bluuebunny/crossref_metadata_2025_split huggingface dataset:
Steady-state fluctuations of a genetic feedback loop with fluctuating rate parameters using the unified colored noise approximation
Authors: Holehouse James , Gupta Abhishek , Grima Ramon 
Published: July 2020

Abstract
A common model of stochastic auto-regulatory gene expression describes promoter switching via cooperative protein binding, effective protein production in the active state and dilution of proteins. Here we consider an extension of this model whereby colored noise with a short correlation time is added to the reaction rate parameters—we show that when the size and timescale of the noise is appropriately chosen it accounts for fast reactions that are not explicitly modeled, e.g., in models with no mRNA description, fluctuations in the protein production rate can account for rapid multiple stages of nuclear mRNA processing which precede translation in eukaryotes. We show how the unified colored noise approximation can be used to derive expressions for the protein number distribution that is in good agreement with stochastic simulations. We find that even when the noise in the rate parameters is small, the protein distributions predicted by our model can be significantly different than models assuming constant reaction rates.
Performance of Paracoccus Solventivorans SP as Sulphur Oxidizing Bacteria to Remove Odour and H2S Has in the Biological Treatment of Malodour
Authors: Farhana F. , Nastaein Q. Z , Tajarudin H. A. , Awang N. A. , Mohd Remy Rozainy M. A. Z 
Published: July 2020

AbstractThe presence of hydrogen sulphide (H2S) is one of the most problematic contaminants in biogas which emitted from industrial processes causing odour nuisance to the surrounding community. Thus, the ability of sulphur oxidizing bacteria (SOB) could eliminate H2S by changes it into non-odorous elemental sulfur or sulfate was investigated. Basically, most of identified sulphur oxidizing bacteria belongs to theThiobacillus, Thiothrix, Thiomicrospira, Achromatium, DesulfuromonasandParacoccuswhich occurs in heterotropic bacteria isolated from soil and marine environment. In corresponding of that, about 400 million of palm oil mill effluent (POME) pond found in Malaysia that could be one of the potential supply places for isolation of SOB as it contains elevated concentration of H2S which can support the growth of SOB. To date, many reports utilized SOB can eliminate the high concentration of H2S in environments. Hence, in this study the bacteria ofParacoccus solventivorans ATCC 700252were used as SOB and mixed with media by biofiltration process. Based on final result, these bacteria demonstrated reduction of H2S with removal efficiency 31% to 64.02% with the sulphate content production is 30 mg/l compare without SOB, the removal efficiency of H2S about 23% to 46% with sulphate content production is 12 mg/l after 28 days. The suitable condition for the growth of sulphur oxidizing bacteria affected on H2S removal efficiency from palm oil mill biogas by biofilter system. Besides that, the odour reduction for media with SOB is higher (73.5%) compared to media without SOB (66.9%). The reason for this phenomenon is due to the ability of SOB to absorb the odorous ‘rotten egg’ smell and changes into elemental sulfur that is no longer hazaroud. In this regard, the utilization ofParacoccus solventivorans ATCC 700252will create a new industry for application in the H2S removal and protect the environment from odour pollution.
Geopolymerization of Fly Ashes From 6 Indonesian Power Plants Using A Standardized Recipes
Authors: Hidayati R.E , Anindika G. R. , Faradila F.S. , Pamungkas C.I.B. , Hidayati I. , Prasetyoko D. , Fansuri Hamzah 
Published: July 2020

AbstractGeopolymers were synthesized using fly ash as raw material from six steam power plants, Adipala (FA1), Indramayu (FA2), Paiton 9 (FA3), Asam-asam (FA4), Pulau Pisang (FA5), and Sanggau (FA6). Fly ash was tested for several characteristics using XRF, XRD, and SEM. XRF analysis showed FA1, FA4, and FA5 included in class C fly ash while FA2, FA3, and FA5 included in class F. The XRD analysis results showed that there were typical peaks of quartz, mullite, calcite, magnetite, and hematite in the fly ash samples. SEM analysis shows the morphology of the fly ash FA1, FA2, FA3, and FA4 spherical with different particle sizes, but in the fly ash FA5 and FA6, the morphological shape is irregular. The highest compressive strength test results obtained by geopolymers made from FA3 after 28 days with compressive strength values of 36.62 MPa. The intensity of the crystalline geopolymer phase decreases when compared to its fly ash. Geopolymer morphology shows the presence of unreacted fly ash particles.
Novelty Studies on Amorphous Silica Nanoparticle Production From Rice Straw Ash
Authors: Uda M.N.A. , Gopinath Subash C.B. , Hashim Uda , Afnan Uda M.N. , Parmin N.A. , Halim N.H. , Anbu Periasamy 
Published: July 2020

Abstract
Turning waste product into the valuable resources is the best alternative way to overcome the waste management issue. Generally, rice is grown and planted twice a year where a lot of rice by-products have been produced after harvesting the matured paddy. Rice straw is one of turning waste products into the valuable resources and to manage the environmental issues. Generally, rice is grown and planted twice a year where a lot of rice by-products are produced. Rices straw is one of the rice by-products, generated roughly 0.7-1.4 kg per kilograms of harvested milled rice. With the nanotechnological approach, silica particles at nano-size can be produced using the incinerated rice straw. In addition to that, this research will report the synthesis, characterization and adsorption analysis towards the heavy metal removal.
High Temperature Cathodic Protection of Fe-Cr Alloy
Authors: Ani M. H. , Azman M. A. F. , Musa M. , Anhar Z. , Hamid M. 
Published: July 2020

Abstract
Power plant industry extensively using ferritic Fe-Cr alloys as boiler materials due to its good resistant to creep, low in thermal shock and thermal expansion. However, the development of new generation of Ultra Supercritical (USC) power plant requires boiler materials to be operate at higher temperature and pressure, thus make it susceptible to high temperature oxidation. The USC power plant successfully reaching the target of working temperature at temperature more than 873K (600°C). By increasing the operating temperature, the efficiency of power plant also increases at the expense of acceleration of high temperature oxidation. This project explored the application of impressed current cathidic protection (ICCP) at 1073 K. At high temperature, gas may dissociates into charged ions that make it possible to conduct electrons. Typical boiler material of T91 was used in high temperature oxidation at 1073K, under Ar-20%O2 mixed gas. The sample is connected to potentiostat with Pt wire to measure the value of corrosion potential (Ecorr), and Icorr. Blank experiment is conducted to determine the presence of reaction by the presence of current conductivity at high temperature in oxygen condition. The weight gain is following parabolic’s rate law, which shows that diffusion is the rate determing step. Blank test shows that as potential induced, current flows from one Pt terminal to another Pt terminal through intermediate mixed gas. Corrosion potential (Ecorr) of the sample show the value is greater than value at room temperature. It is concluded that ICCP is feasible to be conducted for controlling corrosion at high temperature.
Electrochemical Impedance Spectroscopy (EIS) Study of Coconut Water as Natural Inhibitor in Malay Traditional Preservation of Iron Artefact
Authors: Musa M. , Purwanto Hadi , Razak R. , Othman R. , Musa Luqman , Ani MH 
Published: July 2020

Abstract
Treating and cleaning corroded artefact has resulted in long-term loss of artefact integrity and intangible historical value in museum preservation method. Inhibitors and coatings are preferable methods applied in heritage conservation as it is the easiest way for corrosion protection. However, issue of health and environment has led conservators to find a better inhibitor, natural or green corrosion inhibitors. Surprisingly, Malay traditional practice has since long ago used Coconut water (CW) as corrosion inhibitor to preserve keris blades, showing that the knowledge in corrosion protection has been practiced in old Malay civilization for metal preservation. This paper intends to clarify the compositional effect of CW in the inhibition efficiency to iron-based keris blade. Through Tafel and Electrochemical Impedance Spectroscopy (EIS) and Energy dispersive analysis of X-rays (EDAX) analysis, the study showed that CW formed passivation with the highest IE of 92% as compared to other natural inhibitors existing and used in industries such as Ascorbic Acid (AA) and Tartaric acid (TA). EIS and Scanning Electron Microscope (SEM) study has shown and conclude that CW has displayed protective abilities that exceeds both AA and TA.
Correlation between Thermal Insulation Properties with Compressive Strength and Density of Lightweight Geopolymer
Authors: Wan Mastura W I , Romisuhani A , Mustafa Al Bakri A M , Faheem Mohd Tahir Muhammad , Ahmad Syauqi S , Aida Mohd Mortar Nurul 
Published: July 2020

Abstract
This paper reports the results of an experimental work conducted to investigate the correlation between thermal insulation properties with compressive strength and density of lightweight geopolymer prepared by using fly ash as source material and combination of sodium hydroxide and sodium silicate as alkaline activator. The experiments were conducted by varying the ageing time of 3, 7, 28, 60 and 90 days, respectively. The specimens cured for a period of 90 days have presented the highest compressive strength and lowest density accompanied with satisfied value of thermal conductivity. From the results obtained, it was evident that the thermal conductivity had a high correlation coefficient with compressive strength and density.
Interaction between Two Inclined Cracks in Bonded Dissimilar Materials subjected to Various Stresses
Authors: Hamzah K.B. , Nik Long N.M.A. , Senu N. , Eshkuvatov Z.K. 
Published: July 2020

Abstract
This paper deals with the interaction between two inclined cracks in the upper part of bonded dissimilar materials subjected to various stresses which is normal stress (Mode I), shear stress (Mode II), tearing stress (Mode III) and mixed stress. This problem is formulated into hypersingular integral equations (HSIE) by using modified complex potentials (MCP) with the help of continuity conditions of the resultant force and displacement functions where the unknown is the crack opening displacement (COD) function and the tractions along the crack as the right hand terms. Then, the curve length coordinate method and appropriate quadrature formulas are used to solve numerically the obtained HSIE to compute the stress intensity factors (SIF) in order to determine the stability behavior of materials containing cracks. Numerical results showed the behavior of the nondimensionalSIF at the cracks tips. It is observed that the various stresses and the elastic constants ratio are influences to the value of nondimensional SIF at the crack tips.
E-Commerce Beyond the Pandemic Coronavirus: Click and Collect Food Ordering
Authors: Hadi Mohamad Abdul , Athirah Hamzah Anis , Ramli Ramona , Fathullah M. 
Published: July 2020

Abstract
Online platforms have become a focus nowadays as an instrument to help expedite some daily routines such as e-commerce including food ordering, online banking, social networking, and many more. Food ordering through online platforms, for instance, have evolved due to the growing numbers of users of digital platforms, restaurant-goers, and many more. The recent pandemic of coronavirus has changed the scenario of brick-and-mortar businesses while most governments forced to shut down and impose strict regulations of lockdown and social distancing among citizens. Although this situation hit most businesses, statistics have shown there is an increasing amount of E-Commerce spending globally. There has been several commercial systems and studies in the market and literature related to food ordering platforms and processes discussed in the study. However, most systems focusing on order-to-delivery and imposed a higher price for delivery. This study introduces an O2O food ordering concept aiming the takeout customers segment and targeting to optimised orders that can be made in advanced and on-the-go. The concept generates models of a new O2O and distance food ordering for potential E-Commerce implementations. Out of the models, process improvement is analysed and suggest that customers would save time, effort, and able to maintain social distancing among citizens. The models can be generalised to be implemented in various industries and situations, depending on in-depth analysis that would be carried out in future studies.
Enhanced Approach of Risk Assessment for Insider Threats Detection in Smart Manufacturing
Authors: Hashim N A , Zainal Abidin Z , Abal Abas Z , Zakaria N A , Ahmad R , Mardaid E 
Published: July 2020

Abstract
The smart manufacturing integrates Internet of Things (IoT), cloud systems, data analytics and machine learning for autonomous implementation particularly in the factory’s supply chain. The additional components from Information Technology (IT) gives convenience accessibility in spike of welcomed threats from inside or outside the boundary to do harmful events. The valuable information in smart manufacturing consists of intellectual property (IP), assets (hardware and software) data and human talent that lead to data theft and illegal activities due to its monetary values. However, little work is done on assessing risks invaluable information particularly threats from inside. In fact, studies on risk assessments are focusing on financial profit, supply chain production and IT assets. Therefore, an enhanced approach of risk assessment for insider threat detection (RAFITD) is introduced. The proposed approach contributes to a log monitoring of the log on and log out activities, based on the role of employee on a software dashboard. From the result, the log monitoring produces two scenarios, which is the ideal and non-ideal. For the ideal scenario, a balanced ratio between log on and log out is accomplished. Meanwhile, a non-ideal scenario performs an imbalance ratio. The impact of the study brings an insider threat detection for better analysis.
A Comparative Analysis of Artificial Intelligence Techniques in Forecasting Violent Crime Rate
Authors: Ridzuan Khairuddin Alif , Alwee Razana , Haron Habibollah 
Published: July 2020

Abstract
The increase in the occurrence of violent crimes is a major concern in all countries around the globe. Various approaches of crime analyses have been implemented in reducing the number of violent crimes and among them is crime forecasting. Crime forecasting is an effective solution as it assists law enforcement agencies in planning efficient crime prevention measures. It has been observed recently that the application of artificial intelligence (AI) techniques in crime forecasting and analysis is favoured by researchers. Motivated by this development, this study aims to conduct a comparative analysis on the forecasting performance of three artificial intelligence (AI) techniques, namely artificial neural network (ANN), support vector regression (SVR), and gradient tree boosting (GTB) in forecasting the rates of four types of crimes in the United States (US). The forecasting performance of each AI technique was compared in terms of quantitative error measurement. From the results obtained, GTB showed the highest forecast accuracy compared to ANN and SVR as the observed error measurements were the smallest.
Document Tracking using Internet-of-Things Devices for Fast Data Retrieval
Authors: Zainal Abidin Z , Zakaria N A , Harum N , Suhaimi M S , Abal Abas Z , Idris A , Wan Mohd Ghazali K , Abdul Hamid M H 
Published: July 2020

Abstract
University is required to keep printed documents for a certain duration. Documents are evidence, for instance, student’s proof of payment or final exams script, which need to be stored in a safe place within five years or more. The creation of a physical or printed document follows the standard of the International Organization for Standardization (ISO) due to quality management and interrelation between universities for sharing information. However, an inventive way of ISO documentation for storing the evidence from loss and document misallocation is highly requested. Therefore, to overcome the document misallocation problem, an Internet-of-Things (IoT) based file tracking prototype is implemented. The prototype devices consist of Radio-frequency Identification (RFID) that has two parts, which are RFID reader and RFID tag, Arduino Uno, and mobile application (Android). RFID reader scans the information from the RFID tags located at the ISO document’s file. The RFID reader is integrated with Arduino to establish a connection to the network to communicate with mobile applications (Android). This method tracked the current location of the ISO document’s file. The result shows that the ISO document’s file is located in the respective area. Finally, the impact of this research brings efficiency in searching the ISO document’s file in the university.
Feature Selection of High Dimensional Data Using Hybrid FSA-IG
Authors: Fatin Liyana Mohd Rosely Nur , Mohd Zain Azlan , Yusoff Yusliza 
Published: July 2020

Abstract
Feature selection (FS) is a process of selecting a subset of relevant features depends on the specific target variables especially when dealing with high dimensional dataset. The aim of this paper is to investigate the performance comparison of different feature selection techniques on high dimensional datasets. The techniques used are filter, wrapper and hybrid. Information gain (IG) represents the filter, Fish Swarm Algorithm (FSA) represents metaheuristics wrapper and Hybrid FSA-IG represents the hybrid technique. Five datasets with different number of features are used in these techniques. The dataset used are breast cancer, lung cancer, ovarian cancer, mixed-lineage leukaemia (MLL) and small round blue cell tumors (SRBCT). The result shown Hybrid FSA-IG managed to select least feature that represent significant feature for every dataset with improved performance of accuracy from 4.868% to 33.402% and 1.706% to 25.154% compared to IG and FSA respectively.
Binary Black Hole-Based Optimization For T-Way Testing
Authors: Nsaif Hamsa N , Norhayati Abang Jawawi Dayang 
Published: July 2020

Abstract
Software testing is an important process in software development life cycle, which aims to guarantee the quality of software and reduce the number of errors and bugs. In such a process, software inputs and parameters are used to create a set of testing cases. Nevertheless, the number of testing cases increases enormously when considering all combinations of those inputs. Although t-way testing can reduce the test cases, generating the minimum, yet representative t-way testing set is challenging due to the large search space, which renders finding the best solution computationally prohibitive. The extant solutions suffer from the sensitivity to the random initialization and the subjectivity to the local minima, which adversely affects the reproducibility of these algorithms and obstructs finding the optimal solution. To this end, this paper proposes a novel meta-heuristic searching algorithm called Binary Black Hole (BBH) optimization that formulates the t-way testing as a binary optimization problem. Experimental results show the superiority of BBH over the famous Binary Particle Swarm Optimization (BPSO) algorithm. The achieved improvement shows the capability of BBH in generating smaller covering arrays with the same t-strength compared to those generated by BPSO.
Predicting Churn: How Multilayer Perceptron Method Can Help with Customer Retention in Telecom Industry
Authors: Sjarif NNA , Azmi NF , Sarkan HM , Sam SM , Osman MZ 
Published: July 2020

Abstract
Customer churn prediction has been used widely in various kind of domain especially subscription-basis industries. With the rapid growth of telecommunication industry over the last decade, this industry not only focuses on providing numerous products, but also satisfying the customers as it is one of the key solutions to remain competitive. This research proposed MultiLayer Perceptron Method for churn prediction. The evaluation is compared with three classifiers which includes are Support Vector Machine, Naïve Bayes and Decision Tree in term of several aspects. In preprocessing phase, we employed Principal Component Analysis and normalization to find the correlation among all the variables. For the postprocessing, InfoGainAttribute is used to identify the highest factor attribute that leads to customer retention. It is found that MultiLayer Perceptron outperforms other classifiers and international plan plays important role to retain customer from leaving organization.
Intergrating a Minimal Differentiator Expressions Approach into CBR for Linguistic Pattern reuse in Crime Relation: Proposed Method
Authors: Ikhwan Syafiq M. , Shukor Talib M. , Salim Naomie , Mohd Yunos Zuriahati , Haron Habibollah 
Published: July 2020

Abstract
The relation extraction of crime news can help the monitoring specialists to accelerate the crime investigation. However, constructing patterns or designing templates manually requires domain experts. Also the built patterns do not guarantee complete differentiation among different relation instances. The automatic detection of crime entities and relationship among entities can help the regulatory authorities to accelerate the crime investigation and decision support instead of being reliant on manual process. This study aims to increase the effectiveness of the extraction of crime entities and relationship among entities based on the determination of crime lingusitic pattern using Minimal Differentiator Expressions (MDEs) that represent the cases that will be used by the CBR classifier. The proposed extraction methods can help in compiling a highly accurate and machine-understandable crime knowledge bases which can support the regulatory authorities’ investigation. This paper conducted on our proposed MDEs algorithm for linguistic pattern reuse in CBR approaches.
Application of Deep Learning Method in Facilitating the Detection of Breast Cancer
Authors: Samah Azurah A , Nasien Dewi , Hashim Haslina , Sahar Julia , Abdul Majid Hairudin , Yusoff Yusliza , Ali Shah Zuraini 
Published: July 2020

Abstract
Breast cancer is a type of tumour that could be treated if the disease is identified at an earlier stage. Early diagnosis is crucial when it comes to reducing the mortality rate. In this study, deep neural network method is applied to facilitate the detection of breast cancer. The aim of this study is to implement deep neural network in breast cancer classification models that can produce high classification accuracy. Deep Neural Network (DNN) with multiple hidden layers was applied to learn deep features of the breast cancer data. Dataset used in this study was obtained from the UCI Machine Learning Repository which consists of Wisconsin Breast Cancer Dataset (WBCD) and used for the original and diagnostic dataset. The performance of the proposed DNN method was compared against previous machine learning classifier in terms of accuracy. From the results, the accuracy obtained for the original dataset was 97.14% and 97.66% for the diagnostic dataset, which is better than previous SVM method.