysis of water level data in different elevations located in the highland and lowland areas. This research was conducted considering the uncertain water level caused by the river flow from highland to lowland areas. The analysis was conducted using the data collected from the four area stations along Pahang River on different time scales which were hourly and daily time series data. The resulted findings were relevant to be used by the local authorities in water resource management in these areas. Two methods were used for the analysis process which included Cao method and phase space plot. Both methods are based on phase space reconstruction that is referring to reconstruction of one dimensional data (water level data) to d-dimensional phase space in order to determine the dynamics of the system. The combination of parameters  and d is required in phase space reconstruction. Results showed that (i) the combination of phase space reconstruction’s parameters gave a higher value of parameters by using hourly time scale compared to daily time scale for different elevation; (ii) different elevation gave impact on the values of phase space reconstructions’ parameters; (iii) chaotic dynamics existed using Cao method and phase space plot for different elevation and time scale. Hence, water level data with different time scale from different elevation in Pahang River can be used in the development of prediction model based on chaos approach.
The Impact of Entrepreneurial Orientation Success Factors To Muslim SME Success
Authors: Et.al NadratunNafisah Abdul Wahab
Published: April 2021

This study presentsa research of the multidimensional entrepreneurial orientation (innovation, risk and proactive) in relation to the Muslim SME success. Thus far, past literatures shown that limited study of Muslim SME success. This study was conducted in the form of survey, with data being gathered from 122 firms (operating above 3 years) selected through simple random sampling from 2286 Muslim SME in Malaysia. The results show that innovation and proactivefactors have relationshipsto SME Muslim success. The results shed new light on the theory and practice. This finding contributes to RBV theory and to the field of Islamic entrepreneurship focusing on Muslim SME success.
Factors Influencing Passengers’ Preference towards Public Bus Transportation from Kelantan to Northern Region
Authors: Et.al Mohammad Nizamuddin Abdul Rahim
Published: April 2021

A convenient and reliable transport system is integral for every country’s development and this study investigates the factors that influence passengers’ preference towards public bus transportation from Kelantan to Northern Region. The number of passengers who travel to Northern Region by public bus transportation is larger than using train and flight. This research adopted quantitative method where a total of 384 respondents who are using express bus to commute to their destinations. This study was performed in Kota Bharu, Kelantan using simple random sampling technique. The study tested the hypothesis that the factors are positively related to the passengers’ preference. The reliability and Pearson Correlation was also tested with the help of Cronbach’ Alpha. The findings of this study show that factorssuch as accessibility, convenience and safety, play considerable role in promoting the use of public bus transportation. However, the study revealed that price of the bus ticket was the leading factor that influence passengers’ preference. The results of this study will be helpful to the management of bus operators in their effort to continuously upgrade their services for their customer services and recommends that future studies should be conducted using a large sample size and also involve other bus transport service providers in other states or Malaysia as a whole.
Does Customer Knowledge on Islamic Financial Planning is Crucial for Islamic Credit Cards Users?
Authors: Et.al Azwan Abdullah
Published: April 2021

Credit cards is one of the popular products of the Islamic bank. Despite being a popular product, the demand for Islamic credit cards was very low correlated to the conventional credit cards despite its unique offering features to customers. The appointment of  a  trusted  Islamic Banking product is one of the steps to be considered in Islamic financial planning. The knowledge of Islamic financial planning plays a significant role in customer decision making regarding patronage. When making a purchase, it is important that customers completely understand products or services offered to ensure it followed the Shari’ah guidelines. Therefore, this study aims to investigate the factor of customer knowledge on Islamic financial planning that can influence customer satisfaction towards Islamic credit cards. The questionnaires were distributed by employing the convenient sampling technique and Statistical Package for Social Scientist (SPSS) is used to analyze the data that will be gathered. The result shows that the customer knowledge of Islamic financial planning has a significant relationship towards customer satisfaction of Islamic credit card.