bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technologies of solar tracking systems: A review
Authors: Amelia A.R. , Irwan Y.M. , Safwati I. , Leow W.Z. , Mat M.H. , Rahim Mohd Shukor Abdul 
Published: March 2020

Abstract
Solar energy is abundantly in nature and sustainable energy resources around the world. The main challenge with the solar field is less amount of sun energy captured by using photovoltaic (PV) systems. The great performance of the PV systems can be achieved if the panel is kept perpendicular to the direction of the radiations of sun. Hence, solar tracker system is the method to keep the optimum position of the PV panel for always perpendicular to the solar radiation. This paper aims to review on various technologies of solar tracking to determine the best PV panel orientation. The various types of technologies of solar tracking system have been discussed which includes passive solar tracker, active solar tracker and chronological tracker system. The movement degrees of solar tracking system also have been addressed which consisting single-axis solar tracking system and dual-axis solar tracking system. This paper is also overviews the tracking techniques performance, construction, performance, advantages, and disadvantages of existing solar tracking system. The limitations of solar tracking systems are also highlighted for future action improvement. Through this research studies, the most favorable solar tracking system was identified as active solar tracker with the dual axis rotation.
Voice-Based Malay Commands Recognition by Using Audio Fingerprint Method for Smart House Applications
Authors: Abu M , Amir A , Zahri N A H , Ngadiran R 
Published: March 2020

Abstract
Voice-based command recognition is commonly used in security systems, phones, household appliances and hardware designed for handicapped people. Most of the current research study the voice command recognition for the smart home in English. Lack of study for voice command recognition in Malay makes it challenging to apply the voice command services for the smart home in Malaysia. Also, voice recognition is a non-trivial task in natural language processing. This project is to identify the command used for smart home appliances using Malay and design the algorithm for this system. Then, the proposed algorithm will be deployed on a Raspberry Pi to see the performance of Malay command in accuracy and the suitability of the algorithm to be deployed on low cost embedded devices. Light, fan, and television had been chosen as electrical appliances to build the command. An algorithm that previously used to recognize songs, the robust quad algorithm, is used in this project for voice command recognition. The proposed method has two main processes, known as feature extraction and voice recognition. In the feature extraction process, the audio fingerprint will extract data from the command spectral peak. For voice recognition, audio fingerprint matching will be used to analyze the audio commands. The outcome of this project is when the voice command is given by the user by activate or deactivate the target home appliance. The second outcome is the background noise that affects the system is reduced by using robust quad algorithm and increase the accuracy of the system. The results of this project have shown that the proposed algorithm is suitable to be implemented on a Raspberry Pi and achieve a high recognition rate with 87%. In the presence of noise with 15 dB, the proposed algorithm can maintain the high recognition rate with 82%.
Comparative Study of Parallelism and Pipelining of RGB to HSL Colour Space Conversion Architecture on FPGA
Authors: Ehkan Phaklen , Siew Soon Voon , Zakaria Fazrul Faiz , Mohd Warip Mohd Nazri , Ilyas Mohd Zaizu 
Published: March 2020

Abstract
RGB colour model is a basic colour model and complements together to produce full colour range but it is unable to produce sufficient information for digital image analysis. However, HSL is capable to provide other useful information such as colour in degree, saturation of the colour and brightness of colour. In this work, RGB to HSL mathematical conversion algorithm is implemented on FPGA chip. Parallelism and pipelining capabilities of FPGA helps to speed up conversion performance. The RGB to HSL equation is implemented by using two architectures which are parallel and 7-stages pipeline architectures. The designed parallel and pipeline converters have one clock and seven clock cycle of data latency respectively. The parallel and pipeline architectures for RGB to HSL converter have been achieved rate of accuracy by hardware verification up to 99% and 98% and possessed maximum operating frequency merit of 50 MHz and 120 MHz respectively.
Indoor Navigation System for Vision Impairment People through Visible Light Communications
Authors: Rithuan Muhamad Nurnajib , Md Zain ‘Aini Syuhada , Nawawi Norizan Mohamed 
Published: March 2020

Abstract
Indoor navigation is opportune for everyone, and it is particularly requisite for the visually impaired. The paper proposes an indoor navigation system for the Visually Impaired to attain audio output through visible light communications. The transmission of data occurs after identifying the person who has entered the room and the technology light fidelity is used for presenting information to the user. Light fidelity technology is used by the proposed system for the wider range of transmission of data. The usage of visible light for transmitting the data encompasses a wide variety of advantages and eliminates most problems of communication caused by the electromagnetic waves outside the visible spectrum. Light fidelity technology is an evolving branch of Optical Wireless Communication and can be beneficial in coming years for indoor communication because it can afford higher data rate transmission along with the capability to utilize additional users since it uses a broader spectrum bandwidth. The main idea of our project is to create internal navigation system by using Arduino software and Arduino hardware. The transmission of data can act as transceiver, where LED and solar cell are used as the medium to transmit and receive the data.
Design of Compact UHF-RFID Tag Antenna with Meander Line Technique
Authors: Fazilah A F M , Jusoh M , Zakaria A , Sabapathy T , Ibrahim M F , Osman M N , Yaasin M N , Malhotra S , Rahim H A 
Published: March 2020

Abstract
In this paper, a compact UHF RFID tag antenna that can operate at Malaysia UHF RFID frequency (860 MHz – 960MHz) is proposed. The antenna with a common geometry structure without any shorting pin consists of 90degree angled line (meander line) and double T-match structure. The proposed antenna has been designed and simulated using CST Simulation software. The proposed tag antenna design shows a good performance in terms of size, gain and impedance with a dimension of 36 mm × 25 mm × 1.6 mm. The simulated gain of antenna obtained is -0.135 dB at 910 MHz with 19 MHz bandwidth.
Shared Cache Partitioning Based on Performance Gain Estimations
Authors: Mahrom N , Liebelt M J 
Published: March 2020

Abstract
In multiprocessor systems, dynamic cache distribution has been used to increase system performance by effectively partitioning the cache resources. However, different performance metrics used at runtime used to dynamically decide the partition sizes can give different impacts on performance, as well as varying impacts on the hardware cost of the system. In this paper, we propose an Adaptive CPI-based Cache Partitioning (ACCP) scheme to provide better utilisation of the shared cache resources among the competing applications in the system. ACCP uses performance gain estimations of the cache, without incurring significant hardware overhead. It aims to allow all applications in the system to run at approximately the same speed by accelerating the slowest application without significantly decelerating the others. We evaluated the ACCP on a quad-core system on which it achieved on average 23% reduction in miss rate, compared to an unpartitioned shared cache. ACCP also yields a similar IPC throughput improvement to a well-known UCP scheme, and better performance compared to the CPI by Muralidhara et al. Overall, the throughput of the system is improved at minimal complexity without yielding significant additional hardware cost. Hence, ACCP shows better overall performance in managing the hardware overhead compared to the UCP scheme.
Miniaturized and high gain RFID reader antenna at 13.56MHz
Authors: Saleh Y.M. , Wee F.H. , Yew B.S. , Ibrahim S. Z. , Lee Y.S. 
Published: March 2020

Abstract
Technology for radio frequency identification (RFID) is commonly used worldwide. RFID is a developing wireless technology which make new vital challenge. The ability to precisely read a set of RFID tags become major concern in RFID networks coverage Detailed analysis of the design based on the 13.56 MHz radio frequency was suggested to design a kind of RFID reader antenna. Previously, researchers did facing problem with the size of the antenna which was to maintain the compact size at low frequency is challenging. The proposed antenna will be designed in the shape of rectangular spiral which contribute into miniaturize of the antenna size. The antenna will be fabricated after the optimum length and width had been achieved. The goal of this project is to design a small size antenna with 55mm × 55 mm at frequency resonance of 13.56 MHz. to reduce the antenna gain on the future. We are going to design and add the metamaterial to the RFID reader antenna and combine them together and that will help to reduce the antenna gain.
Mobile Augmented Reality (AR) Marker-based for Indoor Library Navigation
Authors: Romli Rusnida , Razali Amir Firdhaus , Ghazali Nur Hafizah , Hanin Nik Adilah , Ibrahim Siti Zuraidah 
Published: March 2020

Abstract
This paper presents the development of Augmented Reality (AR) for smart campus urbanization using library as the environment for the demonstration of the AR prototype. The main goal of the AR development is to help users to get information and direction easily using AR based mobile application when walking inside the library. In normal circumstances, users typically walk around and explore the library area before reaching their targeted destinations. Depending on the library size and number of reading corners, exploration and walking in the library can be time consuming. Therefore, an AR technology is introduced in this paper to improve the user experience inside the library in the right direction and information instantly. This application is developed using Vuforia software to set the image marker-based and process the output into Unity3D software, Android Studio for the Main Menu interface and IBM Watson for voice recognition. The final form of the application is successfully generated from the development of Augmented Reality (AR) application for the smart campus by using a library for the demonstration of the AR prototype. A series of application tests are conducted in each corner of the library to evaluate the effectiveness of developed AR.
Effect of acids formation on the breakdown voltage properties of transformer insulating oil
Authors: Chairul Imran Sutan , Ghani Sharin Ab , Bakar Norazhar Abu , Rahim Nor Hidayah , Ab Aziz Nur Hakimah 
Published: March 2020

Abstract
Studies show that acids influence the electrical insulation strength of transformer insulating oil. Thus, this study was conducted to verify the influence of Low Molecular Acid (LMA) and High Molecular Acid (HMA) on the breakdown voltage of transformer insulating oil. Different weight of LMA and HMA were added into transformer insulating oil samples and then mixed using hotplate magnetic stirrer at 50°C and 750 rpm for 3 hours. Prior to the mixing process, mineral insulating oil samples were filtered, dried and its moisture content were determined according to ASTM D1533 standard test condition. After the mixing process, total acid number (TAN) and AC breakdown voltage (BdV) of the oil mixtures were measured according to standard test conditions of ASTM D974 and ASTM D1816 respectively. The obtained results verified that LMA significantly reduced the breakdown voltage of mineral insulating oil compared to HMA for acidity lower than 1 mg KOH/g.
Automated Detection of Printed Circuit Boards (PCB) Defects by Using Machine Learning in Electronic Manufacturing: Current Approaches
Authors: Zakaria S S , Amir A , Yaakob N , Nazemi S 
Published: March 2020

Abstract
The manufacturing of a printed circuit board in the SMT assembly line goes through multiple phases of automatic handling. To ensure the quality of the board and reduce the number of defects, inspection tasks such as solder paste inspection and automatic optical inspection are conducted. The inspection tasks are carried out at various phases of the assembly line. The paper aims to answer the questions of how machine learning technology can contribute for better PCB fault detection in the assembly line and at which parts of the assembly line this technology has been applied. The paper discusses the PCB defect detection by using machine learning and other approaches. The current research shows that PCB defect detection using machine learning are miniscule. Early detection is still unexplored and experimented in the industry.
Real-Time Drowsiness Detection System for Driver Monitoring
Authors: Arunasalam M , Yaakob N , Amir A. , Elshaikh M , Azahar N F 
Published: March 2020

Abstract
Nowadays, the rate of road accidents due to microsleep has been alarming. During microsleep, people might doze off without realizing it. For many decades, drowsiness detection system for vehicles was not among the major concerns though it turns out as one of imperative features that could have avoid microsleep and thus should be implemented in all vehicles in order to ensure safety of drivers and other vehicles on the road. To the best of our knowledge, enforcements on driving restriction during drowsiness state is yet to be implemented. The absence of such system in the current transportation systems expose drivers to great danger especially at night because accidents are highly likely to happen at night due to drowsy and fatigue drivers. Therefore, this project proposes a real-time drowsiness detection system for vehicles, featuring ignition lock to reduce accidents. An eye blink sensor is embedded in a wearable glasses and heart beat sensor is used to detect drowsiness level of drivers. The system also includes SMS notification system to relatives or friends with location details of the drowsy driver. This project is able to detect and react based on 3 levels of drowsiness by alerting the driver through buzzer. Ignition lock will be applied when high level of drowsiness is detected. Consequently, the vehicle will be slowed down and eventually stopped when dangerous level of drowsiness is detected as a safety precaution.
Machine Learning Algorithms for Optic Pathway Disease Diagnostics: A Review
Authors: Abu M , Zahri N A H , Amir A , Ismail I 
Published: March 2020

Abstract
Most of people are unaware that some of the indicators of optic pathway diseases such as stroke or tumor can be detected from the loss part of human vision, or referred as visual field defect. Ophthalmologist will manually examine the site, size and margin of the lesion from patient’s visual field points mapped by Humphrey Field Analyzer. Different site, size and margin of lesion indicates different type of defects and disease that associated with it. Therefore, an effective automated detection mechanism of multi class visual field defect is in demand to help decision making by ophthalmologist. In this paper, we review multiple techniques of supervised and unsupervised learning method for detection of optic pathway disease.
Low Cost Autonomous Robot Cleaner using Mapping Algorithm based on Internet of Things (IoT)
Authors: Ong R J , Azir K N F Ku 
Published: March 2020

Abstract
The objective of this study is to design and develop a low-cost Arduino autonomous robot cleaner using mapping algorithm to clean floor area of houses or offices. The idea is basically to detect any obstacles with the help of sensor and sent its output to microcontroller that will control the autonomous vacuum cleaner movement. A low-cost solution is proposed in this study by using HC-SR04 ultrasonic sensor for obstacle avoidance and control by Arduino UNO. By using an autonomous vacuum cleaner, user can turn ON the autonomous vacuum robot to clean without any help of a human operator. Wall mapping and random mapping is being applied in this study to find the effective mapping algorithm for autonomous robot cleaner. Additionally, instead of using the traditional button or switch to activate the robot, voice recognition through Google Assistant implemented in this project. Hence, this provides a more user friendly platform not only for normal user but also help visually impaired people to activate the robot.
Inclusion of Cannabis Users in Alcohol Research Samples: Screening In, Screening Out, and Implications
Authors: Venegas Alexandra , Meredith Lindsay R , Cooper Ziva D , Towns Brandon , Ray Lara A 
Published: March 2020

Abstract

Background
Alcohol and cannabis are frequently co-used, as 20–50% of those who drink alcohol report co-using cannabis. This study is based on the argument that alcohol researchers should enroll cannabis users in human laboratory studies of alcohol use disorder (AUD) to strengthen generalizability. This study examines how heavy drinking cannabis users differ from non-cannabis using heavy drinkers.

Methods
In a community sample of non-treatment-seeking heavy drinkers (n = 551, 35% female), cannabis users were identified through: (a) self-reported cannabis use in the past 6 months and (b) positive urine toxicology test for tetrahydrocannabinol (THC). Cannabis users, identified as described previously, were compared with non-cannabis users on demographic and clinical characteristics.

Results
Those who endorsed cannabis use in the past 6 months reported more binge drinking days. Participants who tested positive for THC had higher Alcohol Use Disorder Identification Test scores and more binge drinking days. Younger age and being a tobacco smoker were associated with an increased likelihood of cannabis use in the past 6 months, whereas male gender and being a tobacco use were associated with a greater likelihood of testing positive for THC. Individuals with cannabis use disorder (CUD) endorsed more depression and anxiety and had higher AUD symptom counts than cannabis users without CUD.

Conclusions
The inclusion of cannabis users in AUD samples allows for increased clinical severity. Excluding cannabis users from AUD studies may limit representativeness and expend unnecessary study resources. Lastly, tobacco use may explain a large portion of the effects of cannabis use on sample characteristics.

Short Summary
Alcohol and cannabis are frequently co-used substances. In a sample of non-treatment-seeking heavy drinkers (n = 551, 35% female), cannabis users reported higher alcohol use and higher likelihood of tobacco use than non-cannabis users. Including cannabis users in alcohol research studies will improve representativeness and likely increase clinical severity.
Systematics, biogeography, and diversification of Scytalopus tapaculos (Rhinocryptidae), an enigmatic radiation of Neotropical montane birds
Authors: Cadena Carlos Daniel , Cuervo Andrés M , Céspedes Laura N , Bravo Gustavo A , Krabbe Niels , Schulenberg Thomas S , Derryberry Graham E , Silveira Luis Fabio , Derryberry Elizabeth P , Brumfield Robb T , Fjeldså Jon 
Published: March 2020

AbstractWe studied the phylogeny, biogeography, and diversification of suboscine passerines in the genus Scytalopus (Rhinocryptidae), a widespread, species-rich, and taxonomically challenging group of Neotropical birds. We analyzed nuclear (exons, regions flanking ultraconserved elements) and mitochondrial (ND2) DNA sequence data for a taxonomically and geographically comprehensive sample of specimens collected from Costa Rica to Patagonia and Brazil. We found that Scytalopus is a monophyletic group sister to Eugralla and consists of 3 main clades roughly distributed in (1) the Southern Andes, (2) eastern Brazil, and (3) the Tropical Andes and Central America. The clades from the Southern Andes and eastern Brazil are sister to each other. Despite their confusing uniformity in plumage coloration, body shape, and overall appearance, rates of species accumulation through time in Scytalopus since the origin of the clade in the Late Miocene are unusually high compared with those of other birds, suggesting rapid non-adaptive diversification in the group. We attribute this to their limited dispersal abilities making them speciation-prone and their occurrence in a complex landscape with numerous barriers promoting allopatric differentiation. Divergence times among species and downturns in species accumulation rates in recent times suggest that most speciation events in Scytalopus predate climatic oscillations of the Pleistocene. Our analyses identified various cases of strong genetic structure within species and lack of monophyly of taxa, flagging populations which likely merit additional study to clarify their taxonomic status. In particular, detailed analyses of species limits are due in S. parvirostris, S. latrans, S. speluncae, the S. atratus complex, and the Southern Andes clade.
Epidemiological and Clinical Predictors of COVID-19
Authors: Sun Yinxiaohe , Koh Vanessa , Marimuthu Kalisvar , Ng Oon Tek , Young Barnaby , Vasoo Shawn , Chan Monica , Lee Vernon J M , De Partha P , Barkham Timothy , Lin Raymond T P , Cook Alex R , Leo Yee Sin ,   National Centre for Infectious Diseases COVID-19 Outbreak Research Team, Lian Lim Poh , Ang Brenda , Chuan Lee Cheng , Lye David Chien Boon , Ling Li Min , Lee Lawrence Soon-U , Sadarangani Sapna , Seong Wong Chen , Lee Tau Hong , Junhao Lin Ray , Chia Po Ying , Sadasiv Mucheli Sharavan , Ng Deborah Hee Ling , Choy Chiaw Yee , Yeo Tsin Wen , Tan Glorijoy Shi En , Chan Yu Kit , Tay Jun Yang , Lee Pei Hua , Ong Sean Wei Xiang , Sutjipto Stephanie , Wee Ian Liang En , Frederico Dimatatac , Go Chi Jong , Isais Florante Santo 
Published: March 2020

Abstract

Background
Rapid identification of COVID-19 cases, which is crucial to outbreak containment efforts, is challenging due to the lack of pathognomonic symptoms and in settings with limited capacity for specialized nucleic acid–based reverse transcription polymerase chain reaction (PCR) testing.

Methods
This retrospective case-control study involves subjects (7–98 years) presenting at the designated national outbreak screening center and tertiary care hospital in Singapore for SARS-CoV-2 testing from 26 January to 16 February 2020. COVID-19 status was confirmed by PCR testing of sputum, nasopharyngeal swabs, or throat swabs. Demographic, clinical, laboratory, and exposure-risk variables ascertainable at presentation were analyzed to develop an algorithm for estimating the risk of COVID-19. Model development used Akaike’s information criterion in a stepwise fashion to build logistic regression models, which were then translated into prediction scores. Performance was measured using receiver operating characteristic curves, adjusting for overconfidence using leave-one-out cross-validation.

Results
The study population included 788 subjects, of whom 54 (6.9%) were SARS-CoV-2 positive and 734 (93.1%) were SARS-CoV-2 negative. The median age was 34 years, and 407 (51.7%) were female. Using leave-one-out cross-validation, all the models incorporating clinical tests (models 1, 2, and 3) performed well with areas under the receiver operating characteristic curve (AUCs) of 0.91, 0.88, and 0.88, respectively. In comparison, model 4 had an AUC of 0.65.

Conclusions
Rapidly ascertainable clinical and laboratory data could identify individuals at high risk of COVID-19 and enable prioritization of PCR testing and containment efforts. Basic laboratory test results were crucial to prediction models.