bluuebunny/crossref_metadata_2025_split huggingface dataset:
Studying the Influence of Electroporation on HT29 Cell Line Interaction with Fibronectin and Collagen Protein Micro-Patterned Surface
Authors: Mamman Hassan Buhari , Jamil Muhammad Mahadi Abdul , Ibrahim Tengku Nadzlin Tengku , Wahab Mohd Helmy Abd , Sharif Johan Mohamad , Rahman Nur Adilah Abd , Youseffi Mansour , Javid Farideh 
Published: June 2020

Abstract
Micro-contact printing (MCP) is a scheme that allows a substrate or surface to be functionalized freely with extracellular matrix (ECM) protein such as fibronectin and collagen, in a well-defined manner. MCP can be used to regulate cell adhesion geometry on a substrate and in controlling wound healing process by facilitating directed cell migration. In this study, human colon cancer cell line, HT29 were grown on a micro-contact printed pattern of fibronectin and collagen protein with repeat gratings of 25μm, 50μm, and 100μm wide, for 48 hours. The cells alignments to the patterned substrates were then computed, where 0° means 100% alignment to the pattern. This was done with the purpose of finding those pattern that stimulated the best degree of cell alignment. Best alignment and elongation were obtained on 50μm of the two ECM proteins. The quantitative analysis of the results revealed that HT29 cells aligned most readily to the 50μm width pattern with a mean angle of alignment of 5.0° ± 1.3 and 16.1° ± 4.6, respectively, on fibronectin and collagen pattern surfaces. Contrarily, the cells aligned poorly on the 25μm width pattern of fibronectin, collagen and the control substrates with a mean angle of 33.4° ± 8.4, 36.2° ± 8.9 and 54.5° ± 6.0, respectively. Furthermore, the 50μm stamp pattern was used to investigate the influence of pulse electric field (PEF) on the HT29 alignment to the patterned substrate. The result revealed that there was significant improvement (P < 0.05) in the cell alignment between the electrically treated and the untreated cells. The alignment angles of the electrically treated cells were 4.0° ± 1.2 and 11.2° ± 3.5, respectively, on the 50μm pattern surface of fibronectin and collagen. Therefore, the result of the study revealed that micro-contact printing technique together with pulse electric field could offer a potentially fast method of controlling directed cell migration for wound healing application.
Development a new costing structure for palm oil industry using time driven activity based costing
Authors: Zaini S N A M , Abu M Y 
Published: June 2020

AbstractPalm oil is one of the agricultural commodities most marketable in the world. The Malaysian palm oil industry is undoubtedly the pride of the country. There are few problems in this plantation at present, which do not represent a time frame to measure operations deviation, a rate establishment did not properly explain the connection between supplied assets and functional capacity and a method for tracking unused capacity was not available to the manager. This work aims at developing a new costing model specifically for ramp areas for improved precision. Time-driven activity-based costing (TDABC) is introduced because it can measure time output effectively, correctly identify idle energy and separately list the unused capacity. Costing based on time activity has been implemented. It also offers a better understanding of operating instruments and associated costs when assessing processes and promoting improvements in quality. There are three main divisions in the plantation in Pahang. The maximum utilized ramp capacity and the level of capacity cost rate (CCR) were successfully established with 4800 minutes and 1.00 RM / minute respectively. Finally, the manager finds the unused capability that can be used to improve ramp-resource management on a regular basis. However, the unused capacity created in ramp activities is not present in this case study.
Development of paper based amperometric biosensor for glucose content measurement in Malaysian Stingless Bee Honey
Authors: Julika W N , Ajit A , Syazlin N. , Ariff A. , Naila A , Sulaiman A Z 
Published: June 2020

Abstract
Amperometric biosensor for glucose content measurement in Malaysian stingless bee honey was developed using screen printed carbon electrode (SPCE) integrated with paper disc immobilized with enzyme Glucose Oxidase (GOx) using simple physical adsorption method. The paper-based biosensor required only 8 μL of sample solution for glucose analysis. The calibration of glucose biosensor is linear between 0.5 mM to 4.5 mM (R2= 0.9925) and has a detection limit of 0.15 mM. Interference study on several compound affecting the biosensor response and storage stability was investigated. In addition, its performance was demonstrated in the analysis of six honey samples. The results obtained using glucose biosensor was validated by high performance liquid chromatographic (HPLC) method. The addition of glucose in pure honey at various concentration were also tested by this paper-based biosensor where the current obtained shows increasing trend with the addition of glucose. From this research, it can be concluded that, the prototype sensor to determine glucose adulteration in stingless bee honey was successfully developed.
Effect of TiO2 Nanofluid and Hybrid TiO2 Nanofluid on Mechanical Properties of Steels for Automotive Applications
Authors: Radhiyah A A , Nurziela K 
Published: June 2020

Abstract
Quenching is a process involving rapid cooling in quenching media and hardening of steels. The effect of quenching process on the microstructure and mechanical properties (hardness) are studied and elaborated in this thesis. The quenching media uses including conventional fluid (distilled water and mineral oil), nanofluid (TiO2 nanofluid), and hybrid-based nanofluid (TiO2 hybrid nanofluid). Thermal conductivity and microstructure development are closely-linked to each other. Conventional fluids as quenching media have low thermal conductivity thus limiting the development of desired microstructure in the steels. The thermal conductivity and stability of nanofluid and hybrid-based nanofluid are studied to enhance the thermal properties of the quenching media.
Electrocortical brain oscillations and social anxiety disorder: a pilot study of frontal alpha asymmetry and delta-beta correlation
Authors: Al-Ezzi Abdulhakim , Selman Nidal Kamel , Faye Ibrahima , Gunaseli Esther 
Published: June 2020

Abstract
The main objective of the present study is to investigate whether socially anxious individuals and healthy control show recognizable electroencephalographic (EEG) patterns in the frontal brain during baseline and recovery states. Towards this goal, this study recruited eight participants to examine the severity of social anxiety disorder (SAD) on EEG oscillations through the study of electrocortical frontal alpha asymmetry (FAA) and delta–beta correlation. A group of healthy male participants was chosen (consisting of 4 SAD and 4 HC individuals), and they were assessed by using Social Interaction Anxiety Scale (SIAS) to determine the level of social anxiety. Frontal EEG oscillations were measured to investigate the delta-beta correlation and frontal alpha asymmetry in baseline tasks (eyes opened and eyes closed) and recovery from social tasks (speaking in front of camera). As an outcome, Delta-beta coupling in SAD has shown greater correlation in baseline condition (eyes closed, and eyes open) than the recovery task, unlike HC individuals who exhibited greater correlation in recovery state more than baseline state. For frontal alpha asymmetry, SDA participant have shown greater left frontal cortical activity, whereas HC participants have demonstrated greater right frontal cortical activity. Taking all together, the reported findings indicate that delta-beta correlation and alpha asymmetry are presumptive EEG biomarkers of social anxiety.
Factorial Analysis of Biological Treatment for Contaminated Wastewater from Hatchery Industry
Authors: Zainol Norazwina , Jazlan Che Asilah Ilyana Che 
Published: June 2020

Abstract
The wastewater from a hatchery was dissimilar from a production farm in terms of quality and quantity of waste. The sources of wastewater were basically from uneaten food and fish feces. Biological treatment was a very promising process for removing dissolved organics from refinery wastewater. However, the low availability of clean water has become a critical issue to the shrimp grower. Further, carbon and phosphorus are the main constituents of most wastes, and removal of such elements from waste effluents can reduce the environmental stress and minimize ecosystem deterioration. The purpose of this study is to evaluate the factors affecting the removal of chemical oxygen demand (COD) and total phosphorus (TP) in the contaminated wastewater from hatchery industry. The factors were: ratio acclimatized mixed culture (AMC) to synthetic wastewater (SW) (1:3 and 2:3), the presence and absence of support media (Yes and No), agitation (0 rpm and 100 rpm) and retention time (4 days and 8 days). The responses were COD and TP removal. Design Expert software was used to construct experimental design where all the factor was randomized. As a result, ratio AMC to the SW, agitation and retention time were the most contributing factors to all the responses. The best conditions for the contaminated wastewater from hatchery industry were at ratio (1:3) AMC:SW, present of support media, 0 rpm agitation and 4 days retention time. At this condition the removal for COD and TP were 26.5% and 42.9% respectively. However, by separating the best condition for COD and TP, the removal can achieve 69% and 75.7% respectively. It can be concluded that the biological treatment using AMC can treat contaminated wastewater from hatchery industry.
Fish Larvae Counting System Using Image Processing Techniques
Authors: Awalludin E A , Wan Muhammad W N A , Arsad T N T , Wan Yussof W N J Hj 
Published: June 2020

Abstract
This paper presents the use of computer technology based on image processing techniques to count the number of fish larvae with less time processing. Computer technology used is as an alternative solution to the manual counting approach method in term of determination fish larvae survival rate, stock assessment and monitoring fish growth population. Generally, the fish larvae counting is performed with sequential process with laborintensive task which difficult to be used for counting large sample dataset. Traditional counting method has been used for many years, however many researchers highlighted several drawbacks of the manual counting process such as time consuming, laborious, required human skills-eyes, less-accurate, less consistent, difficult to estimate with many large sample and too many involve with human intervention. Since the problems is addressed, many researchers are interested to develop many techniques to facilitate the process of fish counting with fast assessment. In this study, we present combination of image processing techniques that consists of image enhancement, edge detection, and thresholding process. Meanwhile, the blob analysis is used as the statistical information to measure the objects properties in the image automatically. Total number of 150 samples dataset of Nile Tilapia (Oreochromis niloticus) were used in the experiment. All the samples are divided into three part which are small dataset (50 samples), medium dataset (50 samples) and large dataset (50 samples). The performance of the proposed method and the manual approach method are compared based on the number of fish that was successfully estimated and processing time taken through the experiment. All 150 samples of fish larvae were collected from the Freshwater Hatchery of University Malaysia Terengganu. The experimental results shows that the proposed method based on computer technology is outperformed compared to the manual counting approach in the experiment. This is because, the number of fish larvae measurement by using the proposed method is almost similar and some of samples present accurate result compared to the traditional approach. Moreover, the proposed method is promising on the processing time for measuring all samples with less time processing and more reliable.
Improved students’ performance prediction for multi-class imbalanced problems using hybrid and ensemble approach in educational data mining
Authors: Hassan Hasniza , Ahmad Nor Bahiah , Anuar Syahid 
Published: June 2020

Abstract
Among the problems raised in the data mining area, the class imbalance is a well-known issue that always occurs. Many researchers studied this issue in several fields using three commonly used techniques: sampling, ensemble, or cost-sensitive learning. However, such studies are still new in education domains. This problem always related to the quality of data that gives the most impact to form an accurate prediction result. Many previous studies focus on binary imbalance classification problems instead of the multi-class imbalance problem in education data. This study used 4413 student instances of two datasets; students’ information system and e-learning from the Faculty of Engineering in a Malaysia university for First Semester 2017/2018. Three sampling categories utilized in this study are oversampling techniques, undersampling techniques, and hybrid techniques. The research empirically analyzes five types of ensemble classifiers and seven sampling techniques. The experimental results show a hybrid technique ROS with AdaBoost produces the most excellent performance compared to the other benchmark techniques. SMOTEENN technique with ensembles classifiers consistently produces high results. This technique has great potential in improving the students’ performance prediction model.
Weighting Temporary Change Outlier by Modified Huber Function with Monte Carlo Simulations
Authors: Ghani I M Md , Rahim H A 
Published: June 2020

AbstractRobust method is a popular approach to dealing the existence of outliers in the data. Many researchers have applied Huber weight function. The aim of this paper is to evaluate the performance of the Huber weight function and the modification of the Huber weight function on the temporary change (TC) outliers. The data used in this paper were generated as ARMA(1,0)-GARCH(1,2) model via the Monte Carlo simulation. There are three major situations in this simulations: without weight (WW), with Huber weight (WH) and with a modified Huber weight (WMH). Three different TC contamination (0%, 10% and 20%) and three different time series length (100, 500 and 1000) were tested. The performance of the three situations was compared on the basis of AIC, SIC, HQIC, MAE, MSE and RMSE. The results of the numerical simulations show that the performance in the WMH situation is better than the WH situation in the presence of TC outliers.
A Mini Comparative Study of Requirements Modelling Diagrams towards Swimlane: Evidence of Enterprise Resource Planning System
Authors: Bakar Noor Widasuria Abu , Musa Shahrulniza , Mohamad Abdul Hadi 
Published: June 2020

Abstract
Model-based requirements engineering (MBRE) is an approach that empowers requirements engineers with adequate models to perform requirements engineering (RE) activities. This approach is increasingly becoming an essential part of system engineering projects as it reduces development time, enhances analysis capability and increases the potential for reuse. Use case diagram, activity diagram, business process management and notation diagram (BPMN) and swimlane diagram are among the diagram used in representing the requirements. However, the swimlane diagram has received little attention in the literature and lack of empirical support, particularly in the requirements engineering field. In this study, a multi-criteria comparative work is performed where three other diagrams are identified and examined against the swimlane diagram. Walkthrough sessions are conducted using enterprise application documents with real users to validate the model-based requirements exemplified using the swimlane diagram. These activities are carried out to highlight the efficacy of the swimlane diagram in representing requirements in the RE field. The results confirmed that the swimlane diagram outperforms NL in overall completion time for the requirement validation process. Furthermore, it gives users a better understanding as they did not need to read textual requirements which are typically ambiguous, confusing, and lengthy.
Investigation on the effect of the gap and size of the parasitic structure in multi-direction steerable antenna for WSN
Authors: Zainudin N A F M , Osman M N , Sabapathy T , Jusoh M 
Published: June 2020

Abstract
In this paper, a multi-direction steerable radiation pattern antenna is designed and investigated, which operates at 2.45 GHz frequency. The radiation pattern reconfigurable is achieved by locating the driven elements at the centre of the antenna that surround by four parasitic elements. The artificial switches, are currently inserted at the specific position on the parasitic element. The beam steering to be directed into four direction angles; right, left, upwards and downwards, by controlling the state of the switches, ON/OFF. In this research, an investigation on the effect of gap and the size of the parasitic on the steering angles has been carried out. With minimum numbers of switches deployed, the proposed antenna is a potential candidate to serve as a transmitting element in WSN applications.
An Experimental Framework for Assessing Emotions of Stroke Patients using Electroencephalogram (EEG)
Authors: Khairunizam Wan , Yean Choong Wen , Murugappan Murugappan , Junoh Ahmad Kadri , Razlan Zuradzman M. , Shahriman AB , Mustafa Wan Azani Wan , Ibrahim Zunaidi , Nurhafizah Siti 
Published: June 2020

Abstract
This research aims to assess the emotional experiences of stroke patients using Electroencephalogram (EEG) signals. Since emotion and health are interrelated, thus it is important to analyse the emotional states of stroke patients for neurofeedback treatment. Moreover, the conventional methods for emotional assessment in stroke patients are based on observational approaches where the results can be fraud easily. The observational-based approaches are conducted by filling up the international standard questionnaires or face to face interview for symptom recognition from psychological reactions of patients and do not involve experimental study. This paper introduces an experimental framework for assessing emotions of the stroke patient. The experimental protocol is designed to induce six emotional states of the stroke patient in the form of video-audio clips. In the experiments, EEG data are collected from 3 groups of subjects, namely the stroke patients with left brain damage (LBD), the stroke patients with right brain damage (RBD), and the normal control (NC). The EEG signals exhibit nonlinear properties, hence the non-linear methods such as the Higher Order Spectra (HOS) could give more information on EEG in the signal’s analysis. Furthermore, the EEG classification works with a large amount of complex data, a simple mathematical concept is almost impossible to classify the EEG signal. From the investigation, the proposed experimental framework able to induce the emotions of stroke patient and could be acquired through EEG.
D-Xylonic Acid from Recombinant E. coli BL21 (DE3): Comparison between Shake Flask and Benchtop Bioreactor Fermentation
Authors: Rodzri N A M , Zain W S W M , Hanapiah R M A , Samah R A , Illias R M 
Published: June 2020

Abstract
Production D-xylonic acid from recombinant E. coli BL21 (DE3) at a small scale has been successfully done several times. In an attempt to scale up the production process to a bigger scale, fermentation in bioreactor was conducted. The comparison on growth of recombinant E. coli BL21 (DE3) and production of D-xylonic acid in both shake flask and bioreactor was investigated. Higher specific growth rate of recombinant E. coli BL21 (DE3) and concentration of D-xylonic acid however, was obtained by fermentation in shake flask which is 0.273 h−1 and 9.06 gL−1
D-xylonic acid respectively. The result suggests several mistakes done during fermentation in bioreactor that causes low concentration of D-xylonic acid in bioreactor fermentation. Therefore, this calls up for improvement and better scale-up strategies in future work.
MOOC Student Learning Analytics For Automotive Technology Programme In Vocational College
Authors: Mazin Khairol Azwar , Norman Helmi , Nordin Norazah , Ibrahim Ruslina 
Published: June 2020

Abstract
This study aims to study the analysis of how students learning and see what they do in their Massive Open Online Course in the learning of Automotive Technology Course at Technical and Vocational Education Training institutions. This study used analytics tools, data and reports as part of an educational endeavor. At the beginning of each learning session, all students will be able to participate in this course. The participation of students enrolled in this large-scale course makes it challenging to help students individually achieve their learning objectives. Through the analytical features offered by the MOOC platform, it has made it easier for course coordinators and educators to view student learning activities in the online supplementary restraint system (SRS) course conducted through the MOOC. The findings of student learning analytics found that there are several types of learners and the tendency to follow learning by competency unit in online learning using open learning. Therefore, in this study, the analytical assessment of TVET student learning is used in achieving TVET course learning objectives. The use of learning analysis among TVET students can be used to observe interest and achievement in each unit of competency and identify students at risk during their learning process by analyzing student engagement on the page. By analyzing these interactions, learning analytics has the potential to provide predictive insights about future challenges. These predictions are used to evaluate the adaptability of the content presentation and improve the performance of the learning TVET MOOC process in the future.
Technology Integration in Implementing a Curriculum: Teachers’ Beliefs and Willingness to Change
Authors: Adnan Wan Ilmiwati Wan , Wahid Najihah Abd , Majid Norliana Abd , Jaafar Farah Wahida , Ismail Nor Asmawati 
Published: June 2020

Abstract
Teachers’ roles in implementing a curriculum is crucial in ensuring the planned curriculum is able to achieve its intended meaning. Accordingly, technology integration is considered essential as it perpetuates better learning outcomes for the learners. Specifically, embracing a new curriculum at classroom level requires teachers as its sole enactors to integrate any technology which accompanies an innovation. However, technology advancement does not confirm comprehensive integration. Subsequently, this conceptual paper tries to elucidate teachers’ willingness to change and beliefs as predictors to successful curriculum implementation where technology integration is involved. Findings indicate that these two constructs are able to manoeuvre teachers to implement a new curriculum in a successful manner when technology integration is involved.