bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data-Driven Neuroendocrine-PID Controller Design for Twin Rotor MIMO System
Authors: Ghazali M.R. , Ahmad M.A. , Raja Ismail R.M.T. 
Published: June 2020

Abstract
This paper presents the design of a data-driven neuroendocrine-PID controller based on adaptive safe experimentation dynamics (ASED) method for a twin-rotor MIMO system (TRMS). Neuroendocrine-PID is deemed a compatible controller, often due to its biological-inspired mechanism from a human’s endocrine system that promotes control effectiveness and accuracy. In assessing the robustness of the proposed controller, its parameters were optimized through the ASED method, by tracking both error and input control performances. In particular, the ASED method is a game-theoretic method that randomly perturbs several elements of its controller parameters to search for the optimal controller parameters. Comparison was further made alongside performance of a standard PID controller. Following the simulation conducted, findings with regards to total norm error and total norm input have hereby suggested neuroendocrine-PID as a better controller, following a 13.2% improvement in control accuracy to that of a standard PID controller for TRMS system.
Solar Burst Type II Structures from CALLISTO Database Affected by Coronal Mass Ejections Events Detected using LASCO/SOHO Satellite
Authors: Hamidi Z S , Shariff NNM 
Published: June 2020

Abstract
This paper explains the CME phenomena that connect with type II solar burst, focused on the velocity and structure parameters. The data collected were from CALLISTO and LASCO/SOHO satellite for a solar type II radio burst. Radio data presented was from different stations over the world which similarly occurred within 8 minutes to reach the Earth. The drift rate of this solar burst type II is linear to its CME velocity. The majority of type II burst has a drift rate of range 0.05-0.4 MHz/s which is considered as a slow drift rate. Both harmonic and Herringbone structure of type II has a slow drift rate which drifted from high frequency to lower frequency as time duration increases. Slow drift rate was a complement to the solar radio burst type II. Using LASCO data, there was a CME present during the time burst observed. The energy produced during CME phenomena was high enough to associate with burst type II. Herringbone structure of type II burst has variation in its CME velocity and is unpredictable which may have the extreme velocity or much slower velocity. The structure forms a single band which propagates from high frequency to lower frequency in time duration. However, for the harmonic structure of burst type II, the velocity of its associated CME has average speed of 300 to 600 km/s which normally. Thus, the behavior of type II burst needs to be well understood as it associated with the interaction of particles in CME phenomena.
Sustainable Competitive Advantage of Big Data Analytics in Higher Education Sector: An Overview
Authors: Muhammad R. N , Tasmin R. , Nor Aziati A. H. 
Published: June 2020

Abstract
The new technology paradigm of big data captured by flooded data from billion devices is the hottest buzzword trending in this 21st century. Big data is generated of data at high volume, high velocity, and in a variety of format that is complex (veracity) which necessitates analytical procedures and active management of data to extract meaningful insights. Similarly, big data is also known as a game-changer proficient of transforming the way businesses operate in different organisation for sustainable competitive advantage. This paper introduces an integrated overview of big data technology in the higher education sector and discusses how the application of big data analytics can create value for Higher Education Institutions to sustained competitive advantage. As the education sector is operating in an increasingly complex and competitive environment, given the growing advantage of the educational institutions as one of the sources of revenue that boost the economy.
Characteristics of Rainfall in Peninsular Malaysia
Authors: Muhammad N S , Abdullah J , Julien P Y 
Published: June 2020

Abstract
This study presents the rainfall statistics, conditional probability structure and statistical dependence of rainfall amount of several gauging stations located around Peninsular Malaysia, namely Subang, Senai and Kota Bharu. Daily rainfall measurements for all stations were collected from the Department of Meteorology, Malaysia are long and reliable, with at least 40 years of data. The average annual rainfall estimated for Kota Bharu, Subang and Senai are 2,627 ± 574 mm, 2581 ± 399 mm and 2499 ± 340 mm, respectively. The effect of monsoon seasons on the monthly rainfall amount is evident in this study. The most significant variation in the average monthly rainfall is noticed for Kota Bharu. There was some variation in the average monthly rainfall for Subang and Senai. The conditional probability structure for t-consecutive wet and dry days show that the multi-day events are time-dependent. For example, the probability of occurrence for a single dry day is 0.458, 0.453 and 0.553 and increased significantly to 0.696, 0.780 and 0.817 for 8-consecutive dry days at Subang, Senai and Kota Bharu, respectively. The dependence of rainfall amount was analyzed using the auto correlation function (ACF). The range of ACFs estimated for all stations were very low, i.e. 0.0050 to 0.0209, 0.0093 to 0.0857 and 0.0633 to 0.3700 for Subang, Senai and Kota Bharu, respectively. This result shows that the rainfall amounts are independent of each other. Overall, the analysis shows that the east coast region received more annual rainfall with higher variability, as compared to the central and south parts of Peninsular Malaysia. Additionally, the total amount of rainfall observed for all stations varies spatially and temporarily.
Evaluating Customer Trust towards Online SNSs sellers using Fuzzy AHP
Authors: Ramli Ramona , Ibrahim Ahmad Zulqarnain Mohamed , Bakar Asmidar Abu , Mohamad Abdul Hadi 
Published: June 2020

Abstract
Trust plays a vital role in social commerce due to the inadequacy of physical interaction and experience during the customer-seller transaction. Various studies were drawn in the literature targeting the investigation of the influence criteria related to trust using statistical analysis approach. However, little attention has been paid on the importance of the criteria in evaluating customer trust toward online sellers that used Social Network Sites (SNSs) as business platforms. In this study, the Fuzzy AHP (FAHP) method, an extension of the Analytical Hierarchy Process (AHP) was adopted to determine the importance of criteria in evaluating customer’s trust towards online SNSs sellers. The results of FAHP were then compared against the result of AHP, which both methods’ results similarities and differences were also presented and discussed.
Evaluation of thickness variation of recast layer formation on nitinol from electrical discharge coatings process
Authors: Mansor A F , Azmi A I , Zain M Z M , Jamaluddin R 
Published: June 2020

Abstract
Nitinol is an intermetallic alloy with outstanding properties that suitable as biomaterial. This alloy is capable of recovering to its initial shape after external loading through transformation of the crystalline structure. Unfortunately, excessive exposure of nickel element from this alloy is harmful to human body if released. Thus in this study, the alloy surface was deposited with an oxide layer via electrical discharge coating (EDC) process. The process was performed in deionized water and pure titanium as the electrode. The variation thickness of the recast layer formation was examined by analysing the effects of polarity, gap voltage and erosion depth. Single crater images and electrical waveforms were captured and utilised to elucidate the aforementioned effects. The results exhibited a significant change of layer thickness variation due to different polarity conditions. It was also confirmed that the single crater formation at different polarity was influenced by discharge energy. On other hand, the increase in the open gap voltage can expand the recast layer thickness in lower variation of reverse polarity condition. Finally, erosion depth attributed to a constant layer thickness but in low thickness variation when reverse polarity was employed.
Impact of cognitive and metacognitive strategies on learning performance in digital learning: What’s working and what’s not in the age of brilliant technology
Authors: Anthonysamy Lilian , Choo Koo Ah , Hin Hew Soon 
Published: June 2020

Abstract
Ineffective cognitive processes result in learning difficulties online. Hence, how cognitive learning processes influence the way students engage and learn online needs further investigation. This study, therefore, examined cognitive engagement and metacognitive knowledge strategies on learning performance among Malaysian IT Undergraduates. A sample of 563 IT undergraduates from private higher education in Malaysia participated in this quantitative study that were collected through a questionnaire. Data was analysed using PLS-SEM. The findings of this study constitutes essential results where all cognitive engagement strategies and two of metacognitive knowledge strategies positively influence the students’ perception of learning performance. Nevertheless, one metacognitive strategy resulted in a negative relationship with learning performance which have led to a new finding. This study concluded that the acquisition of cognitive and metacognitive skills are needed to excel in digital learning for deeper learning. Lecturers can use the findings of this study to integrate the necessary cognitive and metacognitive learning approaches across all key learning areas in the digital learning without altering the curriculum.
The Model of Fuzzy Logic in IoT System as Decision Support System for Determining Flood Disaster Status
Authors: Yuwono T. , Ruzardi  , Nordin R. , Mohamed R. , Ismail M. 
Published: June 2020

Abstract
Flood is the most frequent disaster in the world. The impact of floods is very large, like human and animal death, the villages vanished and other environments damaged. In disaster preparedness, it is very necessary to divide the stages of the disaster status level. Therefore the public can prepare themselves according to these stages. The stage of disaster preparedness status is also beneficial for the government and related institutions to act according to the status stage of the disaster. This paper will propose the early warning system for flood disaster based on fuzzy logic in IoT system. This algorithm was built 8 rules. The inputs are the rainfall and height of water. The output is the status of flood disaster. The types of disaster status are normal, moderate 1, moderate 2, emergency 1, and emergency 2. From the simulation result, it is concluded that this fuzzy logic model can to determine the status of flood disaster very well.
Optimization using Mahalanobis-Taguchi System for inductor component
Authors: Safeiee F L M , Abu M Y 
Published: June 2020

Abstract
The fourth industrial revolution (IR 4.0) is built upon the digital revolution where technology and people are connected. It does not just present modern techniques for supporting aspects within industry but cover as well the sustainability. Thus, it is very important for electric and electronic (E&E) industry to develop a new technique for a better quality evaluation of product. The aim of this work is to apply Mahalanobis-Taguchi System (MTS) in production environment at E&E industry for a better quality evaluation. MTS is used to classify normal and abnormal observations and optimize various parameters in workstation to produce a better quality product. This work found that positive gain through signal to ratio (SNR) indicated the quality of system still in good condition from February with 0.1244 until December with 0.4432 after insignificant variable have been removed. This work also suggested condition of core should be removed since the variable does not contribute to the system along 2018. Meanwhile, some variables are showed inconsistency of significant to the system such as wire condition, epoxy condition, lead part condition and soldering condition. This concluded that MTS is a practical method for classification and optimization in the industry.
A preliminary study on the uses of gadgets among children for learning purposes
Authors: Ali Zuraina , Anuar Ahmad Mahfuz Bin Mohamed , Mustafa Nurul Atikah Binti , Halim Khairun Nisa Binti Abdul , Sivabalan Kasturi 
Published: June 2020

Abstract
The study explores the uses of gadgets to assist young learners in their quest for learning. More specifically, the aims of the current study are to identify the gadgets that are used among children for learning purposes, hours they spend in using the gadgets, rules that are being implemented by parents for the uses of gadgets, benefits gain by children in the uses of the gadgets and parents’ expectations of the uses of the gadgets for learning purposes. The study that employs qualitative research among six respondents found that smartphones, tablets and computers were among the gadgets that were used by the children when parents permitted them to use the tools on average for three hours. It was also observed that some parents were rigid while some were lenient setting rules for their children to use the gadgets. Various perceived benefits were also demonstrated among parents. In terms of expectations, parents demonstrated some hope that the uses of the gadgets among their children would make the latter able to learn language, mathematics and social skills; to name a few. The study implies that parents need to control the uses of gadgets among their children even though the tools are used for learning purposes.
Seismic Analysis of Single Unit Tunnel Form Building Subjected to Out-of-Plane Lateral Cyclic Loading Using Ruaumoko 2D Programme
Authors: Shamilah A A , Faizah B N , Aweis A S , Mustaqqim A R 
Published: June 2020

Abstract
To date, frequent seismic events are seen to cause major destruction to the countries that are hit by great Earthquake with magnitude greater than 7 Scale Richter. These kinds of disasters are unpredicted and may give negative impacts for structures and human. However, the consequences of seismic can be mitigated by characterizing the hazard that might be affecting the existing structures. Therefore, the performance of tunnel form building (TFB) has been examined under various level of earthquake events. Ten numbers of ground motions are selected based on previous earthquake records to determine the level of safety of single unit tunnel form building (TFB). Four previous earthquake records are selected from countries outside of Malaysia, while the other six previous earthquake records are selected from East and West Malaysia. The prototype building has then been modelled and analysed to obtain the maximum lateral displacement and lateral loading capacity to assess the structural deformation of the TFB at peak ground acceleration for selected past earthquake history. From this analysis, the safety level of TFB under selected ten past earthquake records are investigated. It can be concluded that this type of building survives under local earthquakes but experienced severe damage or collapse under major earthquakes deriving from countries outside of Malaysia.
Uncorrelated Discriminant Projection Based on Maximum Margin Criterion and Its Kernelized Extension
Authors: Amin Muhammad , Ahmad Noor Atinah 
Published: June 2020

Abstract
A new linear dimensionality reduction algorithm called uncorrelated discriminant projection (UDP) is proposed in this paper. The proposed UDP algorithm is based on the maximum margin criterion (MMC) which aim at maximizing class separation after dimension reduction. By imposing an uncorrelated constraint in the objective function, UDP extracts statistically uncorrelated features which are important in many pattern recognition problems. Moreover, we propose performing UDP in reproducing kernel Hilbert space (RKHS) which leads to a nonlinear variant of UDP called kernel uncorrelated discriminant projections (KUDP). In order to demonstrate the effectiveness and efficiency of the newly proposed algorithms, we conducted experiments on two benchmark face databases. The experimental results indicates that both UDP and KUDP are able to find face subspaces optimal for recognition.
Performance Comparison of Machine Learning Algorithms for Classification of Chronic Kidney Disease (CKD)
Authors: Abdullah Azian Azamimi , Hafidz Syazwani Adli , Khairunizam Wan 
Published: June 2020

Abstract
Kidney is one of the vital organs in a human body while ironically, chronic kidney disease (CKD) is one of the main causes of death in the world. Due to the low rate of loss of kidney function, the disease is often overlooked until it is in a really bad condition. Dysfunctional kidney may lead to accumulation of wastes in blood which would affect several other systems and functions of the body such as blood pressure, red blood cell production, vitamin D and bone health. Machine learning algorithms can help in classifying the patients who have CKD or not. Even though several studies have been made to classify CKD on patients using machine-learning tool, not many researchers perform pre-processing and feature selection technique to obtain quality and dependable result. Machine learning used with feature selection techniques are shown to have better and more dependable result. In this study, feature selection methods such as Random Forest feature selection, forward selection, forward exhaustive selection, backward selection and backward exhaustive selection were identified and evaluated. Then, machine learning classifiers such as Random Forest, Linear and Radial SVM, Naïve Bayes and Logistic Regression were implemented. Lastly, the performance of each machine-learning model was evaluated in terms of accuracy, sensitivity, specificity and AUC score. The results showed that Random Forest classifier with Random Forest feature selection is the most suitable machine learning model for classification of CKD as it has the highest accuracy, sensitivity, specificity and AUC with 98.825%, 98.04%, 100% and 98.9% respectively which outperformed other classifiers.
The Use of Ontology in Clinical Information Extraction
Authors: Jusoh S , Awajan A , Obeid N 
Published: June 2020

Abstract
Extracting clinical data from medical or clinical reports is a crucial effort. These records contain the most valuable pieces of evidence of treatments in humans. Integration of information extraction (IE) and ontology can produce a great tool for clinical concept extraction. The aim of this paper is to present a quick overview of the research work which has applied IE and ontology approaches in medical or clinical concepts extraction. This paper also presents our proposed framework based on the integration of both approaches mentioned above for extracting clinical concepts.
Students’ Perceptions of Using Information and Communication Technology as an E-Learning Method
Authors: Halim H , Sulaiman N 
Published: June 2020

Abstract
Nowadays, ICT is used as a catalyst in e-learning to improve the quality of the teaching and learning processes. E-learning primarily incorporates interactive multimedia elements to involve and appreciate learners in the learning process. Multimedia applications provide interactive features, navigation, attract students and also help students to focus more during the learning process. This paper focuses on student perceptions of e-learning as a method of teaching and learning. The study sample consists of two groups of students: group A for traditional approach of learning and group B for e-learning approach. Moodle is used as a platform for e-learning. The research tool uses questionnaires and log data from the activity of Moodle. The questionnaire results are analyzed using SPSS software. From the analyzed data on student’s perception of traditional learning, 53% of students deny that this approach allows them to develop their current understanding of learning. 26.7% of respondents strongly disagree that content is appealing in traditional teaching delivery. A total of 55% of students agree to the use of multimedia e-learning to increase student understanding. Multimedia elearning was interesting and enjoyable to use, according to the findings, 75% of respondents agreed. The study shows that the student’s perception of multimedia e-learning helps to increase the student’s performance. The result has shown that students have demonstrated better learning performance through e-learning.
Widad Psychetra Door (WPD) as New Mobile Application (APPS)
Authors: Harun Siti Aminah Binti , Kasim Nur Muneerah , Jinnah Arifa Binti Mohd Ali , Fahmi Fajjar Binti , Sundaralinggam Navina AP , Khalili Danial Amin Bin , Firdus Fadhlin Mukhtarah Binti , Khair Nur Nabila Binti Sabahul , Noor Ain Aliya Binti Mohd , Saharudin Nurul Wahidatul Nasrah Binti 
Published: June 2020

Abstract
The purpose of this paper is to address the new invention - Widad Psychetra Door (WPD) on how re-generate low costing instrument of psychology games (combining perceptual illusions and active focus repetitive behavior) to Re-Instrumental Scale for basic Personality Test among teenagers’ personality. This study is conducted to identify the perception of the 10 adolescents from their own experiential testing of WPD. This research used a qualitative methodology through interviewed and data was analysed used content analysis with 10 respondents in age range between adolescent are 14 to 16 years old. The segmented difficulty level shape and vision experiences is based on five factor model (Agreeableness) and their satisfaction which segmented can be the best analogues in future application (apps) of WPD. The result shown the level of satisfaction is higher in third segmented and majority of respondents highly perceived this WPD can be applied as one of the application games (apps).
Selection of Optimal Ingredients for Out-of-furnace Smelting Based on Computer Application
Authors: He Yong 
Published: June 2020

Abstract
The optimization system software of the blast furnace batching studied in this paper is a complete set of blast furnace batching problem solutions. Its theory is based on the classic material balance and heat balance equations of blast furnace smelting. Blast furnace batching calculations used by most domestic steel companies are mainly based on forward calculation plus verification adjustment. Optimization of blast furnace batching based on linear programming the system can effectively improve calculation efficiency, and provide clear and unique optimization for blast furnace operators in all experience levels matching scheme.
An Extensive Research on Application of Interaction Design in Products
Authors: Wang Li 
Published: June 2020

Abstract
The human society has been ushered in an era of experience economy oriented by information products thanks to the booming of information technology since 1940s. The human society is featured by the fact that consumers begin to pursue spiritually satisfactory products rather than mass-produced products at functional and modelling levels. The so-called “experience” is what consumers seek for an emotionally and spiritually pleasing experience. Traditional industrial design concepts can no longer meet the needs of the customs nowadays, so new concepts to guide the design of products from the perspective of interaction are introduced by designers to solve the contradiction between customers’ need and products supplied. On the basis of the this background, this paper tends to discuss how interaction design can be applied in product development. The software and industrial products are in an attempt to provide inspirations into how to put this concept into practice.