bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determination of Geological Strike Based on Magnetotelluric’s Polar Diagram and Geological Condition in Tangkuban Parahu’s Geothermal Area
Authors: Hafidz Muhammad , Srigutomo Wahyu , Sule Rachmat 
Published: August 2019

Abstract
In geothermal exploration, magnetotelluric method (MT) has the capability to resolve conductive body which then can be interpreted as cap rock. A reliable representation of the Earth’s resistivity dimensionality can be achieved by incorporating the direction of geoelectrical strike and geological condition in the geothermal area. In this study, the magnetotelluric method was applied in Tangkuban Parahu volcanic area to reveal the subsurface structure of the area. Due to the uncertainty of MT modelling result, dimensionality analysis (polar diagram) is performed to find out MT data characteristic prior to MT inversion modelling. After that, lineament is mapped based on elevation map to estimate geological strike. Both methods are validated by geological condition in Tangkuban Parahu. The result of polar diagram analysis shows that the direction of geoelectrical strike is dominated NE-SW in mostly frequency and the result of lineament shows similar direction with polar diagram analysis as plotted in rose diagram yields about N45°E.
Geoelectric Strike Analysis from Magnetotelluric (MT) Data Using Swift and Polar Diagram Methods
Authors: Maulinadya S , Grandis H 
Published: August 2019

Abstract
The magnetotelluric (MT) method is commonly used to estimate the subsurface conductivity structure. From the point of view of computational resources availability, currently it is a common practice to perform a 2D MT inversion modelling of MT data measured along a profile. For that purpose, the geoelectric strike angle determination from MT data is essential. The geoelectric strike angle can be determined by rotational analysis of the MT impedance tensor. In this paper we compare geoelectrical strike angle from both Swift method and polar diagram analysis by plotting the results as rose diagrams. The results from rotational analysis suffer from 90° ambiguity in the structural direction. Along with information from the regional geology to resolve the ambiguity, the profile for MT 2D modelling can be more appropriately selected. We used MT data from a geothermal prospect to illustrate our exercise.
A Comparison Study of Carbonized Kapok Fibres Treated by Sodium Hydroxide Solution and Hydrochloric Acid Solution as an Absorbent in Removing Oil Waste
Authors: Ahmad Faisal Nik Mohd Azlin Shah Nik , Abdullah Mohammad , Azrul Aizad Mohamed Saadun Muhamad , Nurul ‘Ain Zaiton Siti , Amiza Azman Hairul , Che Lat Diana , Khudzairi Khalid Ahmad , Hambari Nurhaslina 
Published: August 2019

Abstract
Hydrophobic-oleophilic properties of Kapok (Ceiba pentandra) fibre enables it to show good oil absorption capacity. In this study, Kapok fibre was treated with two types of solvent which is Hydrochloric acid solution (HCl) and Sodium Hydroxide solution (NaOH). Both solutions function to remove lignin, pectin and wax that surrounds the outer surface of Kapok fibre. To achieve its carbonized properties, both samples of Kapok fibre were burned in a furnace at 450°C for approximately an hour. By doing this, it was found that activation time between carbonized Kapok fibre porosity shows a positive result, thus enhancing the capability of Kapok fibre as an absorbent. Absorption rate of two samples of Kapok fibre which is NaOH-treated Kapok fibre and HCl-treated Kapok fibre were evaluated on different types of oils which are diesel, lubricant oil, petrol and used vegetable oil. Mass used for each absorbent samples differ by using 0.2 g, 0.4 g, 0.6 g, 0.8 g and 1.0 g respectively. Dosage reusability and percentage of oil removal were examined for this two samples of absorbent. From the dosage reusability experiment it showed that both carbonized Kapok fibre can absorbed the oil after six cycle of using the same absorbent dosage. Meanwhile, the absorption oil experiment showed that HCl-treated Kapok fibre higher than NaOH- treated Kapok fibre. It is proven that HCL-treated Kapok fibre can perform better compared to NaOH-treated Kapok fibre.
Study of effective laying pattern of permeable interlocking concrete paver for storm-water management
Authors: Chow M.F. , Ng J.W. , Chong S.T. 
Published: August 2019

Abstract
This study determined the skid resistance and runoff infiltration rate of different laying patterns of PICP, namely stretcher bond and herringbone patterns. The dimensions of PICP block are 10.3 cm (height) × 12.5 cm (width) × 25 cm (length) and arranged for a total coverage area of 1.8 m2. Pendulum skid resistance tester and ring method were used to determine the skid resistant and runoff infiltration rate, respectively. The herringbone pattern showed higher skid resistant value in either dry or wet condition compared to stretcher bone pattern. Herringbone pattern exhibited infiltration rate of 21450.7 mm/hr while stretcher bond pattern only has an infiltration rate of 18516 mm/hr. It is observed that herringbone pattern performed better than the stretcher pattern in term of storm-water management.
Investigation of tribological properties of lithium grease with SiO2 nanoparticles
Authors: Rylski Adam , Siczek Krzysztof 
Published: August 2019

Abstract
The aim of the work was to investigate the effect of the SiO2 nanoparticles concentration in the lithium grease and of contact pressure on the spinning friction coefficient in the contact zone between a steel plate and a ball. The invvestigations were carried out using the a tribotester for the spinning friction torque in the contact between the ball and the plate. Ball rotated relative to the plate axis at a constant speed and was loaded by the a force increasing in a stepwise manner for the consecutive series. The contact zone was lubricated with a pure lithium grease - pure or with the grease with suspended SiO2 nanoparticles. The friction coefficient decreased with the increase of contact pressure for the pure lithium grease. For the concentration □ = 6wt.% of SiO2 nanoparticles in the grease friction coefficient decreased and for the other concentrations it increased with the increase of the contact pressure. If the values of average contact pressure were below 550 MPa, the friction coefficient values for pure lithium grease were higher than those for lithium grease with suspended SiO2 nanoparticles. For higher values of the contact pressure, the values of the friction coefficient for the pure lithium grease could be lower, equal or higher than those for lithium grease containing SiO2 nanoparticles depending on the value of SiO2 the concentration.
A Review of hybridization of carbon nanotube into graphene for gas sensor application
Authors: Hanim Khairul Azman Nur , Mahyiddin Ramli Muhammad , Salwa Mat Isa Siti 
Published: August 2019

Abstract
Hybridization of two mechanically strong materials which is carbon nanotube and graphene can provide specific advantages over other materials in gas sensor research and can relate to the chemical properties. Consequently, graphene and carbon nanotube show extreme sensitivity towards changes in the local chemical environment that originates from the susceptibility of the electronic structure to interacting molecules. Furthermore, a sensitivity and chemical selectivity to a diverse array has made them perfect candidates for consolidation into the design of gas sensor. The development of hybridization of carbon nanotube and graphene based gas sensor still in its infancy, but attempts to make the gas sensor more quantitative are important for further advancement of gas sensor innovation.
Development And Evaluation Of Immersive Card Games As Booster Memory In Engineering Science
Authors: Ismalina Haris Nur , Talip Amarul , Zulfabli Hasan Mohd 
Published: August 2019

Abstract
Engineering science is one of the core courses that must be taken by students in engineering. There is no doubt that too many laws and concepts to be learned and understood will cause students to feel difficult and less interested in pursuing engineering science. Many studies have shown that learning motivation and understanding can be achieved through educational games. Therefore, the main purpose of this study was to help engineering students learn and understand concepts by using educational card games through immersive technology. Card development and evaluation methods have been done while pre and post test have been conducted to see the effectiveness of the card against respondents. As a result, it shows that card designs play a role in enhancing student understanding while providing positive attitudes towards the use of the educational card games with immersive technology in engineering science learning. Notwithstanding, the outcome of the survey of the respondents involved in the test shows the enthusiasm and determination to use the card games. As a result, it can be highlighted and applied to all students.
Handover Delay Analysis on Cellular Communication for Connected Car Application in Urban Area
Authors: Fahmin Ab Hamid Azarul , Abdul Rahman Md Tasyrif , Rahman Anas , Ameer Tan Zairul 
Published: August 2019

Abstract
The study on delay of cellular communication is conducted by considering handover session in urban area. The experiment was performed on three distinct devices to study the handover delay based on 2G and 3G connectivity. Handover delay experienced by a moving vehicle was measured based on the data transmission latency during communication transfer session from previous cell network area that is passed by the vehicle to a new cell network area. From this experiment, the best selection of wireless communication module by considering the handover delay in urban area is determined by suited module to be use on connected car system.
Warpage Optimisation On The Front Panel Housing Moulded By Acrylonitrile Butadiene Styrene (ABS) (Virgin and Recycle) Material: A Review
Authors: Hidayah Mohamad Huzaim Nurul , Zamree Abd Rahim Shayfull , Roslan Norshahira , Aisyah Miza Ahmad Tamizi Nur 
Published: August 2019

Abstract
Injection molding process is well known in plastic molding industries. The development of this process had causes the materials used to mold plastic product to increase. However, this downside of this large amount of plastic consumption also leads to the fact that plastic waste fills the landfill. This cause researches on recycling plastic to increase. Even though injection molding process has many advantages, but the occurrence of defects on plastic part molded is one of the most important issues to be resolved. Warpage defect is one of the defect that normally occurred on molded part. This paper presents a review of the current research on the outlook of injection molding process and the effect of parameter processing on plastic molded part. The effect of parameter processing on mechanical properties of plastic mold parts with a mixture of virgin and recycled material has been numerously studied. However, studies on the physical appearance and quality of plastic mold parts by a mixture of virgin and recycled material have yet to be explored.
A review on applied statistical and artificial intelligence techniques in crime forecasting
Authors: Ridzuan Khairuddin Alif , Alwee Razana , Haron Habibollah 
Published: August 2019

Abstract
Crime forecasting is an important component of crime analysis towards providing early information about possible crime occurrences in the future. Different models have been proposed to assess different crime data structures and representations. From the literature study conducted, there are several types of crime forecasting models that have been introduced such as statistical model and artificial intelligence (AI) model. Recent trends indicate that researchers have shifted their interest towards AI model due to its flexibility in handling variations in crime data structures. The study found that AI model is capable of capturing nonlinearity pattern of crime data in which statistical model fails to achieve. Moreover, the structure of crime data is mostly nonlinear. Thus, an AI model is favoured among researchers towards developing a robust crime forecasting model. This paper provides a review on the background, trends, and challenges on applied statistical and AI model in crime forecasting.
RAD Design and Data Management Systems of Natural Resources and Local Wisdom
Authors: Tongkaw S. , Inkaew W. , Tongkaw A. 
Published: August 2019

Abstract
This research proposed the Rapid Application Development (RAD) design and data management systems of natural resources and local wisdom from the real data. The objectives were to: 1) collect local resources such as biological of local plant, animal, and the wisdom in the community; 2) study, organize and create an information system collection; 3) create a web-based application to present information of the data. The research used Rapid Application Development to plan and combining process from existed data to the web-based application for managing natural resources and local wisdom for data management. Natural resources and local wisdom data management at Tambon Ramdang is a case study of the successful implementation from the RAD design. The conclusion showed the lesson learn from this research and extended future work in this area.
Environmental Risks in Supply Chain: Recommendations and Directions for Future Research
Authors: Mukhtar Arwa , Romli Awanis , Abdullateef Mansoor , Al-bashiri Hael 
Published: August 2019

Abstract
This paper explores the environmental risks in supply chains and provides recommendations for subsequent studies. Typically, the environmental responsibility is a core part of sustainability which focuses attention directly to protecting and restoring the environment. Furthermore, environmental awareness is essential to design globally distributed supply chain networks. Therefore, the aim of this research is to explore the environmental risks and to identify the available solutions along with a projection of future trends. The basic research steps have been followed to complete this work. The Findings of this research describes the environmental risks that arises during supply chains operations. Furthermore, recommended solutions have been highlighted to address the identified risks. The Blockchain technology is regarded as a suitable solution for the environmental risks issue. The motivation for recommending this technology is its capabilities to contribute effectively towards greening the supply chain operations.
Consideration of Canny Edge Detection for Eye Redness Image Processing: A Review
Authors: Mohd Adnan M. R. H. , Mohd Zain Azlan , Haron Habibollah , Zulfaezal Che Azemin Mohd , Bahari Mahadi 
Published: August 2019

Abstract
Eye redness can be taken as a sign of inflammation which may suggest severity and progression of a specific disease. In image processing, there is apportioning a digital image into relevant features in sets of pixels where is called image segmentation. The image that consists of numerous parts of different colors and textures need to be distinguished in this process. In each digital image, the transformation of images into edges was using edge detection techniques. It represents the contour of the image which could be helpful to recognize the image as an object with its detected edges. The Canny edge detector is a standard edge detection algorithm for many years among the present edge detection algorithms. This paper focuses on important canny edge detection for detecting a region of interest (ROI) in eye redness images.
A Review on Collaborative Learning Environment across Virtual and Augmented Reality Technology
Authors: Muhammad Nur Affendy Nor’a , Ajune Wanis Ismail 
Published: August 2019

Abstract
Collaborative Learning Environment (CLE) in various application settings are presented and describe in this paper. CLE focuses on facilitating learning process through collaboration task. This paper reviews the numerous Augmented Reality (AR) and Virtual Reality (VR) technology that adopt collaborative system. It provides for an insight view of the capabilities of collaborative learning through the adoption of collaborative system in AR and VR. The adoption perspective define the cruciality to adopt collaborative in AR and VR in order to support learning process of the user of the respective task in a specific subject domain.
A Concise Review of Named Entity Recognition System: Methods and Features
Authors: Ikhwan Syafiq M. , Shukor Talib M. , Salim Naomie , Haron Habibollah , Alwee Razana 
Published: August 2019

Abstract
Named Entity Recognition (NER) is an elementary tool for all application areas in Natural Language Processing (NLP) such as Automatic Summarization, Information Extraction, Information Retrieval, Text Mining, Machine Translation, Question Answering, and Genetics. NER is a task to discover and categorises the named entities (‘atomic elements’) in the text into predefined classes such as the names of persons, organizations, locations, terminologies of time, quantity and etc. Different languages may have different morphologies and thus involve dissimilar NER procedures. For example, an Arabic NER system cannot be practically used in processing Malay texts due to the different morphological features. The morphological features of every language are rich and complex and donates to the difficulties of implementing an actual method to develop the accurate NER system. In this paper, we review on three main techniques that commonly used to develop an NER system well-known as Rule-Based, Machine Learning, and Hybrid approach. This paper also highlights the features of each technique.
Empirical Performance Evaluation of Imputation Techniques using Medical Dataset
Authors: Alade O A , Sallehuddin R. , Selamat A. 
Published: August 2019

Abstract
This paper evaluates the error measures of missing value imputations in medical research. Several imputation techniques have been designed and implemented, however, the evaluation of the degree of deviation of the imputed values from the original values have not been given adequate attention. Predictive Mean Matching Imputation (PMMI) and K-Nearest Neighbour Imputation (KNNI) techniques were implemented on imputation of fertility dataset. The implementation was on three mechanisms of missing values: Missing At Random (MAR), Missing Completely At Random (MCAR) and Missing Not At Random (MNAR). The results were evaluated by mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE). PMMI performed better than KNNI in all the results. MSE for example, has the ratio of 0.0260/2.8555 (PMMI/KNNI) for 1-10% MAR – 99.09% reduced error rate; 0.1108/3.0120 (PMMI/KNNI) for 30-40% MCAR – 96.32 reduced error rate; and 0.0642/3.7187 (PMMI/KNNI) for 40-50% MNAR – 98.27% reduced error rate. MCAR was the most consistent missingness mechanism for the evaluations. Density distributions of the imputed dataset were compared with the original dataset. The distribution plots of the imputed missing data followed the curve of the original dataset.
A Comparative Study on Hoping Mechanism of LEACH Protocol in Wireless Sensor Networks: A Survey
Authors: Mahmuddin M. , Alabadleh W. A. , Kamarudin L. M. 
Published: August 2019

Abstract
Low Energy Adaptive Clustering Hierarchy (LEACH) is a procedure, which is the most appropriate for the WSN routing. LEACH depends upon an adapted clustering procedure. The LEACH manipulates clusters and a single tier structure on the basis of a two-stage manoeuvre. LEACH functions in a single hop in such a way that every cluster head (CH) in WSNs my transfer its data to the BS and therefore the CH accepts the responsibility of sending information to the entire network. LEACH with Multi-Hop This procedure is the extension of single hop method, which works in a way that maximum CHs could send data to the BS.in this paper discussed the two extensions of LEACH in full detail with regard to their proposed schemes in terms of contributions and limitations.
An Enhanced Energy Efficient Hybrid Asynchronous Duty Cycle MAC in Wireless Sensor
Authors: Maulidin  , Mahmuddin M. 
Published: August 2019

Abstract
Wireless sensor network (WSN) has countless potential application in many areas due to its easy deployment process, lower installation cost, less cabling required, and high mobility. However, limited energy residue (especially deposited in small size battery) is always a major obstacle in WSN. Improving mechanism on MAC layer is one of the potential research that could increase battery lifespan. In the active phase of the MAC layer, a node can receive and transmit packet when awake. Then, a node is in a sleep phase, it switches off the radio automatically to save energy and gives alert. While in idle listening phase, node still using the energy. Duty cycling performed in MAC layer don’t involve turning off their radio and switching sleep mode but repeating off/on process. Therefore, this study proposed mechanism of WSN that used in order to enhance power energy using duty cycle in MAC layer. The proposed of asynchronous duty cycle MAC layer using a hybrid duty cycle MAC in implementation the performance of WSN. In addition, this paper also elaborated the design asynchronous hybrid duty cycle MAC with multi-hop broadcast.
Evaluation Performance of Hybrid MAC Protocol in Wireless Sensor Network
Authors: Maulidin  , Mahmuddin M. 
Published: August 2019

Abstract
The implementation Wireless Sensor Network (WSN) in generally can be applied in any environment where the important MAC layer plays vital. Researchers discover that the major power consumption of wireless sensor network nodes are related to their radio transceiver’s activities on MAC. This paper explains the implementation expected systeme that can be used in the WSN system. It focuses on the comparison some MAC protocol in order to discover the performance of each protocol. Therefore, this paper is benchmarking with other MAC protocol to identify the capability of the proposed hybrid protocol in term of some parameter. Then, this paper determines the proposed hybrid protocol that is camparised withother protocol based on evaluation of some parameter choosen.
Utilization of Filter Feature Selection with Support Vector Machine for Tumours Classification
Authors: Tengku Mazlin T A H , Sallehuddin R , Zuriahati M Y 
Published: August 2019

Abstract
Due to rapid technology advancement, machine learning has been widely used for solving cancer classification problem. Classification performance is highly depending on the quality of input features. With an explosive increase number of features of high dimensional data, the occurrence of ambiguous samples and data redundancy directly leads to poor classification accuracy. Therefore, this paper presents a utilization of filter feature selection using four filter methods such as Information Gain, Gain Ratio, Chi-Squared and Relief-F by performing attribute rankings to remove the irrelevant and redundant features and evaluate the significance and correlation of input data. Then, the classification will be performed using Support Vector Machine (SVM) to measure the accuracy performance based on the number of selected features. The performance measurement will be validated on standard Breast Cancer datasets consisting of 286 instances obtained from the UCI repository. Evaluation metrics such as accuracy, sensitivity, specificity and Area under Receiver Operating Characteristic Curve (AUC) will be used to assess the performance of the SVM classifier using four different filter methods. Experimental result shows that Gain ratio improves the accuracy of SVM classification compared to Information Gain, Chi-Squared and Relief-F in classifying breast cancer data with only small number of features selected.