bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-Density Polyethylene (LDPE) Food Packaging Defect Classification using Local Binary Pattern (LBP)
Authors: Sabri N , Abdull Hamed H N , Isa M A , Ghazali N S , Ibrahim Z 
Published: December 2021

Abstract
The motivation of this research is to automate the current food packaging inspection process by implementing the non-destructive approach. The current practices require human intervention where human vision tends to overlook the faulty on the package resulting in accuracy dilemma. Human also may be exhausted due to repeated activities. This paper provides the primary phase for effective automation of image classification solution implemented using Weka software. An evaluation of the performance of the Support Vector Machine (SVM), K-nearest Neighbour (KNN) and Random Forest (RF) classification models for Low-Density Polyethylene (LDPE) food packaging defect image classification using a small sample of dataset and Linear Binary Pattern (LBP) as feature extraction algorithm is investigated. Four criteria have been used to evaluate the performance of each classification model which is accuracy, sensitivity, specificity and precision obtained from the confusion matrix table. The results indicate that SVM performs better than RF and KNN with 95% accuracy, 95% sensitivity, 72% specificity and 95% precision in classifying LDPE food packaging defect images.
Multiple Responses Injection Moulding Parameter Optimisation Via Taguchi Method for Polypropylene-Nanoclay-Gigantochloa
Authors: Rosli M S , Othman M H , Amin Sri Yulis M , Azman M A I 
Published: December 2021

Abstract
Recently, the reinforcement of natural fibres into the polymer has been the main topic due to ecological which can sustain the life of our earth. Natural plant fibre composite has advantages in production in manufacturing product due to biodegradability and environmental protection. The injection moulding process is a major interest within the field of manufacturing technology because of the issue of archive the good quality of the product while minimizing the defect of the product that has been produced. Therefore, this research purpose describes the effects of gigantochloa scortechinii (natural fibre) mix with the polypropylene-nanoclay by using multiple objective optimisations for instance Taguchi Orthogonal Array method for injection moulding processing condition towards multiple responses such as melt flow index, flexural strength, warpage, and shrinkage. The compounding material used in this research is polypropylene, nanoclay, the compatibilizer which is polypropylene graft maleic anhydride (PP-g-MA), and gigantochloa scortechinii which known as bamboo fibre. For comparison purpose, the contents of natural fibre selected are 0wt.%, 3wt.% and 6wt.% towards the processing condition which are packing pressure, melt temperature, screw speed and filling time. Based on the signal to noise ratio analysis results, the highest value of S/NQP is at 6wt.% which is 160.6451 dBi followed by 3wt.% (158.1919 dBi) and 0wt.% (134.8150 dBi). Furthermore, the most influential parameter changed with the existence of Gigantochloa Scortechinii from melt temperature into packing pressure. In conclusion, the optimum values for multiple responses have been affected by the present of Gigantochloa Scortechinii.
Effect of Cellulose Nanofibers (CNF) as Reinforcement in Polyvinyl Alcohol/CNF Biocomposite
Authors: Ulaganathan Rathesh Kumaran , Senusi Nur Aiman Mohamad , Noor An’Amt Mohamed , Abdullah Wan Nazwanie Wan , Amin Mohamad Asyraf Mohd , Razab Mohammad Khairul Azhar Abdul , Ismardi Abrar , Abdullah Nor Hakimin 
Published: December 2021

Abstract
This research was targeted to use the planetary ball milling method to extract cellulose nanofibers (CNFs) from commercial microcrystalline cellulose and also to utilize the obtained extracted cellulose nanofibers (CNFs) as reinforcement in polyvinyl alcohol (PVA) thin film. The effect of cellulose nanofibers (CNFs) on the mechanical and physical properties of polyvinyl alcohol (PVA) thin films was investigated. As a result of the study, we found that the thin film’s tensile strength is good, and the surface morphology of the CNFs suspension enhances the bonding between the PVA and the reinforcement. Tyndall effect was accurate with the visible light scattering through CNF suspension, and the CNF/PVA thin film exhibited transparent thin film. In contrast, the CNF/PVA composite’s mechanical and physical properties are good due to the excellent dispersion and absence of agglomeration of CNFs. The prepared PVA/CNF biocomposite would be a suitable candidate to be implemented as biodegradable food packaging material.
Relationship between Density and Early Compressive Strength of Slurry Infiltrated Fiber Reinforced Concrete (SIFCON)
Authors: Rahim Mustaqqim Abdul , Jonq Lim Jiann , Ayob Afizah , Anuar Shamilah Anudai , Bawadi Nor Faizah , Ibrahim Norlia Muhamad , Shahidan Shahiron , Ahmad Ahmad Nur Aizat , Wahab Roshasmawi Abdul 
Published: December 2021

Abstract
The aim of the study is to study the physical and mechanical characteristics of Slurry Infiltrated Fiber Reinforced Concrete with fiber percentage volume of 5% and lower. For the testing of physical characteristics of the concrete, density test been conducted. For the testing of mechanical characteristics, compression test used to determine strength of concrete sample. The density of Slurry Infiltrated Fiber Reinforced Concrete increased when the usage of steel fiber percentage volume increases from 1% to 5%, nevertheless when compared to density of ordinary concrete, ordinary concrete is denser. For the significant of study, the mechanical properties of Slurry Infiltrated Fiber Reinforced Concrete, compressive strength increased when the fiber content increases from 1% to 5% percentage volume.
High Gain Transformer-less DC/AC Inverter for PV System
Authors: Zunnurain I A , Hariz M F , Ilham S M , Kimpol N , Anuar M N K , Yumi K M 
Published: December 2021

Abstract
Investigation interests on many scientific aspects of photovoltaic (PV) trans-former-less inverter system has improved over the past decade. Using step-up transformer or high frequency transformer in electrical system has made the entire system expensive and voluminous. There is alternative topology to replace the transformer by implementing DC/DC quadratic boost converter to expand the voltage from 12VDC
to 325VDC
from the photovoltaic (PV) solar and convert it to AC applying H-bridge inverter circuit. This method will replace the conventional method of bulky transformer into a lighter converter with the same performance. The circuit is simulated using Power Sim (PSIM) software to initiate the design and study the circuit capability. The experimental result will project the exact voltage in the range of 230VACrms
. The harmonic profile of the inverter is studies and compared with the normal inverter configuration.
Microbiologically Influenced Corrosion of Iron by Nitrate Reducing Bacillus Sp
Authors: Mohd Zaidi Muhammad Aiman Faiz , Masri Mohammad Najmi , Kew Wee Seng 
Published: December 2021

Abstract
Iron has played a crucial role in the human ecosystem currently in transportation, manufacturing, and infrastructure. Iron oxide is known as rust, usually the reddish-brown oxide formed by iron and oxygen reactions in moisture from water or air. Microbiologically influenced corrosion (MIC) is a significant problem to the economic damage, especially in industrial sectors and its direct presence with nitrate/iron-reducing bacteria. This paper aims to explore the MIC of iron by nitrate-reducing Bacillus sp. including the redox reaction occurs, microbiologically influenced corrosion, iron/nitrate-reducing and mechanisms of microbial iron/nitrate reduction.
Exploring Pupil Position as An Eye-Tracking Feature for Four-Class Emotion Classification In VR
Authors: Lim Jia Zheng , Mountstephens James , Teo Jason 
Published: December 2021

Abstract
This paper presented a preliminary investigation of a novel approach on emotion recognition using pupil position in Virtual Reality (VR). We explore pupil position as an eye-tracking feature for four-class emotion classification according to the four-quadrant model of emotions via a presentation of 360° videos in VR. A total of ten subjects participated in this emotional experiment. A 360° video with four sessions of stimulation of emotions will be presented in VR to evoke the user’s emotions. The eye data were recorded and collected using Pupil Labs eye-tracker and the emotion classification was done by using pupil position solely. The classifier used in this investigation is the Support Vector Machine (SVM) machine learning algorithm. The results showed that the best accuracy achieved from this four-class random classification was 59.19%.
Effect of Graphene Nanoplatelets on Water Absorption Properties of Coconut Shell Reinforced Unsaturated Polyester Composites
Authors: Abdullah A , Abu Bakar M B , Mohd S H , Masri M N 
Published: December 2021

Abstract
Coconut shell (CS) reinforced unsaturated polyester (UPE) composites have been prepared by using hand lay-up and compression molding techniques. To improve fiber-matrix adhesion, the CS was chemically treated by two chemical treatments, which are alkali (NaOH) and alkali-silane with concentration NaOH (6%) and silane (2%). To enhance the performance of CS-UPE composites, graphene nano platelets (GNP) was also added as nanofiller. The water absorption tests were conducted to characterize the physical properties of the composites. The result shows that water absorption increases with the increasing GNP. The more adding of GNP fillers’ weight percentages, the higher the water absorption will be getting.
Influence of Preparation Method on Properties of Natural Rubber/Sepiolite Composites
Authors: Jitsopin Patiwarada , Masa Abdulhakim , Hayeemasae Nabil , Mohamad Rasidi Mohamad Syahmie 
Published: December 2021

Abstract
Natural rubber (NR) composites filled with various sepiolite loadings were prepared and optimized by two different mixing methods, namely, melt mixing and latex mixing methods. The properties were evaluated through viscosity, stress relaxation, curing behaviors and tensile properties of rubber composites. The viscosity was influenced by sepiolite content and mixing methods. The greater interaction between rubber and sepiolite was obtained from melt mixing method. This reflected to the greater tensile strength found in this method. Considering the content of sepiolite, similar trend was observed for the curing properties and elongation at break. The greatest tensile strength was observed when the sepiloite content was at 1 phr.
Evaluation of 20 kV Distribution Network Losses In Radial Distribution Systems Due to Distributed Generation Penetration
Authors: Arnawan H , Muzamir I , Mohd I Y , Siti R A R , Hadi S 
Published: December 2021

Abstract
The installation of distributed generation with renewable energy becomes a solution when the demand for electricity is increasing and electricity generation with fossil energy is increasingly limited. There has been a change in power flow before and after the installation of distributed generation. However there can be a negative impact on the distribution network losses applicable to reactive power flows. There are cases where the distributed generation capacity is greater than the supplied load, resulting in distributed generation operating as a system voltage regulator and requiring reactive power, so that DG will absorb the reactive power from the system. The increasing demand for reactive power in DG also causes an increase in the current flowing in the network, and causes an increase in losses in the network, especially for the losses in reactive power.
Integration of Aluminium Interdigitated Electrodes with Zinc Oxide as Nanocomposite for Selectively Detect Alpha-Synuclein for Parkinson’s Disease Diagnosis
Authors: Adam Hussaini , Gopinath Subash C. B , Hashim Uda 
Published: December 2021

Abstract
Parkinson’s disease is associated with motor and non-motor symptoms, mostly a motor symptom such as tremor is said to be an early indication for Parkinson’s disease development. Because of higher demands for faster and more precise diagnostic methods, it has sparked trends in the development of a biosensor for the diagnosis of Parkinson’s disease. Therefore, this study has fabricated a biosensor that is capable of detecting a specific Parkinson’s disease biomarker such as aggregation of alpha synuclein and this is crucial in reducing the burden of Parkinson’s disease and to be able to detect the disease at the earlier stage. Finding the inconsistent aggregation of alpha-synuclein is a promising method for the early detection of Parkinson’s disease. Using conventional photographic process, aluminium interdigitated electrodes (ALIDEs) have been fabricated and employed with sensitive electrochemical strategy for the specific detection of the Parkinson’s disease antigen (alpha synuclein). The microelectrode was developed based on aluminium electrode sputtered on silicon substrate. Further, zinc oxide (ZnO) was deposited by sputtering on the working electrode of the ALIDEs using a spin-coating method. The ZnO nanocomposite onto aluminium microelectrode surface provides a favourable platform for efficient loading of antibody via binding with antigen alpha synuclein. The effective loading of the biomolecules (antibody and antigen) on the ZnO nanocomposite surface modified aluminium microelectrode was observed by SEM, AFM and 3D Profilometer. The current flow for each concentration of alpha synuclein was observed at 7.5×10−6 A (10 fM), 8.8×10−6 A (100 fM), and 8.5×10−6 A (1 pM) respectively.
Temperature measurement methods in an experimental setup during bone drilling: A brief review on the comparison of thermocouple and infrared thermography
Authors: Islam Md Ashequl , Kamarrudin Nur Saifullah , Daud Ruslizam , Ibrahim Ishak , Rahman Anas , Mat Fauziah 
Published: December 2021

Abstract
Predicting thermal response in orthopedic surgery or dental implantation remains a significant challenge. This study aims to find an effective approach for measuring temperature elevation during a bone drilling experiment by analyzing the existing methods. Traditionally thermocouple has frequently been used to predict the bone temperature in the drilling process. However, several experimental studies demonstrate that the invasive method using thermocouple is impractical in medical conditions and preferred the thermal infrared (IR) camera as a non-invasive method. This work proposes a simplified experimental model that uses the thermocouple to determine temperature rise coupled with the thermal image source approach. Furthermore, our new method provides a significant opportunity to calibrate the thermal IR camera by finding out the undetected heat elevation in a workpiece depth.
Morphological Analysis of Fabricated 5.0 μM Interdigitated Electrode (IDE)
Authors: Uda M N A , Gopinath Subash C B , Hashim Uda , Uda M N Afnan , Parmin N A , Halim N H , Hashim M K R , Anbu Periasamy 
Published: December 2021

Abstract
The aim of this research is to study the morphological analysis of fabricated Interdigitated Electrode (IDE). This device electrode was physically characterized using 3D nano profiler, scanning electrode microscope (SEM), Energy-dispersive X-ray spectroscopy (EDX) and Atomic Force Microscope (AFM). Based on this analysis, IDE pattern was analyzed thoroughly based on the IDE pattern specifications with 5 μM finger gap and this research significantly will stand as a platform quantify the biomolecules in further analysis.
Processing and analysis of botanical micro-and macroobjects using computer vision technologies
Authors: Vaganov A V , Krotova O S , Khvorova L A 
Published: December 2021

Abstract
This article discusses the problems of automation of processing and analysis of botanical micro-and macroobjects. The problem is a comprehensive interdisciplinary research aimed at recognizing and searching for botanical micro-and macroobjects using computer vision technologies. Computer vision is an area of artificial intelligence that deals with the analysis and extraction of information from images (in this case, the fern dispute). The purpose of this study is to solve a number of applied and fundamental problems in the biosystematics of botanical objects and the study of microevolutionary processes. The results of the research are stored in a specially developed database “Spore morphology of ferns of the Pteridaceae family”. The database implements a set of queries relevant to biometrics tasks. The database is based on images and biometric data on the morphology of fern spores obtained in the form of measurements of systematically important signs of spores, as well as data on the shape and surface of the studied objects. The diagnostic characters of taxa of the Pteridaceae family have been standardized for solving the research problems. In the course of the study, fundamentally new knowledge was obtained that will supplement the natural classification of the Pteridaceae family, as well as test hypotheses about the relationship of a number of taxa represented on the continents of Eurasia and Africa, for an objective reconstruction of events of past geological periods. Processing and analysis of botanical micro-and macro-objects and the development of specialized software are carried out in the Python programming language using an integrated development environment for Python - PyCharm. When developing the graphical interface of the program, we used the sets of Python libraries PyQt5 and a visual tool for designing and creating graphical user interfaces (GUI) from Qt components - Qt Designer.
A new approach to identifying the local structure of multidimensional chaotic time series
Authors: Makshanov A V , Zhuravlev A E , Tyndykar L N 
Published: December 2021

Abstract
The paper is devoted to the solution of the problems of mathematical supply of decision making during multichannel monitoring of large-scaled systems. The work also deals with space-time dynamics of multidimensional time series of different origins. Highly dynamical chaotic processes whose fine structure cannot be revealed by standard spectral methods are regarded. Technologies for dimension reduction based on data matrix representation on the first singular basis and multiple regression in projections’ space are developed.
Neural networks for classification problem on tabular data
Authors: Nazdryukhin A S , Fedrak A M , Radeev N A 
Published: December 2021

Abstract
This work presents the results of using self-normalizing neural networks with automatic selection of hyperparameters, TabNet and NODE to solve the problem of tabular data classification. The method of automatic selection of hyperparameters was realised. Testing was carried out with the open source framework OpenML AutoML Benchmark. As part of the work, a comparative analysis was carried out with seven classification methods, experiments were carried out for 39 datasets with 5 methods. NODE shows the best results among the following methods and overperformed standard methods for four datasets.
Information system for monitoring of hypopituitarism in childhood and adolescence
Authors: Rusakov M O , Krotova O S 
Published: December 2021

Abstract
The article is devoted to the development of a medical information system (MIS) designed to monitor and predict hypopituitarism in children and teenagers. MIS combines the medical information storage and management system with an intellectual system of medical decision-making support. The information system is based on a database with information obtained from impersonal medical discharge papers of children and adolescents of the Altai Territory diagnosed with hypopituitarism. Medical discharge papers provide information about the patient’s health status while in the hospital, the results of examinations and treatment. Discharges form a complete medical history of the patient, and the information system allows assessing the disease in dynamics. The purpose of the intelligent information system is to predict the patient's growth in order to select the optimal treatment strategy. The intelligent decision support system is based on a machine-learning model trained on data from a database. The model was trained in the Python programming language. The MIS interface is developed using the C # programming language. The use of MIS in medical institutions will allow doctors to carry out a personalized approach to the monitoring and predicting the growth for patients, and to choose the optimal trajectory of treatment.
Raspberry Pi-based mobile system of the pupil size evaluation
Authors: Ya Suranov A 
Published: December 2021

Abstract
The article considers development of a human pupil measuring system on the Raspberry platform. The system is aimed at evaluating the variations of the human pupil diameter or area in the process of watching test images or video recordings. To reduce the interference from the eye surface the camera uses a band-stop color glass filter PS 13. In order to increase the pupil image contrast, IR LED backlighting of the eye is implemented. To provide the mobility of the system, battery power of the single-board computer was used while the registered image and the measurement results were transmitted via a Wi-Fi channel. The video camera and the single-board computer Raspberry Pi 4 with the battery bay are attached to the head-mounted flexible belt. The article gives the operation duration evaluation of the battery-supplied system. During the first stage of image processing, binarization by the threshold was performed. The threshold is determined by the image brightness histogram. Since the study is focused on relative variations of the pupil size, the pupil diameter or area values in pixels were chosen as informative parameters. The image recording and processing frequency in the system equalled 25 Hz that provides accurate recording of the pupil variations.
To the question of realization of machine vision technology based on FPGA-architectures
Authors: Timakov K A 
Published: December 2021

Abstract
In the last few years, machine learning and machine vision technologies have started to gain more and more popularity. This industry occupies one of the leading positions in the field of information technology. The paper is devoted to the development of a machine vision algorithm based on new generations of FPGAs for recognizing handwritten Cyrillic characters in images and video streams, in particular. The article raises the issues of using FPGA as an image segmentation accelerator and organizing work with the video stream, choosing the most suitable FPGA platform, creating training samples of handwritten characters, and working with the convolutional neural network AlexNet.
Characterization of a CMOS pixel sensor for charged particle tracking
Authors: Li L. , Zhang L. , Dong J.N. , Liu J. , Wang M. 
Published: December 2021

Abstract
A prototype of the CMOS pixel sensor named Supix-1 has been
fabricated and tested in order to investigate the feasibility of a
pixelated tracker for a proposed Higgs factory, namely, the Circular
Electron-Positron Collider (CEPC). The sensor, taped out with a 180 nm CMOS Image Sensor (CIS)
process, consists of nine different pixel arrays varying in pixel
pitches, diode sizes and geometries in order to study the particle
detection performance of enlarged pixels. The test was carried out with a 55Fe radioactive source. Two
soft X-ray peaks observed were used to calibrate the charge to
voltage factor of the sensor. The pixel-wise equivalent noise
charge, charge collection efficiency and signal-to-noise ratio were
evaluated. A reconstruction method for clustering pixels of a signal has been
developed and the cluster-wise performance was studied as well. The test results show that pixels with the area as large as of
21 × 84 μm have satisfactory noise level and charge collection
performance, meeting general requirements for a pixel sensor. This contribution demonstrates that the CMOS pixel sensor with
enlarged pitches, using the CIS technology, can be used in tracking
for upcoming collider detectors akin to the CEPC.