bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Review of Frequency Selection and Antenna Arrangement System for Microwave Imaging in Early Breast Cancer Detection
Authors: Jumaat Hadi , Ali Mohd Tarmizi , Ping Kismet Hong , Faudzi Najwa Mohd , Miswadi Nurfarahin , Yon Hamizan 
Published: November 2019

Abstract
Microwave imaging technique is one of the developing techniques that having attention by researcher around the world in early breast cancer monitoring due it is non-ionizing and the potential for cost saving and simpler system as compared to the current imaging techniques. The frequency selection is crucial in this application due to no bandwidth proven best. However, the amount of antenna is said affected the image resolution. This paper is an attempt to review the frequency selection and the antenna arrangement system in the past decades works for future antenna development in early breast cancer detection.
Segmentation of Cortical and Cancellous Bone with Osteogenesis Imperfecta using Thresholding-based Method
Authors: Voon Tan Tze , Som Mohd Hanafi Mat , Yazid Haniza , Basaruddin Khairul Salleh , Sulaiman Abdul Razak 
Published: November 2019

Abstract
Osteogenesis Imperfecta (OI) is a genetic bone disorders that mainly affect the bones which commonly leads to the multiple fractures. The purpose of this study is to segment the cortical and cancellous bone of tibia affected with the OI from the CT images. This project consists of two sections, segmentation of the cortical and cancellous bone, and the evaluation of the image performance. Contrast adjustment was implemented to enhance the contrast of images. K-Means and multi-threshold were implemented to segment the cortical bone at the proximal, diaphysis, and distal tibia. Post-processing was applied to further refine the segmented images. All segmented images were then evaluated by using the ground truth images. From the results, the process with contrast adjustment and multi-threshold obtained the highest accuracy and Dice-coefficient of 99.91% and 81.42% respectively at the proximal region while 99.93% and 73.88% at the distal region. However, pathway that make use of K-Means performed best in diaphysis region. This method has obtained the highest accuracy and Dice-coefficient of 99.98% and 95.59% respectively.
Pearson’s Correlation Coefficient Analysis of non-invasive Jaundice Detection based on Colour Card Technique
Authors: Abu Bakar Asyraf Hakimi , Mohd Hassan Mohd Najmuddin , Zakaria Ammar , Abdul Halim Ahmad Ashraf 
Published: November 2019

Abstract
Jaundice is describes as yellow discoloration of the skin and other tissues of a newborn infant. It happens when the bilirubin pigment rises up to 5 mg/dL or 85 μmol/L due the organs just started to developed. 75% of newborns in Malaysia had jaundice in the first week of life. Conventional assessment method is not convenient since it unable to detect all type of human skin colours, caused traumatization and costly. This research work proposed jaundice detection system based on the colour card technique that represent all types of human skin colours. This research does not involve any subject due to parent’s cooperation and ethics limitation. The input data is represented by the colour card shades. It represents random bilirubin colour in patient’s body, all types of human skin colour, and standard reference bilirubin concentration colour. It acquires input data by capturing different type of colour card shades using OPT101 photodiode sensor and USB4000-XR1-ES spectrometer. The input data collected were verified through Anderson-Darling normality test and analysed using Pearson’s correlation coefficient to measure the strength of the association between the two variables for each input sample tested. Based on the correlation results, it shows high correlation value (r=0.997). Percentage error analysis is used to validate the experimental device and shows value of 9.90% which prove this technique is reliable. The significant contributions of this work is the improvement of the accuracy in detecting jaundice level for all type of human skin colours through this system.
Fabrication and Biomechanical Evaluation of Polyurethane Material for Synthetic Bone
Authors: Zulkefli Siti Adawiyah , Shaikhani Maryam Hanim , Nasution Ahmad Kafrawi , Wahab Asnida Abdul , Abdul Kadir Mohammed Rafiq , Ramlee Muhammad Hanif 
Published: November 2019

Abstract
Synthetic bone has become an important tool for education in the orthopaedics field and biomechanical research. The use of the conventional tool such as cadaver has become a challenge to the researcher and orthopaedic surgeon, as it was highly cost, ethical issues and storage. In addition, the available synthetic bones in the market were expensive and only in European size. This research was focusing on developing the synthetic bone using polyurethane material, evaluate the mechanical strength of the developed synthetic bone and characterize the morphological structure of the developed synthetic bone. The development of the synthetic bone was using Polyurethane (PU) as its material. Two type composition of PU was used for this research. The material mixed and poured into the mould that has been designed according to American Society Testing and Material (ASTM) standard which was ASTM-F1839. Then, composition 1 and composition 2 undergo mechanical testing and morphology analysis by using Instron and Scanning Electron Microscopy (SEM) respectively. The average Young’s Modulus of composition 1 and composition 2 were 208.6963 MPa and 384.6304 MPa respectively. In short, the developed synthetic bone has greater Young’s modulus compared to the synthetic bone that available in the market and which are 132.3254 MPa (Sawbone) and 68.1483 MPa (Synbone). The morphological analysis has shown the fabricated synthetic bone has compact structure compare to the one in the market that mimic the cancellous bone. In conclusion, composition 2 of PU have the highest Young’s modulus but from the morphological analysis it does not mimic the morphology of cancellous bone.
Finite Element Approach Using Electrical Tomography for Bioassay Application
Authors: Ropandi Wan Aizatul Nadihah Binti , Zulkiflli Nur Amira , Nawi Nina Diana , Abdullah Fatin Aliah Phang , Pusppanathan Jaysuman , Zakaria Zulkarnay 
Published: November 2019

Abstract
Single-cell imaging is a part bioassay application that is highly used in the studies of microbiology. This bioassay application is used in order to determine the cell activity, behaviour and reaction as well as electrical properties and characteristic. Most of this can be achieved by using mass spectrometry, impedance analyser and flow cytometry. Currently, there is an emerging trend of on-chip integrated device that allows bioassay application to be performed real time. However, in terms of cell monitoring, which allows us to view the cross section image of cell, there is much to be explored. As each cell is composed of different material with specific relative permittivity, Electrical Capacitance Tomography is chosen to determine the electrical properties and spatial distribution of cell. Therefore, the purpose of this research is to simulate Electrical Capacitance Tomography for yeast cell growth in order to determine the most suitable configuration needed for ECT system.
Voice Pathology Analysis using DT-CWPT and ReliefF Algorithm
Authors: Kassim Farah Nazlia Che , Vijean Vikneswaran , Muthusamy Hariharan , Abdullah Rokiah , Abdullah Zulkapli 
Published: November 2019

AbstractVoice pathology analysis has been one of the useful tools in the diagnosis of the pathological voice. This method is non-invasive, inexpensive and reduces time required for analysis. This paper investigates the feature extraction based on the Dual-Tree Complex Wavelet Packet Transform (DT-CWPT) with entropies and energy measures tested with two classifiers, k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM). Feature selection using ReliefF algorithm is applied to reduce redundancy features set and obtain the optimum features for classification. Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and Saarbruecken Voice Database (SVD) are used. This research was done on multiclass and by specific pathology. The experimental results automates the process of voice analysis hence produce promising results of the presence of diseases in vocal folds.
Image quality assessment (IQA) using high-frequency and image variance (HFIV) for colour image
Authors: Tan Li Chien , Yazid Haniza , Chong Yen Fook 
Published: November 2019

Abstract
Image quality is often lost during image acquisition, transmission, and compression. Therefore, image quality assessment (IQA) is crucial in image processing. Currently, image quality can be measured from the frequency domain features, but it only applicable to blurred grayscale images. Nevertheless, noise distortion is also a common problem in digital images, and colour also affects the perception of image quality. Therefore, this paper proposes an enhanced blur and noise specific colour image quality assessment that measures high-frequency components and image variance. The number of high-frequency components is related to the edge and noise. In order to distinguish the distortion of the image, the image variance estimation is included. Experiments on public databases have shown that this method outperforms PSNR and SSIM in terms of noise and blur distortion and has low processing time of 0.0941 s/img.
The Effect of Material Characteristic of Shoe Soles during Long Duration Running
Authors: Cheng Chan Siow , Tan J P , Qing Tan Yin 
Published: November 2019

AbstractLong duration running has been associated with musculoskeletal injuries such as patellofemoral pain syndrome and knee osteoarthritis. This study was designed to investigate the effects of two different shoe insoles on kinematic and kinetic performance during long duration running. In total 15 subjects (7 males and 8 females) were recruited to perform 15 minutes continuous running on the treadmill in 3 different shoe insole conditions: (i) no insole; (ii) Ethyl Vinyl Acetate (EVA) insole and (iii) Polyurethane (PU) insole. The result revealed a significant increase in maximum vertical ground reaction force (VGRF) with the PU insole compare with the no insole and EVA insole conditions (p<0.05). There is no difference between conditions in kinematic variables: step length, stride length and cadence (p>0.05).
Encapsulation of C. odorata extracts for antimicrobial activity
Authors: Azmi Siti Nur Amylina , Mohamad Che Wan Sharifah Robiah , Kasim Khairul Farihan 
Published: November 2019

Abstract
The purpose of this study is to investigate the relationship between the methycellulose (MC) and ethylcellulose (EC) of encapsulated C. odorata extracts (methanol and ethanol) and their antimicrobial properties against E. coli and Staphylococcus aureus. The encapsulated of C. odorata extract was prepared by solvent displacement method through dialysis tube cellulose membrane and it was freeze-dried to obtain the suspension of encapsulated C. odorata extract. Then, antimicrobial properties of encapsulated C. odorata extracts was performed by broth dilution method on target bacteria. A few drops of hydrochloric acid (HCl) were added into growth media until pH 4 to mimic the acidic conditions in human stomach. The results showed the encapsulated methylcellulose of methanol extract (MC-M) inhibit both bacteria types.
Classification of Microorganism Species Based on Volatile Metabolite Contents Similarity
Authors: Abdullah Azian Azamimi , Aziz Amira Najihah Abdul , Kanaya Shigehiko , Ranjan Dash Satya 
Published: November 2019

Abstract
Microorganism species can become pathogenic and cause bacterial infection, result from the imbalance in microbial ecosystem between host and microbe. Microorganisms emit secondary metabolites, known as volatile metabolites or organic compounds (VOCs) for various functions such as intra- or inter-species interactions, defense and attraction. Currently, VOCs are widely used as a biomarker for human diseases. This research is aimed to identify the relationship between microorganism species and volatile metabolite compound from the collected species and VOCs emitted organism data by using unsupervised machine learning approaches such as hierarchical clustering and graph-clustering method. Supervised machine learning methods also been used to classify the microorganism pathogenicity such as support vector machine (SVM) and random forest (RF). These data are collected from KNApSAcK and mVOC database where it provides most of the microorganism species and metabolites contents. From the collected data, there are in total of 1088 VOCs emitted by 517 microorganism species. As a result, the application of machine learning methods enable us to identify the relationship of species with their emitted VOCs and classify the microorganism species into their own pathogenicity.
PCA-Polynomial-ELM Model Optimal for Detection of NS1 Adulterated Salivary SERS Spectra
Authors: Othman Nur Hainani , Yoot Lee Khuan , Mohd Radzol Afaf Rozan , Mansor Wahidah , Amanina Yusoff Nur 
Published: November 2019

Abstract
Of recent, there has been much interest in the application of Surface Enhance Raman Spectroscopy (SERS) analysis in the detection of diseases such as dengue. Early diagnosis of dengue affords early intervention, greater chance of cure and prevention of mild dengue progressing into life threatening stage. SERS produces, on the interaction of photons from laser beam with saliva samples, a spectral image of its composition here. In the case of dengue fever, Non–Structural Protein 1 (NS1), being its biomarker, is the biochemical fingerprint to be revealed by SERS. NS1 presents in body fluid such as blood and saliva of patients since day one of infection, that makes NS1 a favourite alternative to antibody types of biomarker. However, the concentration of NS1 in saliva is low, yielding a low intensity SERS spectrum. In addition, the spectrum is usually interfered with undesirable noisy features. Extreme Learning Machine (ELM) is a fast algorithm with its strength in data pattern generalization. It has been applied in pattern recognition and machine learning for classification and regression, with encouraging performance. Our work here intends to determine an optimal polynomial-ELM model in classifying SERS spectra of saliva samples adulterated with NS1, amongst the different models subject to three different termination criteria of Principal Component Analysis (PCA). Performance of ‘100%’ is attained for accuracy, sensitivity, specificity and precision, while ‘1’ for kappa, by combining the cumulative percent of total variance (CPV) termination criterion and polynomial-ELM model of power 2 and constant 0.5.
Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
Authors: Jusoh Nurfarhana Hazwani , Yazid Haniza , Basah Shafriza Nisha , Abdul Rahim Saufiah 
Published: November 2019

Abstract
This research aims to detect the pulmonary nodule presented in lung Computed Tomography (CT) scan images. Generally, a Computer-Aided Diagnostic (CAD) system was designed and developed to aid the radiologists in medical imaging department to reduce the time and to obtain faster and better results for lung nodules diagnosis of a patient. Four major stages involve in this paper which are pre-processing, segmentation, features extraction and classification. The images that were utilized were acquired from LIDC-IDRI database that available publicly for CT scan lung images. Initially, the median filter was employed in pre-processing to filter and remove the noises, unwanted distortions and artifacts presented in the images during scanning process. For the second stage, the implementation of Otsu thresholding (thresholding-based method) and watershed algorithm (region-based method) were used to segment the nodules (Region of Interest (ROI)). Manual cropping method was implemented to segment the nodule for further process. The main contribution of this paper is the extraction of the features based on shape descriptor. 10 features were extracted from the segmented nodules. Finally, all extracted features from the segmented nodules were classified into nodule candidates and non-nodule candidates using Back Propagation Neural Network (BPNN). Based on the experiment, it can be observed that the proposed approach works well with CT scan images and segmented the interested nodules with the accuracy of 94%. This semi-automated approach is fast compared with the conventional approach used by the radiologists in current time being.
Design and Optimize Solid Microneedle using Genetic Algorithm
Authors: Zaharin Nurul Fatihah , Markom Marni Azira , Tan Erdy Sulino Mohd Muslim , Sabani Norhayati 
Published: November 2019

Abstract
Microneedle is an example of Transdermal drug delivery (TTD) device. It is known for eliminating pain and inconvenient intravenous injections. This study presents a work on design microneedle and optimize the designs using Genetic Algorithm (GA). At first, a few solid microneedles are designed with difference parameters, and the considered parameters involve are shape of the needle, materials, size of array, base of microneedle, height of microneedle and number of needles on the microneedle’s array base. The microneedle is designed to meet the output requirement which are the total deformation and equivalent stress. Pressure on the tip and size of microneedle base are set to be constant which are 3.18 MPa and 2500 μm × 2500 μm × 50 μm, respectively. Then, optimisation process is conducted on the designs using Genetic Algorithm. Based on the optimisation results, it showed that the optimum structure for the studied microneedles is canonical type, diameter and needle height are 500 μm and 500 μm, respectively, PVA material and involve with 3 number of needles. The results showed that GA is capable to achieve the output requirement and able to optimize the parameter of the microneedle structure.
Hardened Glass Particle and Carbon Black Using Resin for Potential Electromagnetic Shielding in Biomedical Electronic Equipments
Authors: Meng Cheng Ee , Abdul Majid Mohd Shukry , Bakar Shahriman Abu , Mohd Nasir Nashrul Fazli , Fhan Khor Shing , Yeow You Kok , Yee Lee Kim , Mohd Jamir Mohd Ridzuan , Hong Tan Wei , Ridha Shaharuddin Shahrir , Chong You Beh 
Published: November 2019

Abstract
This study aims to investigate the electromagnetic properties of a composite of hardened glass particle and carbon using resin in determining the absorbability of the composite for electromagnetic interference (EMI). The electromagnetic absorption measurement was conducted using T-R method (transmission-reflection) by measuring the dielectric constant, loss factor, real and imaginary part of permeability, reflection coefficient and transmission coefficient. The measurement is taken for X band frequency and Ku band frequency within the frequency range from 8.2GHz to 12.4GHz and 12.4GHz to 18GHz, respectively. Dielectric constant of sample decrease when frequency increases. The high dielectric constant of material implies that the material has high absorbability of field energy, resulting in high attenuation of the applied field.
Investigation on Green Properties of Magnesium Alloy AZ31 Feedstocks Molded via Metal Injection Molding Process
Authors: Zainon Nooraizedfiza , Omar Mohd Afian , Rosli Nur Liyana Mohd , Marzuki Marina 
Published: November 2019

Abstract
Powder loading is an important parameter because of its role in part shrinkage, dimensional stability, and final density. Thus, this research investigated the properties of the molded magnesium feedstocks in determining the best powder loading for producing magnesium part through metal injection molding process. In this research, the feedstocks with three magnesium alloy AZ31 powder loading of (63, 65, 67) vol%, was prepared comprising the binder component of paraffin wax, high density polyethylene, waste plastic, and stearic acid (PW/HDPE/WP/SA) with weight fraction 55/21/14/10, respectively. After injection molding, the density, diamensional accuracy, and strength of the green part was investigated. The findings reveal that 65 vol% of powder loading resulting to the best green properties.
The Optimization of the Hydroxyapatite (HA) Material Characteristics Produced From Corbiculacea (Etok) Shells
Authors: Roslan Mohd Riza , Nasir Nashrul Fazli Mohd , Khalid Mohd Farid Abdul , Mohammad Nur Farahiyah , Meng Cheng Ee , Hashim Nor Nabielah Nazihah , You Beh Chong , Majid Mohd Shukry Abd. , Amin Nasrul Amri Mohd 
Published: November 2019

Abstract
Hydroxyapatite commonly used in medical field for tissue disease, bone disease, drug delivery and also for non-medical field purpose such as wastewater treatment. Due to excellent biocompatibility and bioactive properties, hydroxyapatite (HA) which is a group of calcium phosphate (CaP) and similar to the natural bone composition has been broadly ventured in medical area. Synthesising the HA was done via precipitation method by implementing the Corbiculacea (Etok) shells as the resource of calcium precursors. Calcination of Corbiculacea (Etok) shells took place to convert calcium carbonate (CaCO3
) to calcium oxide (CaO). CaO were then reacted with water to form calcium hydroxide (Ca(OH)2) and later, reacted with phosphoric acid(H
3
PO
4). This experiment manipulated the CaP ratio to study the properties HA formed. CaP ratios used are 1.50, 1.67 and 2.00. The characterization were performed using Energy Dispersive X-Ray Spectroscopy (EDS), Scanning Electron Microscopy (SEM) and Fourier Transformation Infrared (FTIR).
Analysis of Drought Potential in Sumba Island until 2040 Caused by Climate Change
Authors: Sipayung Sinta Berliana , Susanti Indah , Maryadi Edy , Nurlatifah Amalia , Siswanto Bambang , Nafayest Muhammad , Putri Fanny Aditya , Hermawan Eddy 
Published: November 2019

Abstract
Climate Change is one of the events that can change climate components due to global warming events. One of the changes in climate components can cause changes in rainfall in an area. While changes in rainfall conditions in an area can cause increased vulnerability of a region to potential of drought. In this research, the effects of climate change on the drought potential in Sumbawa Island region was investigated, where this region is one of the areas prone to drought in Indonesia. Climate projection until 2040 was carried out using the Conformal Cubic Atmospheric Model (CCAM) model with 14 km spatial resolution and monthly temporal resolution. While the drought index is calculated by the SPI (Standardize Precipitation Index) method where positive numbers tend to mean wet, lift between -1 to 1 is neutral, and increasingly negative numbers tend to mean dry. It is known that in 2040 January was known that there would be no drought on Sumbawa Island with values ranging from -1 to 2. While in August of 2040, the potential for drought disaster should be watched out. This is because in this month the drought index value ranges from -2.5 to - 2. The potential for drought itself is known to increase in August 5 years until 2040 when compared with 5-year data, 2025 and 2030 in August in the Bima region. Meanwhile, based on time series analysis, it is estimated that there will be some extreme dry conditions, in August 2022, 2024, 2028, 2030, and 2033. Knowing these extreme conditions, it is hoped that this will become the basis for regional planning systems, starting from planning infrastructure and social systems to climate change mitigation and adaptation.