bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computer modeling of strain process of flexible rods with nonlinear and viscoelastic characteristics
Authors: Salimov Sh , Yusupov G , Abdieva G 
Published: July 2020

Abstract
A computer model is a software implementation of a mathematical model, supplemented by various utility programs. A computer model exhibits the properties of a physical model when its abstracts components — the programs — are interpreted by a computer. In addition, a computer model, as a physical device, can be the part of test benches, virtual laboratories. Computer simulation allows without significant difficulties to modify mathematical models, which are the basis for obtaining results with a high degree of accuracy. In the article was considered the application of the developed methods for predicting nonlinear viscoelasticity of flexible rods under various loading conditions based on creep curves is possible only in the case of finite strains Rod oscillations with viscoelastic and nonlinear characteristics are considered in this paper. From the point of view of practice, it is interesting to study the oscillations of flexible rods (yarn) when the rod receives excitation depending on the acting dynamic loads in the form of a real oscillogram.
Simulation modelling of cold rolled metal strip by asymmetric technology
Authors: Mavlonov T , Akhmedov A , Saidakhmedov R , Bakhadirov K 
Published: July 2020

Abstract
In the article provided the results of studies the optimization of energy-saving technologies in mechanical engineering using modern methods of simulation modeling is becoming an urgent area for the informatization of engineering production on the process of cold asymmetric rolling of metal sheets is accompanied by an inhomogeneous stress-strain state.
The research considers the noncanonical areas of strain, an approach is proposed for determining the optimal technological parameters and studying the stress state of the cold rolling process using asymmetric rolling technology in the active zone of elastoplastic strains based on simulation using the application software LS-DYNA by LS-PrePost (R) version V4.6.1. To optimize energy-saving for rolling technologies, considered a stationary regime of symmetrical rolling, the kinetic energy does not change over time, and the potential energy in the active zone of elastic-plastic strains tends to increase. For the case of asymmetric rolling, a high level of kinetic energy is observed, and there is a fluctuation over time, explained by different coverage of asymmetric rollers in the zone of active elastic-plastic strains, as a result of which the stationary nature of the metal sheet rolling mode is violated.
Building oscillations based on a plate model
Authors: Usarov M , Ayubov G , Mamatisaev G , Normuminov B 
Published: July 2020

Abstract
The paper is devoted to the numerical solution of the problem of transverse oscillations of a multi-storey building within the framework of a continuous plate model under seismic effects. Cantilevers anisotropic plate is proposed as a building dynamic model, the theory of which is developed in the framework of a three-dimensional dynamic theory of elasticity and takes into account not only structural forces and moments but also the bimoments. The proposed plate model of a building allows us to take into account and study all types of different spatial oscillations of the building structure under the impacts different in direction. Formulas are given for the reduced density, elastic moduli, and shear of the plate model of the building. The base acceleration, given in time by a harmonic law, is taken as a seismic impact. The problem is solved by the finite difference method. Examples are considered and numerical results are obtained. Waveform, displacements, and accelerations distribution diagram of multi-storey high-rise buildings under transverse oscillations are plotted.
Dynamics of viscoelastic orthotropic shallow shells of variable thickness
Authors: Normuminov B , Abdikarimov R , Eshmatov B , Yulchiyev D 
Published: July 2020

Abstract
Thin-walled structural elements such as plates, panels, and shells of variable thickness are widely used at present in engineering, machine-building, and construction. Modern technologies allow creating any structural elements of a given shape, material, and the law of thickness variation. Therefore, the solution to the problems of the statics and dynamics of plates, panels, and shells of variable thickness, considering the real properties of the material, is relevant. Nonlinear parametric oscillations of viscoelastic orthotropic shallow shells of variable thickness are considered in the paper. Using the Kirchhoff-Love hypothesis, a mathematical model of the problem is constructed in a geometrically nonlinear statement. To describe the viscoelastic properties of a shallow shell, the hereditary Boltzmann-Volterra theory with the Koltunov-Rzhanitsyn relaxation kernel is used. To obtain resolving equations of the problem, the Bubnov-Galerkin method was used in combination with the numerical method. The effects of various physico-mechanical and geometrical parameters of a shallow shell of variable thickness were investigated.
Prediction of Ventricular Fibrillation Using Support Vector Machine
Authors: Heng Wei Wei , Ming Eileen Su Lee , Jamaluddin Ahmad Nizar B , Harun Fauzan Khairi Che , Abdul-Kadir Nurul Ashikin , Yeong Che Fai 
Published: July 2020

Abstract
Sudden cardiac death (SCD) remains one of the top causes of high mortality rate. Early prediction of ventricular fibrillation (VF), and hence SCD, can improve the survival chance of a patient by enabling earlier treatment. Heart rate variability analysis (HRV) has been widely adopted by the researchers in VF prediction. Different combinations of features from multiple domains were explored but the spectral analysis was performed without the required preprocessing or on a shorter segment as opposed to the standards of The European and North American Task force on HRV. Thus, our study aimed to develop a robust prediction algorithm by including only time domain and nonlinear features while maintaining the prediction resolution of one minute. Nine time domain features and seven nonlinear features were extracted and classified using support vector machine (SVM) of different kernels. High accuracy of 94.7% and sensitivity of 100% were achieved using extraction of only two HRV features and Gaussian kernel SVM without complicated preprocessing of HRV signals. This algorithm with high accuracy and low computational burden is beneficial for embedded system and real-time application which could help alert the individuals sooner and hence improving patient survival chance.
Malaysian Bumiputera Contractors’ Supply Chain: A Preliminary Appraisal
Authors: Azwi M K , Mustapa M , Mustapa F D 
Published: July 2020

Abstract
The construction industry is an industrial sector that is complex and dynamic. As a developing country, Malaysia recognizes building as one of the main contributors to the economy of the country. Hence, being one of the economic drivers, the construction industry needs to ensure it remains important and competent by venturing successful strategies applied by other sectors. The implementation of supply chain management, especially in the manufacturing sector, has been positive and has produced the expected benefits such as cost reduction, competitive advantages, improved productivity, value creation and better relations between parties. This study aims to review reported outcome on Bumiputera contractors’ supply chain network. Additionally, this study also intent to analyse the main categories of risk that affect the Bumiputera contractors’ project performance which related to their approach on supply chain management. Current research papers on relevance to the issue were critically reviewed. The results from the structured literature review managed to identifies that supply chain is not used extensively among the Bumiputera contractors. Additionally, risks associated with the supply chain network in construction industry can be further categorised into external and internal factors such as cooperative risk, financial risk, technology risk and economic risk. The result have aspired a better understanding between the supply chain management with sustaining project performance among Bumiputera contractors. This study is a part of an on-going contract research with the overall aim to model supply chain network using risk parameters which will be identified at later stage of this research.
Recent Technologies in Construction; A Novel Search for Total Cost Management of Construction Projects.
Authors: Igwe Uchenna Sampson , Mohamed Sarajul Fikri , Azwarie Mohamed Bin Mat Dzahir 
Published: July 2020

Abstract
There is a continuous rise in the implementation of information-driven technology in construction, especially for effective control and management of construction resources. However, the enormous opportunities that these technologies provide have not been adequately utilized for construction cost management. There are so many innovations in the current IR 4.0 era, where digitization and connected systems are the trend of activities in engineering and other allied industries. These innovations are being adopted in the construction industry, to enhance the efficiency of construction processes. The areas of the current trend include Internet of things [IoT], Augmented and Virtual Reality [AR and VR], 5D-BIM, Autonomous Equipment, Artificial Intelligence and Machine Learning, and Predictive Analytics. This paper explores the applications and benefits of these areas of new technological trends in construction project management with emphasis laid in cost management of construction projects. Eighty-one[81] recent publications in journal articles, textbooks, web pages and conference proceedings published between 2008 and 2019 were reviewed in order to articulate and reveal areas of application of the technologies in project cost management and control. The paper exposes areas of application of the current ICT trends which construction managers and project cost managers should harness.
Prospects and Challenges of Green Materials for Construction Low-cost Building in Nigeria.
Authors: Adeniyi Shogo Musbau , Mohamed Sarajul Fikri 
Published: July 2020

Abstract
Housing plays an essential role in the wellbeing of people because it is the only place where people can fall back to relaxed and re-calibrated to put body and soul together. Thus, this paper been part of the more extensive study is on prospects and challenges of green materials an alternative material to provide housing for the low-income earners at affordable price in the developing countries such as Nigeria. The approach used to carry out the research is gathering information through the primary and secondary source. Four hundred structured questioners were designed and administered to the experts in the building industry out which 305 were considered usable after the data screening on the subject matter. The analysis was carried with statistical package for social science (SPSS) 23 software, the results from the response received reveal that relevant green materials have the following advantages affordability, renewability and naturality, free from volatile organic compound, durability among others. On the other, it has hitches of human neglect, lack of information, socio-economic influence, climate and weather influence among others.
Prototype Development of IoT Based Smart Waste Management System for Smart City
Authors: Harith Muhammad Zar Mohd Zaid , Hossain Mohammad Asif , Ahmedy Ismail , Idris Mohd Yamani Idna , Soon Tey Kok , Noor Rafidah Md 
Published: July 2020

Abstract
The inefficient waste collection system has resulted in environmental pollution and large consumption of sources of energy. This is because of inefficient waste collection systems result in smell pollution, unpleasant views, breading of insects, animal scavengers and rodents which also giving rise to a range of diseases when some waste bins are left overloaded and uncollected. As one of the efforts to overcome the inefficiency of the waste collection system problem and to achieve smart cities, an IoT (Internet of Things) based smart bin prototype is proposed in this paper. Altogether, it is an automatic centralized monitoring system that provides the timely status of a bin, enables optimal route planning for collections, reduces collection times, and saves costs as well as fuel consumption.
Features and Behaviours Mapping In Model-based Testing in Software Product Line
Authors: Sulaiman Raduni , Jawawi DNA. , Halim Shahliza Abdul 
Published: July 2020

Abstract
Testing in Software Product Line (SPL) is very hard task due to the high degree of variability that existed in products. Nowadays, many testing approaches have concern on reusability of technique. Feature Model (FM) is used to represent variability and commonality of products in SPL. The components of FM that represented as symbols caused the needs of mapping with other models to represent their semantics. In this paper, there are concise definitions that relates with mapping approaches between FM and behaviour model. Model definitions presented in our algorithms is used for automation mapping process based on traceability link created. The advanced query mechanism proposed to automate the process of mapping between models. Based on the experimental result, it shows that our proposed algorithm can help tester in automate searches for accurate mapping of features and requirements.
Reliability aware Resource Scheduling based on Fuzzy Cuckoo Search (FCS) Technique for IaaS Cloud
Authors: Madni Syed Hamid Hussain , Latiff Muhammad Shafie Abd , Abdullah Abdul Hanan 
Published: July 2020

Abstract
Resource scheduling assigns the precise and accurate tasks to CPU, network, and storage. The aim behind this is the optimum usage of resources. However, well-organized scheduling is needed for both cloud providers and cloud users. Several resource scheduling algorithms have been discussed in the literature, but there are little emphases to reliability aware resource scheduling. In this research article, an innovative technique is proposed that is known as the Fuzzy Cuckoo Search (FCS) technique based on the fuzzy theory and cuckoo search algorithm to solve real-time optimization problematic issues. The FCS technique is used to address the reliability aware resource scheduling problems in IaaS Cloud. An experiment has been carried out on the CloudSim simulator and results of FCS techniques are compared with the Genetic Algorithm (GA), Honey Bee (HB) and Particle Swarm Optimization (PSO) scheduling algorithms. Finally, computational results demonstrate that the FCS technique is produced 39.21% better optimal solutions than the best solutions obtained by the comparison algorithms in terms of failure rate. It specifies that the FCS technique is more appropriate for reliability aware resource scheduling for IaaS Cloud.
Enhancement of Individuality Representation for Multi-Biometric Identification
Authors: Leng W Y , Shamsuddin S M , Sulaiman S 
Published: July 2020

Abstract
Personal identification is one of the areas in pattern recognition that has created a center of attention by many researchers to work in. Recently, its focal point is in forensic investigation and biometric identification as such the physical (i.e., iris, fingerprint) and behavioural (i.e., signature) style can be used as biometric features for authenticating an individual. In this study, an improved approach of presenting biometric features of true individual from multi-form of biometric images is presented. The discriminability of the features is proposed by discretizing the extracted features of each person using improved Biometric Feature Discretization (BFD). BFD is introduced for features perseverance to obtain better individual representations and discriminations without the use of normalization. Our experiments have revealed that by using the proposed improved BFD in Multi-Biometric System, the individual identification is significantly increased with an average identification rate of 98%.
Comparison of Web Services for Sentiment Analysis in Social Networking Sites
Authors: Basmmi Ain Balqis Md Nor , Halim Shahliza Abd , Saadon Nor Azizah 
Published: July 2020

Abstract
With various type of web services available, it is hard to identify and compare which of the free access web services work best in analysing sentiment of extremist content in social networking sites. For that purpose, a generic approach by working with API of web service using PHP programming language is used to test each dataset that was extracted based on the keyword ‘extremism’. Data from both Twitter and Facebook has been used as these two are the most powerful platforms for expressing one’s feeling. The comparison for web service is done based on the analysis of its accuracy, precision, recall and f-measures in obtaining the lowest score of mean square error (MSE). Four sentiment analysis web services are used which are Sentiment Analyzer, Aylien, ParallelDots, and MonkeyLearn. From the comparison, MonkeyLearn obtained the best final results among all web services with the lowest MSE score of 14%. For the benefit of other researchers, the finding of this will reveal the suitable web service for analysing sentiment issues as critical as extremism.
Group-Based Authentication Schemes used for Machine Type Communication Devices in WSN: A Review
Authors: Ullah S , Zahilah Raja , Arshad Marina Md , Abdullah Abdul Hanan , Kadir Rashidah 
Published: July 2020

AbstractM2M communication is the next vital part of IoT infrastructure. It is extremely important for IoT systems to prosper in machine-type communication (MTC) devices that have low computational power, limited energy and small amount of memory capabilities. Thousands of devices transmitting data while working remotely and independent of any external supervision, creates concern for the security of data and devices as the topology is totally different to that of personal computers. In relation to the security of the devices, authentication is the first important part that has to be addressed against all possible security threats in IoT communication. In this regard, we focus on different types of authentication techniques being carried out by the researchers in M2M communicating environment of several remotely operating devices and address their security threats.
Analysis on Reflective Writing Using Natural Language Processing and Sentiment Analysis
Authors: Chong Calvin , Sheikh Usman Ullah , Samah Narina A , Sha’ameri Ahmad Zuri 
Published: July 2020

Abstract
Natural Language Processing (NLP) opens up the possibility for a machine to help us human process the vast data out there. There are multiple branches of NLP, but this thesis focuses on sentiment analysis, more specifically for reflective writing analysis. However, to obtain accurate results, NLP model needs to be tailored for the specific application. In this thesis, an NLP model is developed to process survey results obtained from psychology course by building a word database and categorise the level of reflection using fuzzy logic system. The main processes involved in this work are mainly performing intensive literature review on reflective writing models and to design fuzzy logic rules which can categorise the various levels of reflection demonstrated by the students. The model is then used to analyse a total of 47 reflective journals collected from the survey responses of the students from the School of Education in UTM. These surveys need to be pre-processed using some tools such as Natural Language Tool Kit (NLTK) to be fed to the developed model. There is the need to build a word database with words specific to the psychology field to improve the accuracy. From the analysis of the students’ survey, most of the students exhibit level 1-2 reflection.
Design and Fabrication of a Work Desk with Integrated Charging Ports, Desk Lamp and Storage Capability
Authors: Wessam H 
Published: July 2020

Abstract
This paper presents the design, development, and fabrication of a new work desk with integrated charging ports, desk lamp and storage capability for students’ use at the Outdoor Discovery Centre (ODC) hub at Jerudong International School (JIS), Brunei Darussalam. It contains a solar-powered lamp to provide light for students while conducting projects in the hub and storage compartments for students to place their belongings. It can organize and store wires, solar charge controllers, and switch box of a solar power system. Removable fans can be connected to the desk for students’ comfort. Charging ports are provided in the desk to charge electronic devices. The dimensions of the desk are based on anthropometric data of students of ages 14 - 18 years old. Feasible concepts of the product are generated and the final concept is selected based on product specifications such as aesthetics, cost, function, size, materials, environment-friendliness, and safety. The product is termed a better solution for use in ODC hub by its in-charge, Miss Follows Smith and the in-charge of renewable energy project at JIS, Dr. Lloyd.
Face Recognition and Machine Learning at the Edge
Authors: Yee Joanne Ling Sin , Sheikh Usman Ullah , Mokji Musa Mohd , Rahman Syed Abd 
Published: July 2020

Abstract
The number of IoT is expected to reach 20 billion by year 2020. This is due to data that log in the sensors or cameras are all send to the cloud for further processing. Cloud computing is not able to support big data analytic anymore due to network bandwidth. Face recognition is chosen as a case study to demonstrate the challenges to shift the application to the edge. The objective of this project is to develop a face recognition system that is suitable to be used at the edge using a deep neural network. Secondly, investigate the performance in terms of model size, speed and inference time after different bit-width fixed point quantization on the weights of the network. Lastly, deploy the model to Raspberry Pi 3 and test the performance. The chosen data set is AT&T. MATLAB is used to train the network in laptop with i5-7300 CPU while OpenCV-python is used to load and test the network in Raspberry Pi3 and laptop. The proposed system is designed by doing transfer learning on SqueezeNet to classify face. Fixed-point quantization is being applied to the weights of the layers to reduce the size of the model. From the experiment result, it is recommended to use 8-bit fixed-point quantization to the weights in all the layers in the model to compress the size of the network up to 2.5 times while maintaining the original accuracy 90%. That is only 1.1× speed up of the model on Raspberry Pi 3 after different bit-width weight quantization.
Optimal design of an Autonomous Emergency Braking (AEB) system for a passenger vehicle
Authors: Mustafar M Z Che , Abu Bakar S A 
Published: July 2020

Abstract
This paper models the performance of a passenger vehicle equipped with Autonomous Emergency Braking (AEB) using a feedback control system in MATLAB Simulink. Two types of AEB control systems are simulated and compared; proportional-integral (PI) control and fuzzy logic control (FLC). Performance of both control systems simulated are compared using AEB City collision scenario defined in Euro New Car Assessment Protocol (NCAP). Results show that the proposed PI control system is able to meet Euro NCAP AEB City set requirements.