bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment of Bridge Deck Movement under the Impact of Environmental Factors and Traffic Load
Authors: Ha Trung-Hieu , Chou Tien-Yin , Fang Yao-Min 
Published: July 2020

Abstract
The Bridge Health Monitoring (BHM) system has become crucial for long-span bridge structures. This study aims to assess the bridge deck movement based-on GPS time series data and environmental data obtained from BHM system. The correlation and regression analysis are utilized to find out the pairwise relationship between the bridge deck movement in all directions and environmental factors as well as traffic load. The result shows the highest correlations in bridge deck vertical movements, the symmetrical oscillation in different parts of bridge deck and it also reveals the impact of air temperature change, wind velocity and traffic vehicle on bridge deck movement in all directions.
Can Cold-Formed Steel Section Be Use As A Sustainable Structural Member in Building and Civil Engineering Constructions? A Mini Review
Authors: Lawan M M , Shek P N , Tahir M M 
Published: July 2020

AbstractCold-Formed Steel (CFS) section for several decades was not considered as a structural member in building and civil engineering constructions due to inadequate technical information available about its usage, despite the potentials it demonstrated as proven by current research studies. Therefore, this paper aimed at demonstrating the structural capability of CFS section as a sustainable structural member in building and civil engineering constructions. Some research studies conducted reported in this paper shows the possibility of CFS section to be utilized as a structural member in the construction industries. Results from the research studies reported shows that flexural capacities were found to be increased when the CFS section was integrated compositely. In conclusion, and as demonstrated in this paper based on the studies reported, the CFS section can be employed as a sustainable structural member in small and medium size buildings, civil engineering and in lightweight industrial constructions.
Performance of MR-De’Duster in Capturing Low Density Particulate
Authors: Hussein Norelyza , Yusof Mohd Rashid Mohd , Jamian Nor Ruwaida , Hashim Nor Hasyimah , Hassan Che Hafizan Che , Zaidi Nur Syamimi 
Published: July 2020

Abstract
A newly multi-cyclones named MR-deDuster is developed to capture particulate emission from potential industries. This study aims to assess the performance of MR-deDuster in capturing low density particulate. The tested particulate used in the study is PreKotTM (proprietary of AMR Sdn. Bhd), which is a low density particulate available in the market and commonly used as a pre-coating material with particulate density of 747 ± 2.2 kg/m3. Fractional collection efficiency, overall collection efficiency, cut diameter (dpc) and stack concentration were used to determine the performance of unit. The study indicates the unit able to capture about 88% of low density particulate at volumetric gas flow rate of 0.19 m3/s. The study has shown that collection efficiency of MR-deDuster increased as the volumetric gas flow rate increased. However, as the volumetric flow rate of gas was further increased to 0.21 m3/s, the collection efficiency of the unit was reduced. The optimum collection efficiency was observed to occur at volumetric gas flow rate of 0.19 m3/s.
An Ontology Development Architecture for Strategic Threat Intelligence of South China Sea Conflict (OntoSCSC)
Authors: Kamarudin Muhammad Fakhrul Syazwan , Othman Siti Hajar 
Published: July 2020

Abstract
The purpose of this study is to investigate the conflict of South China Sea area and develop an ontology architecture South China Sea conflict. The South China Sea is a marginal sea that is part of the Pacific Ocean, covering an area of about 3,500,000 square kilometres (1,400,000 sq mi) from the Karimata and Malacca Straits to the Taiwan Strait. Under its seabed are believed to be huge oil and gas reserves. In addition, several countries are subject to competing claims of sovereignty for the sea and its mostly uninhabited islands. The variety of names used for the islands and the sea also reflect these claims. The disputes within the South China Sea can possibly touch off an increasingly broad territorial conflagration. Various claimants fight about issues of sovereignty not defenceless to simple lawful goals. Other than that, the disputes are additionally discover by wild patriotism, as each inquirer joins symbolic motivation toward the South China Sea’s islands that deep exceed their aim material wealth. Furthermore, Ontology is the study of being’s philosophy. More broadly, its studies concepts that are directly related to becoming, existence, reality in particular, as well as the basic categories of being and their relationships. Traditionally listed as part of the major branch of philosophy known as metaphysics, ontology frequently deals with questions about what entities exist or can be said to exist and how these entities can be grouped, linked within a hierarchy, and subdivided by similarities and differences about South China Sea conflicts.
Junction-Centric Data Forwarding in Urban Vehicular Communication: Future Direction and Challenges
Authors: Aliyu A , Abdullah A H , Abdulrahman S , Joda U M , Abdulraheeem Z A 
Published: July 2020

Abstract
All Data packet transmission is a concept in vehicular communication for achieving road safety based on Intelligent Transportation System (ITS). The packet forwarding is carried out in two scenarios including road zone and junction zone forwarding in order to address the problem of intermittent disconnection that leads to packet loss and packet error. Several studies have been conducted considering these scenarios to achieve effective communication. These studies have been revisited to provide comprehensive understanding in order to further explore the existing solutions. However, the re-visitations of these studies have not considered some of the existing junction zone packet forwarding, which is based on video data transmission. To this end, this paper suggests a qualitative review on Junction-centric Data Packet Forwarding (JDPF) focusing on vehicular communication. Precisely, a review of various junction-centric approaches with their comparative assessment is presented. Major challenges in the junction- centric data packet forwarding are identified as future directions of research. The major issues include high traffic load, incorrect metric priority selection and link disconnection at the junction area. The review would be useful to practitioners and researchers, in terms of augmenting clarity in the junction-centric data packet forwarding literature.
Feature Engineering for Predicting MOOC Performance
Authors: Mohamad Nadirah , Ahmad Nor Bahiah , Jawawi Dayang Norhayati Abang , Hashim Siti Zaiton Mohd 
Published: July 2020

Abstract
Increasing data recorded in massive open online course (MOOC) requires more automated analysis. The analysis, which includes making student’s prediction requires better strategy to produce good features and reduces prediction error. This paper presents the process of feature engineering for predicting MOOC student’s performance utilizing deep feature synthesis (DFS) method. The experiment produces features which all the top features selected using principal component analysis (PCA) are the features that are generated from method. In terms of prediction comparing both based features and generated features, the result shows better accuracy for generated features proposed using k-nearest neighbours technique which shows the method potential to be used for future prediction model.
Analysis of Image Magnification in X-Ray fan beam Computed Tomography
Authors: Ishak Muhamad Noor Izwan , Sipaun Susan Maria , Rahman Mohd Fitri Abdul , Shari Mohamed Rabaie 
Published: July 2020

AbstractX-ray computed tomography (CT) is a non-destructive measurement method that allows inspection into both external and internal geometry of a scanned sample. This work is mainly concerned with industrial X-ray CT and its 2D image reconstruction parameters. The purpose of our study was to investigate how image magnification in 2D X-ray CT is influenced by the object position for a 50.5 mm x 50.5 mm cuboid. Using a standard definition of magnification, equations were derived to enable geometrical magnification to be determined from its position and vice versa knowing the diameter and machine parameters. Experimental data are compared and observed with regard to geometrical magnification. Results from experimental data showed a strong correlation between geometrical magnification and image magnification obtained from the reconstructed CT image. Derived sizes of cuboid from magnification were more consistent horizontally with geometrical magnification than vertically.
A Statistical Data Selection Approach for Short-Term Load Forecasting Using Optimized ANFIS
Authors: Mustapha M , Mustafa M W , Salisu S , Abubakar I , Hotoro A Y 
Published: July 2020

Abstract
Volume of the forecasting data and good data analysis are the key factors that influence the accuracy of forecasting algorithm because it depends on data identification and model parameters. This paper focuses on data selection approach for short-term load forecasting. It involves formulating data selection algorithm to identify factors (variables) that influence energy demand at utility level. Correlation Analysis (CA) and Hypothesis Test (HT) are used in the selection, where Wavelet Transform (WT) is applied to bridge the gap between the forecasting variables. This results to three groups of data; data without CA, HT and WT, data with CA, HT but without WT and data with CA, HT and WT. An optimized adaptive neuro-fuzzy inference system (ANFIS) using Cuckoo Search Algorithm (CS) is used to conduct the forecasting. The essence is to reduce the computational difficulty associated with the gradient descent (GD) algorithm in traditional ANFIS. With the three data groups, it is observed that CHW data can give satisfactory results more than the NCNHNW and NCNHW data. Also the numerical results shows that CHW data selection approach can give a MAPE of 0.63 against the bench-mark approach with MAPE of 3.55. This indicates that it is good practice to select the actual data and process it before the forecasting.
Performance Comparison between SVM and K-Means for Vehicle Counting
Authors: El-Khoreby Mohamed A , Abu-Bakar Syed Abd Rahman , Mokji Musa Mohd , Omar Syaril Nizam 
Published: July 2020

Abstract
Support vector machine (SVM) and K-means have been two well known methods used in classification. Choosing an accurate classifier for good features to differentiate between the foreground and background has a significant effect in increasing the accuracy of the detection. This paper presents and analyzes performance comparison between SVM and K-means classifiers for vehicle counting targeted for intelligence transportation systems (ITS) application. In particular, precision and recall have been used for the comparison between the two methods. Five videos from different weather conditions have been used for the testing purposes. SVM shows a better performance in terms of precision and recall.
Automated Classification of Stroke Lesion Using Bagged Tree Classifier
Authors: Saad N M , Abdullah A R , Syafeeza A R , Noor N S M , Ali N H , Muda A S 
Published: July 2020

Abstract
Stroke is a “brain attack” that often causes paralysis, resulted from either bleeding in the brain (hemorrhagic) or the blockage of blood flow to the brain (ischemic). It posed a big challenge to Malaysian healthcare services with at least 32 deaths per day, while survivors were burdened with multiple problems. Conventionally, the diagnosis is performed manually by neuroradiologists during a highly subjective and time consuming tasks. Therefore, this paper intends to diagnose and classify stroke by investigating diffusion- weighted imaging (DWI) of brain stroke images using Bagged Tree classification. Stroke is classified into three main types which are acute stroke, chronic stroke and hemorrhage stroke. The performance of the proposed method is then verified using accuracy and Area Under the Curve (AUC). Based on the results, the overall accuracy for the classification is 96.7%. The AUC of each type of stroke for acute stroke, chronic stroke and hemorrhage stroke is 97%, 100% and 99%, respectively. This outcome could serve as an insight to improve the healthcare of the community by providing better solutions using such intelligent system.
Effects of Approximation in Computation on the Accuracy and Performance of Deep Neural Network Inference
Authors: Ow Hui Nee , Sheikh Usman Ullah , Mokji Musa Mohd 
Published: July 2020

Abstract
Recently, deep learning is at the forefront of the state-of-the-art machine learning algorithms and has shown excellent results in a variety of applications such as medical field, consumer as well as autonomous vehicles. Convolutional Neural Network (CNN) – is the leading deep learning architecture that is mostly applied. However, huge dataset is needed to train with complex architecture to achieve precise learning. Inference can be performed when given a ready CNN model and its weight file to another user. Inference takes time with precise weights and huge dataset. To overcome this problem, and enhance the inference system, approximation computation will be applying in terms of weight for changed of decimal place. The smaller size of the dataset is used in the inference process to reduce the inference time. MobileNetV2 architecture is used with the new weight for inference. Also, open source libraries such as TensorFlow, Keras and python is used. GPU (NVIDIA GeForce GTX 1060 6GB 64 Bit) is used as training and inference platform. Inference time is shortened, and the accuracy of performance for new weights compare with the precise weight only has a small gap which still has a great performance for classification. This work has proved that with 4 decimal places is able to obtain the same accuracy for inference when compared to benchmark with 9 decimal places. Inference time for 4 decimal places is also less than benchmark time.
Ship systems synthesis and analysis using holistic design approach: The QFD-AD method
Authors: Khairuddin J , Maimun A , Siow C L 
Published: July 2020

Abstract
Design complexity is generally experienced in the design development and production of large and complex systems. It is viewed as the key element that would determine the design development cycle and quality. In this context, a study was conducted to demonstrate the ROPAX ship design and development processes applying the QFD-AD method. It is proposed to synthesise and analyse the ship systems design and configurations at the early design phase. This study explored the method applicability to facilitate concurrent design and decision-making, alternative to the conventional ship design spiral model. Moreover, it presented the potential method to support holistic design approach in exploring ship design as large and complex systems.
Potential of range extender electric vehicles (REEVS)
Authors: Veza I , Roslan M F , Said M F M , Latiff Z A 
Published: July 2020

Abstract
Battery Electric Vehicles (BEVs) is a promising technology. However, it suffers from low range characteristics thus increasing the anxiety to prospect customers and hindering its market penetration. To overcome this challenge, a range extender that can generate additional power to charge the battery could be the solution. This brief review article will highlight the prospects and challenges of range extender technology for electric vehicles. A number of automobile manufacturers have launched their Range Extended Electric Vehicles (REEVs) models and the detailed comparison will be given. Several types of range extenders will be discussed, including the internal combustion engine, microturbine, and fuel cell. Lastly, this report will suggest the use of Low Temperature Combustion (LTC) i.e Homogeneous Charge Compression Ignition (HCCI) engine be utilised as range extenders for electric vehicles.
Design and fabrication of an ergonomic sitting stool with storage capability
Authors: Wessam H 
Published: July 2020

Abstract
The paper presents design, development, and fabrication of a modern and ergonomic sitting stool with storage capability, for the Electronic Learning Center (ELC) of Jerudong International School (JIS), Brunei Darussalam. Dimensions of the stool are based on anthropometric data of teenage students of 18 years of age. It is fabricated using readily available materials that can be reused and recycled which makes the stool environmentally friendly. It is designed and developed after analyzing the available stools in the market. The analysis is performed based on product specifications such as aesthetics, cost, function, size, materials, environment-friendliness, and safety. The stool is termed a better solution by the supervisor and senior students of the ELC that could solve the problem of limited desk space at ELC, provide comfortable seating for students, and also provide the students with enough space to store their books, folders, bags, pencil case, and their water bottle in the storage compartment of the stool.
Complex geometry automotive muffler sound transmission loss measurement by experimental method and 1D simulation correlation
Authors: Mohammad M , Muhamad Said M F , Khairuddin M H , A Kadir M K , Dahlan M A A , Zaw T 
Published: July 2020

Abstract
A muffler is a device to attenuate noise from the exhaust. The muffler performance determined by the acoustic performance is called sound transmission loss (STL). This paper aims to measure the STL experimentally and correlated with the 1D simulation result. STL was measured using the impedance tube. Four-pole method (microphone) and two-load method were applied to measure the STL. The STL was also determined through the 1D simulation tools software. Three types of mufflers STL were measured; small expansion chamber, big expansion chamber and complex muffler. The respective error between simulation and experiment were 0.17%, 7.89%, and 11.40%. Hence, the STL experiment result was well correlated with the 1D simulation model.
Ignition Characteristics of Supersonic Combustion
Authors: Elhawary Shehab , Saat Aminuddin , Mazlan Mohammad Amri , Wahid Mazlan Abdul 
Published: July 2020

Abstract
Detonation may be initiated by two different modes, direct initiation or deflagration-to- detonation transition (DDT). Direct initiation can occur by a strong source such as using exploding wire or high-voltage discharge jets. Nevertheless, this method required a significant amount of energy in order to ensure that the generated blast wave will not separate and decay. A good alternative to direct initiation is Pre-detonator initiation, it depends on initiate the detonation in an ancillary small tube connected to the main tube then the detonation waves propagate to achieve detonation in the main tube. The pre-detonator is one of the most used methods to initiate the detonation due to the high reliability and design simplicity. This article is used to present a short review on experimental studies of supersonic combustion using various types of pre-detonator together with preliminary experimental work on single supersonic combustion experiment by using methane-oxygen and propane-oxygen mixtures. From this initial work, it is shows that equivalence ratio of Propane-Oxygen mixture at 0.6 shows smaller size of the supersonic combustion wave front as compared to the Methane-Oxygen mixture at 0.6 and 0.8.
Implementation of the PDCA continuous improvement cycle (Plan-D0-Check-Act) as a tool for improving the quality of the cast AA5083 alloy produced in the foundry laboratory
Authors: Al-Bakoosh Abdelaisalam Ali , Ahmad Zamani , Idris Jamaliah 
Published: July 2020

Abstract
Production of the high-quality alloy sample using the casting process it is not an easy and simple matter, it is one of the critical difficulties faced by the foundry technologist and researchers. Since the PDCA continuous improvement cycle is a key tool to achieve quality improvement of the product. Therefore, it was applied as an attempt to produce a high-quality cast AA5083 alloy. The main purpose of this paper is to avoid the defects that occur during the production of cast AA5083 alloy using the casting technique, which leads to minimizing product quality. The defects that may take place during the casting process of aluminium alloys have been identified through the literature reviews and taken into consideration to avoid them. The cause-effect diagram (Fishbone-Diagram) was constructed to show the root cause of the defects to avoid them, as well as the PDCA cycle was used to minimize the defects effectively. The results obtained showed that by applying the PDCA continuous improvement cycle and using the quality control tools, the quality of the cast AA5083 alloy can be improved.
Steel Wire Cleaning using Cold Plasma
Authors: Zainal Muhamad Nor Firdaus , Redzuan Norizah , Misnal Mohd Fadthul Ikmal , Ahmad Norhayati , Ibrahim Raja Kamarulzaman Raja 
Published: July 2020

Abstract
Current galvanizing process used hydrochloric acid to remove oxide layer and mild acidic bath to remove oil on metal wire surface. These cleaning processes are compulsory before steel wire coated with zinc. These chemicals cleaning technique cause ecological harm and produce toxic waste. To consider of minimizing these problems, cold plasma was introduced for metal wire cleaning. Previous research already proves that cold plasma capable to remove oil by using dielectric barrier discharge (DBD) and remove oxide layer on copper by using RF plasma discharge. Therefore, in this research, the same plasma discharge system that is DBD was used to remove oil and oxide layer on steel wire. 8kV of voltage and air was used to generate plasma. By using copper and steel wire as electrode, it can remove oil around 82% and oxide layer around 54%.
Thousands of reactants and transition states for competing E2 and S

N

2 reactions
Authors: von Rudorff Guido Falk , Heinen Stefan N , Bragato Marco , von Lilienfeld O Anatole 
Published: July 2020

Abstract
Reaction barriers are a crucial ingredient for first principles based computational retro-synthesis efforts as well as for comprehensive reactivity assessments throughout chemical compound space. While extensive databases of experimental results exist, modern quantum machine learning applications require atomistic details which can only be obtained from quantum chemistry protocols. For competing E2 and S

N

2 reaction channels we report 4,466 transition state and 143,200 reactant complex geometries and energies at MP2/6-311G(d) and single point DF-LCCSD/cc-pVTZ level of theory, respectively, covering the chemical compound space spanned by the substituents NO2, CN, CH3, and NH2 and early halogens (F, Cl, Br) and hydrogen as nucleophiles and early halogens as leaving groups. Reactants are chosen such that the activation energy of the competing E2 and S

N

2 reactions are of comparable magnitude. The correct concerted motion for each of the one-step reactions has been validated for all transition states. We demonstrate how quantum machine learning models can support data set extension, and discuss the distribution of key internal coordinates of the transition states.