bluuebunny/crossref_metadata_2025 huggingface dataset:
Fractional Theoretical Model for Gravity Waves and Squall Line in Complex Atmospheric Motion
Authors: Chen Liguo , Yang Liangui
Published: March 2020

The evolution of nonlinear gravity solitary waves in the atmosphere is related to the formation of severe weather. The nonlinear concentration of gravity solitary wave leads to energy accumulation, which further forms the disastrous weather phenomenon such as squall line. This paper theoretically proves that the formation of squall line in baroclinic nonstatic equilibrium atmosphere can be reduced to the fission process of algebraic gravity solitary waves described by the (2 + 1)-dimensional generalized Boussinesq-BO (B-BO) equation. Compared with previous models describing isolated waves, the Boussinesq-BO model can describe the propagation process of waves in two media, which is more suitable for actual atmospheric conditions. In order to explore more structural features of this solitary wave, the derived integer order model is transformed into the more practical time fractional-order model by using the variational method. By obtaining the exact solution and the conservation laws, the fission properties of algebraic gravity solitary waves are discussed. When the disturbance with limited width appears along the low-level jet stream, these solitary waves can be excited. When the disturbance intensity and width reach a certain value, solitary wave formation takes place, which is exactly the squall line or thunderstorm formation observed in the atmosphere.
U-Model Based Adaptive Neural Networks Fixed-Time Backstepping Control for Uncertain Nonlinear System
Authors: Zhang Jianhua , Li Yang , Fei Wenbo , Wu Xueli
Published: March 2020

Under U-model control design framework, a fixed-time neural networks adaptive backstepping control is proposed. The majority of the previously described adaptive neural controllers were based on uniformly ultimately bounded (UUB) or practical finite stable (PFS) theory. For neural networks control, it makes the control law as well as stability analysis highly lengthy and complicated because of the unknown ideal weight and unknown approximation error. Moreover, there has been very limited research focus on adaptive law for neural networks adaptive control in finite time. Based on fixed-time stability theory, a fixed-time bounded theory is proposed for fixed-time neural networks adaptive backstepping control. The most outstanding novelty is that fixed-time adaptive law for training weights of neural networks is proposed for fixed-time neural networks adaptive control. Furthermore, by combining fixed-time adaptive law and Lyapunov-based arguments, a valid fixed-time controller design algorithm is presented with universal approximation property of neural networks to ensure the system is fixed-time bounded, rather than PFS or UUB. The controller guarantees closed-loop system fixed-time bounded in the Lyapunov sense. The benchmark simulation demonstrated effectiveness and efficiency of the proposed approach.
Impact of Carotid Endarterectomy on Choroidal Thickness and Volume in Enhanced Depth Optical Coherence Tomography Imaging
Authors: Krytkowska Elżbieta , Masiuk Monika , Kawa Miłosz P. , Grabowicz Aleksandra , Rynio Paweł , Kazimierczak Arkadiusz , Safranow Krzysztof , Gutowski Piotr , Machalińska Anna
Published: March 2020

Purpose. Carotid endarterectomy (CEA) is considered an effective therapeutic method for improving ocular circulation. The choroid is a predominantly vascular tissue; thus, systemic and local vascular alterations may influence its morphology and function. The aim of the current study was to analyse changes in choroidal thickness and volume in patients with significant internal carotid artery stenosis (ICAS) before and after unilateral CEA. Methods. The 42 eyes of the 21 asymptomatic patients included in the study were divided into two groups: those ipsilateral (EIE) and those contralateral (ECE) to CEA. All participants underwent a complete ophthalmologic examination, including enhanced depth imaging-optical coherence tomography (EDI-OCT). A comparative analysis of subfoveal thickness (CT) and choroidal volume (CV) measured in nine Early Treatment of Diabetic Retinopathy Study (ETDRS) subfields at baseline, on the 2nd day after CEA, and in the 3rd month after CEA was performed. Results. In the EIE and ECE groups, no significant differences in either CT or CV values before and on the 2nd day after the CEA were observed. In the EIE group, a significant increase in CT and CV in the 3rd month after CEA compared to baseline was noted in the specific ETDRS region. Changes in CT and CV after surgery were positively correlated with the participants’ physical activity status and diastolic blood pressure and negatively correlated with the participants’ age and smoking status. Additionally, the analysis of changes in CV after CEA showed a positive correlation between the EIE and ECE groups. Conclusions. CT and CV fluctuations in the central and perifoveal areas visualized with EDI-OCT enabled the observation of the processes of tissue adaptation to variable blood flow conditions.
High-Resolution Remote-Sensing Image-Change Detection Based on Morphological Attribute Profiles and Decision Fusion
Authors: Wang Chao , Liu Hui , Shen Yi , Zhao Kaiguang , Xing Hongyan , Wu Haotian
Published: March 2020

Change detection (CD) is essential for accurate understanding of land surface changes with multitemporal Earth observation data. Due to the great advantages in spatial information modeling, Morphological Attribute Profiles (MAPs) are becoming increasingly popular for improving the recognition ability in CD applications. However, most of the MAPs-based CD methods are implemented by setting the scale parameters of Attribute Profiles (APs) manually and ignoring the uncertainty of change information from different sources. To address these issues, a novel method for CD in high-resolution remote sensing (HRRS) images based on morphological attribute profiles and decision fusion is proposed in this study. By establishing the objective function based on the minimum of average interscale correlation, a morphological attribute profile with adaptive scale parameters (ASP-MAPs) is presented to exploit the spatial structure information. On this basis, a multifeature decision fusion framework based on the Dempster–Shafer (D-S) theory is constructed for obtaining the CD map. Experiments of multitemporal HRRS images from different sensors have shown that the proposed method outperforms the other advanced comparison CD methods, and the overall accuracy (OA) can reach more than 83.9%.
Experimental Study on Mechanical Deformation Characteristics of Inclined and Straight Alternating Pile Groups
Authors: Kong Desen , Deng Meixu , Li Yazhou
Published: March 2020

In order to investigate the bearing characteristics of inclined straight alternating pile groups under vertical and horizontal loads, the indoor model test of 2 × 2 inclined straight alternating pile groups with two layers of soil on low pile caps was carried out, the manufacturing method of inclined straight alternating pile groups was studied, and the test scheme was reasonably designed. In the test, the fast maintenance load method was used to simulate vertical loads, and the horizontal force loading frame was designed to simulate horizontal loads. The experimental data were obtained by pasting strain gauges on the pile body, and the computer was used to process the data according to the mechanical formula. The distribution of axial force, lateral friction resistance, and end resistance of each characteristic pile of the pile group foundation was obtained, and the settlement law of the pile group was analyzed. At the same time, combined with the test data and the existing theories, the interaction mechanism between pile caps, piles, and soil of inclined and straight alternating pile groups is discussed. The load sharing characteristics between piles and pile caps are analyzed, and the horizontal load is in the proportion between straight piles and inclined piles. The stress characteristics of straight piles and pile groups in the pile group system are compared and analyzed, and some valuable conclusions are obtained.
Using Modified Fly Ash for Removal of Heavy Metal Ions from Aqueous Solution
Authors: Nguyen Thuy Chinh , Tran Trang Do Mai , Dao Van Bay , Vu Quoc-Trung , Nguyen Trinh Duy , Thai Hoang
Published: March 2020

This paper presents the characteristics of fly ash which was modified by 2-mercaptobenzothiazole (MBT) and sodium dodecyl sulfate (SDS) as the surfactants after treating with 1M NaOH solution. The change in morphology, specific surface area, crystal structure, and composition of the unmodified and modified fly ash was evaluated by FTIR, XRD, FESEM, BET, and EDX methods and techniques. The FTIR spectra of modified fly ash showed that there was no chemical reaction between the surfactants and fly ash. The XRD patterns and FESEM images indicated that modified fly ash had zeolite structure with a pore size of about 50 nm. Heavy metal ion adsorption behavior as well as adsorption isotherm models (Langmuir and Freundlich) of Cd2+ and Hg2+ ions of the unmodified and modified fly ash were also investigated and discussed. The amount of adsorbed ions of the modified fly ash was higher than that of the unmodified fly ash. The calculated results from the adsorption data according to the adsorption isotherm models of the above ions displayed that the Langmuir isotherm model was complied for the Cd2+ adsorption process while the Freundlich isotherm model was fitted for the Hg2+ adsorption process.
Review of Stereo Matching Algorithms Based on Deep Learning
Authors: Zhou Kun , Meng Xiangxi , Cheng Bo
Published: March 2020

Stereo vision is a flourishing field, attracting the attention of many researchers. Recently, leveraging on the development of deep learning, stereo matching algorithms have achieved remarkable performance far exceeding traditional approaches. This review presents an overview of different stereo matching algorithms based on deep learning. For convenience, we classified the algorithms into three categories: (1) non-end-to-end learning algorithms, (2) end-to-end learning algorithms, and (3) unsupervised learning algorithms. We have provided a comprehensive coverage of the remarkable approaches in each category and summarized the strengths, weaknesses, and major challenges, respectively. The speed, accuracy, and time consumption were adopted to compare the different algorithms.
The Influence of LED Lighting on Attention and Long-Term Memory
Authors: Lee Chung Won , Kim Jin Ho
Published: March 2020

The fact that the illuminance of LED lights affects human attention and long-term memory has been verified through various studies, but there are no consistent research results about what level of illuminance is effective. The aims of this study were to systematically verify the effects of LED lighting on attention and long-term memory. The experiment was designed with four illuminance levels—300 lx, 400 lx, 500 lx, and 1,000 lx—as experimental conditions to determine the effects of LED lights on attention and long-term memory. Participants in the experiment were 18 college students. The attention task was performed using a handmade attention measuring instrument. Long-term memory was measured by the word fragment completion (hereinafter, referred to as “WFC”) task on the memory retention volume of the learning task that was learned exactly 24 hours before. Of the total 20 tasks, the ratio of correctly retrieval tasks was used as a dependent variable. As a result, attention showed the highest performance with a mean performance of 19.39 (SD = 3.78) at 1,000 lx. A statistically significant difference was also found between the 1,000 lx and 300  lx conditions (p=0.01). On the contrary, long-term memory showed the highest retrieval rate at an average of 58.06% (SD = 22.57) at 400 lx, and long-term memory performance was better in the order of 500 lx (mean = 48.89, SD = 20.33), 1,000 lx (mean = 45.83, SD = 23.53), and 300 lx (Mean = 43.33, SD = 19.10). Statistically, there was a significant difference between 300 lx and 400 lx (p=0.01), 400 lx and 1,000 lx (p=0.01). Through this study, it was verified that the effects of attention and long-term memory are different according to the illuminance of LED lighting, and these results can be important data to clarify the influence of light on human memory in the future.
Association between Alanine Aminotransferase/Aspartate Aminotransferase Ratio (AST/ALT Ratio) and Coronary Artery Injury in Children with Kawasaki Disease
Authors: Wang Jinxin , Li Jiawen , Ren Yue , Shi Hongying , Rong Xing , Zhang Xuting , Shao Yiping , Wu Rongzhou , Chu Maoping , Qiu Huixian
Published: March 2020

Objective. To investigate the association between the aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (AST/ALT ratio, AAR) and intravenous immunoglobulin (IVIG) resistance, coronary artery lesions (CAL), and coronary artery aneurysms (CAA) in children with Kawasaki disease (KD). Design. We retrospectively studied 2678 children with KD and divided them into two groups: a low-AAR group and a high-AAR group with a median AAR of 1.13 as the cut-off point. The differences in laboratory data, clinical manifestations, and coronary artery damage rates were compared between the two groups. Results. The incidence of CAL was higher in the low-AAR group than in the high-AAR group at 2 and 3-4 weeks after illness onset (p<0.001, respectively). The IVIG resistance rate was significantly higher in the low-AAR group than in the high-AAR group (29.94% vs 21.71%, p<0.001). The levels of C-reactive protein, erythrocyte sedimentation rate, white blood cell count, bilirubin, fibrinogen, thrombin time, D-dimer, and brain natriuretic peptide were also significantly higher in the low-AAR group compared with the high-AAR group. The levels of albumin and IgG were significantly lower in the low-AAR group compared with those of the high-AAR group. The proportion of typical KD cases in the low-AAR group was significantly higher than that in the high-AAR group. Low-AAR correlated with the risk of coronary artery damage and IVIG resistance. Conclusion. Children with KD who had low-AAR value were more likely to develop coronary artery damage and IVIG resistance. Low AAR is a risk factor for CAL, CAA, and IVIG resistance in KD.
Vision-Related Quality of Life among Adult Patients with Visual Impairment at University of Gondar, Northwest Ethiopia
Authors: Yibekal Betelhem Temesgen , Alemu Destaye Shiferaw , Anbesse Dereje Hayilu , Alemayehu Abiy Maru , Alimaw Yezinash Addis
Published: March 2020

Purpose. The purpose of this study was to assess vision-related quality of life and associated factors among adult patients with visual impairment at the University of Gondar Tertiary Eye Care and Training Center, Northwest Ethiopia. Methods. The institution-based cross-sectional study was conducted from April 24 to May 12, 2017, at the University of Gondar Tertiary Eye Care and Training Center among 484 patients with visual impairment. Pretested, structured National Eye Institute Visual Function Questionnaire-25 was used to collect data by interviewing. Data were entered using EPI-INFO version 3.5.1 and analyzed with SPSS version 20. Binary logistic regression was used to determine factors associated with vision-related quality of life. Variables with p value <0.05 in multivariable logistic regression were considered as statistically significant. Result. A total of 484 study subjects participated with a response rate of 98.9%. The median age of the participants was 60 years with the interquartile range of 25 years. The proportion of poor vision-related quality of life was 238 (49.2%) (95% CI: 44.2%–53.3%). Age >75 years (AOR = 1.87 (95% CI: 1.02–3.40)), rural residency (AOR = 1.71 (95% CI: 1.13–2.60)), severe visual impairment/blindness (AOR = 2.76 (95% CI: 1.80–4.23)), and history of visual impairment longer than 3 years (AOR = 2.85 (95% CI: 1.61–5.04)) had statistically significant association with poor vision-related quality of life. Conclusion. Almost half of the patients with visual impairment had poor vision-related quality of life. Severe visual impairment/blindness, long duration of visual impairment, older age, and rural residency had a statistically significant association with poor vision-related quality of life.
Vehicle Fuel Consumption Prediction Method Based on Driving Behavior Data Collected from Smartphones
Authors: Yao Ying , Zhao Xiaohua , Liu Chang , Rong Jian , Zhang Yunlong , Dong Zhenning , Su Yuelong
Published: March 2020

Transportation is an important factor that affects energy consumption, and driving behavior is one of the main factors affecting vehicle fuel consumption. The purpose of this paper is to improve fuel consumption monitoring databases based on mobile phone data. Based on the mobile phone terminals and on-board diagnostic system (OBD) installed in taxis, driving behavior data and fuel consumption data are extracted, respectively. By matching the driving behavior data collected by a mobile phone with the fuel consumption data collected by OBD, the correlation between driving behavior and fuel consumption is explored, so that vehicle fuel consumption could be predicted based on mobile phone data. The fuel consumption prediction models are built using back propagation (BP) neural network, support vector regression (SVR), and random forests. The results show that the average speed, average speed except for idle (ASEI), average acceleration, average deceleration, acceleration time percentage, deceleration time percentage, and cruising time percentage are important indicators for fuel consumption evaluation. All three models could predict fuel consumption accurately, with an absolute relative error less than 10%. The random forest model is proved to have the highest accuracy and runs faster, making it suitable for wide application. This method lays a foundation for monitoring database improvement and fine management of urban transportation fuel consumption.
Potential Protective and Therapeutic Roles of the Nrf2 Pathway in Ocular Diseases: An Update
Authors: Wang Ming-xuan , Zhao Jing , Zhang Hong , Li Ke , Niu Ling-zhi , Wang Yuan-ping , Zheng Ya-juan
Published: March 2020

Nuclear factor- (erythroid-derived 2-) like 2 (Nrf2) is a regulator of many processes of life, and it plays an important role in antioxidant, anti-inflammatory, and antifibrotic responses and in cancer. This review is focused on the potential mechanism of Nrf2 in the occurrence and development of ocular diseases. Also, several Nrf2 inducers, including noncoding RNAs and exogenous compounds, which control the expression of Nrf2 through different pathways, are discussed in ocular disease models and ocular cells, protecting them from dysfunctional changes. Therefore, Nrf2 might be a potential target of protecting ocular cells from various stresses and preventing ocular diseases.
Enhanced Immunogenicity of Mitochondrial-Localized Proteins in Cancer Cells
Authors: Prota Gennaro , Gileadi Uzi , Rei Margarida , Lechuga-Vieco Ana Victoria , Chen Ji-Li , Galiani Silvia , Bedard Melissa , Lau Vivian Wing Chong , Fanchi Lorenzo F. , Artibani Mara , Hu Zhiyuan , Gordon Siamon , Rehwinkel Jan , Enríquez Jose A. , Ahmed Ahmed A. , Schumacher Ton N. , Cerundolo Vincenzo
Published: March 2020

Epitopes derived from mutated cancer proteins elicit strong antitumor T-cell responses that correlate with clinical efficacy in a proportion of patients. However, it remains unclear whether the subcellular localization of mutated proteins influences the efficiency of T-cell priming. To address this question, we compared the immunogenicity of NY-ESO-1 and OVA localized either in the cytosol or in mitochondria. We showed that tumors expressing mitochondrial-localized NY-ESO-1 and OVA proteins elicit significantdly higher frequencies of antigen-specific CD8+ T cells in vivo. We also demonstrated that this stronger immune response is dependent on the mitochondrial location of the antigenic proteins, which contributes to their higher steady-state amount, compared with cytosolic localized proteins. Consistent with these findings, we showed that injection of mitochondria purified from B16 melanoma cells can protect mice from a challenge with B16 cells, but not with irrelevant tumors. Finally, we extended these findings to cancer patients by demonstrating the presence of T-cell responses specific for mutated mitochondrial-localized proteins. These findings highlight the utility of prioritizing epitopes derived from mitochondrial-localized mutated proteins as targets for cancer vaccination strategies.
Germline BRCA Mutation Rates in Latina Women Presenting for Gynecologic Oncology Care
Authors: Hong Linda , Gonzalez Rebecca , Unternaehrer Julia , Ioffe Yevgeniya
Published: March 2020

Objective: Germline BRCA mutation rates in the Latina population are yet to be well described. We aimed to quantitate the rates of referral for genetic testing in qualifying women and testing completion rates in a population of women presenting for gynecologic oncology care. Results were then stratified by ethnic/racial background. Methods: Charts of new patients evaluated at a comprehensive cancer center in Southern California were reviewed. Patients qualifying for genetic testing in accordance with NCCN Guidelines version 1.2017 for breast and/or ovarian cancer genetic assessment were identified. The actual rates of prescriptions for genetic testing placed, testing completion rates, test results, as well as patients’ family history were abstracted. Data were analyzed with chi-square tests. Results: Five hundred and seventy-two of 2,053 patients met testing criteria, and 256/572 (45%) were prescribed testing in accordance with the guidelines. By ethnicity, testing was prescribed in 44% of Non-Hispanic White (NHW), 44% of Latina, 46% of African-American, and 60% of Asian (p = 0.6) patients. Testing was completed in 65% of NHW, 66% of Latina, 65% of African-American, and 67% of Asian patients (p = 0.97). Completion rates were low overall: 28% of those who met testing criteria were tested (p = 0.85). Pathogenic BRCA mutations were found in 29% of NHW and 21% of Latina, 45% of African-American, and 20% of Asian patients (p = 0.4). Conclusions: There was no difference by ethnicity in rates of testing prescription, completion, or presence of BRCA mutations. Overall, testing rates were suboptimal. BRCA mutations were found in large percentage of Latinas (21%). Further studies are underway to identify barriers to testing prescriptions and completion for Latina women.
Should COVID-19 Concern Nephrologists? Why and to What Extent? The Emerging Impasse of Angiotensin Blockade
Authors: Perico Luca , Benigni Ariela , Remuzzi Giuseppe
Published: March 2020

Here, we review the most recent findings on the effects of SARS-CoV-2 infection on kidney diseases, including acute kidney injury, and examine the potential effects of ARBs on the outcomes of patients with COVID-19. Lastly, we discuss the clinical management of COVID-19 patients with existing chronic renal disorders, particularly those in dialysis and with kidney transplants.
A Modified Overlapping Partitioning Clustering Algorithm for Categorical Data Clustering
Authors: Alaqtash Mohammad , A.Fadhil Moayad , F. Al-Azzawi Ali
Published: March 2020

Clustering is one of the important approaches for Clustering enables the grouping of unlabeled data by partitioning data into clusters with similar patterns. Over the past decades, many clustering algorithms have been developed for various clustering problems. An overlapping partitioning clustering (OPC) algorithm can only handle numerical data. Hence, novel clustering algorithms have been studied extensively to overcome this issue. By increasing the number of objects belonging to one cluster and distance between cluster centers, the study aimed to cluster the textual data type without losing the main functions. The proposed study herein included over twenty newsgroup dataset, which consisted of approximately 20000 textual documents. By introducing some modifications to the traditional algorithm, an acceptable level of homogeneity and completeness of clusters were generated. Modifications were performed on the pre-processing phase and data representation, along with the number methods which influence the primary function of the algorithm. Subsequently, the results were evaluated and compared with the k-means algorithm of the training and test datasets. The results indicated that the modified algorithm could successfully handle the categorical data and produce satisfactory clusters.
Test First Model for Application in the Academic Setting
Authors: Sham Awang Abu Bakar Normi , Yahya Norzariyah
Published: March 2020

This research elaborates the selection of the Test First and Test Last model for a pilot experiment that was executed as a feasibility study to validate the suitability of the existing Test First model for its implementation in the series of actual experiment. The series of actual experiment is designed to investigate the quality of the project developed by the students in higher educational institution with the Test First over Test Last model. The findings gathered from the pilot experiment demonstrate that there were misunderstandings on the user stories among the participants that have led to the development of an enhanced Test First model.
The Design and Evaluation of DACADE Visual Tool: Theoretical Implications
Authors: Sheikh Abdul Aziz Madihah , Lindgaard Gitte , Syarqawy Hamzah Mohd , Allan Whitfield T. W.
Published: March 2020

A goal of every designer is to create successful products for consumers. In creating a successful product, it is crucial for a designer to understand consumers’ perceptions of a product early in the design process. Nevertheless, design students lack the necessary data collection and user testing skills to support effective design decision-making. Consequently, their products might not be acceptable to the intended consumers and are thus likely to fail in the marketplace. For design students to acquire those skills, design curricula should incorporate statistical courses teaching the concepts of data and user testing. We addressed this challenge by developing an automated visual tool named DACADE, assisting design students to systematically collect and analyze data. This paper reports the theoretical implications discovered during the process from designing through to implementing and evaluating DACADE concerning the transfer of learning, the appropriateness of graphics used in a software tool, and user motivation in a learning environment.
On Randomness of Compressed Data Using Non-parametric Randomness Tests
Authors: A. Al-Khayyat Kamal , F. Al-Shaikhli Imad , Vijayakuumar V.
Published: March 2020

Four randomness tests were used to test the outputs (compressed files) of four lossless compressions algorithms: JPEG-LS and JPEG-2000 algorithms are image-dedicated algorithms, while 7z and Bzip2 algorithms are general-purpose algorithms. The relationship between the result of randomness tests and the compression ratio was investigated. This paper reports the important relationship between the statistical information behind these tests and the compression ratio. It shows that, this statistical information almost the same at least, for the four lossless algorithms under test. This information shows that 50 % of the compressed data are grouping of runs, 50% of it has positive signs when comparing adjacent values, 66% of the files containing turning points, and using Cox-Stuart test, 25% of the file give positive signs, which reflects the similarity aspects of compressed data. When it comes to the relationship between the compression ratio and these statistical information, the paper shows also, that, the greater values of these statistical numbers, the greater compression ratio we get.
PAPR Reduction Using Huffman and Arithmetic Coding Techniques in F-OFDM System
Authors: Idris Azlina , Atiqah Md Deros Nur , Taib Idris , Kassim Murizah , Danial Rozaini Mohd , Mohd Ali Darmawaty
Published: March 2020

Filtered orthogonal frequency division multiplexing (F-OFDM) was introduced to overcome the high side lobes in the OFDM system. Filtering is implemented in the system to reduce the out-of-band emission (OOBE) for the spectrum utilization and to meet the diversified expectation of the upcoming 5G networks. The main drawback in the system is the high peak to average ratio (PAPR). This paper investigates the method used in reducing the PAPR in the F-OFDM system. The proposed method using the block coding technique to overcome the problem of high PAPR are the Arithmetic coding and Huffman coding. This research evaluates the performance of F-OFDM system based on the PAPR values. From the simulation results, the PAPR reduction of the Arithmetic coding is 8.9% lower, while the Huffman Coding is 6.7% lower in the F-OFDM system. The results prove that the Arithmetic Coding will out-perform the Huffman coding in the F-OFDM system.
An Identification of Multiple Harmonic Sources in a Distribution System by Using Spectrogram
Authors: H. Jopri M. , R. Abdullah A. , Manap M. , Sutikno T. , Ab Ghani M. R.
Published: March 2020

The identification of multiple harmonic sources (MHS) is vital to identify the root causes and the mitigation technique for a harmonic disturbance. This paper introduces an identification technique of MHS in a power distribution system by using a time-frequency distribution (TFD) analysis known as a spectrogram. The spectrogram has advantages in term of its accuracy, a less complex algorithm, and use of low memory size compared to previous methods such as probabilistic and harmonic power flow direction. The identification of MHS is based on the significant relationship of spectral impedances, which are the fundamental impedance (Z1) and harmonic impedance (Zh) that estimate the time-frequency representation (TFR). To verify the performance of the proposed method, an IEEE test feeder with several different harmonic producing loads is simulated. It is shown that the suggested method is excellent with 100% correct identification of MHS. The method is accurate, fast and cost-efficient in the identification of MHS in power distribution arrangement.
Performance Comparison of Artificial Intelligence Techniques for Non-intrusive Electrical Load Monitoring
Authors: Khalid Khairuddin , Mohamed Azah , Mohamed Ramizi , Shareef Hussain
Published: March 2020

The increased awareness in reducing energy consumption and encouraging response from the use of smart meters have triggered the idea of non-intrusive load monitoring (NILM). The purpose of NILM is to obtain useful information about the usage of electrical appliances usually measured at the main entrance of electricity to obtain aggregate power signal by using a smart meter. The load operating states based on the on/off loads can be detected by analysing the aggregate power signals. This paper presents a comparative study for evaluating the performance of artificial intelligence techniques in classifying the type and operating states of three load types that are usually available in commercial buildings, such as fluorescent light, air-conditioner and personal computer. In this NILM study, experiments were carried out to collect information of the load usage pattern by using a commercial smart meter. From the power parameters captured by the smart meter, effective signal analysis has been done using the time time (TT)-transform to achieve accurate load disaggregation. Load feature selection is also considered by using three power parameters which are real power, reactive power and the TT-transform parameters. These three parameters are used as inputs for training the artificial intelligence techniques in classifying the type and operating states of the loads. The load classification results showed that the proposed extreme learning machine (ELM) technique has successfully achieved high accuracy and fast learning compared with artificial neural network and support vector machine. Based on validation results, ELM achieved the highest load classification with 100% accuracy for data sampled at 1 minute time interval.
Robot Motion Control Using the Emotiv EPOC EEG System
Authors: Dewangga Sandy Akbar , Tjandrasa Handayani , Herumurti Darlis
Published: March 2020

Brain-computer interfaces have been explored for years with the intent of using human thoughts to control mechanical system. By capturing the transmission of signals directly from the human brain or electroencephalogram (EEG), human thoughts can be made as motion commands to the robot. This paper presents a prototype for an electroencephalogram (EEG) based brain-actuated robot control system using mental commands. In this study, Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) method were combined to establish the best model. Dataset containing features of EEG signals were obtained from the subject non-invasively using Emotiv EPOC headset. The best model was then used by Brain-Computer Interface (BCI) to classify the EEG signals into robot motion commands to control the robot directly. The result of the classification gave the average accuracy of 69.06%.
The Effects of Nitrogen and Oxygen Atmosphere on the Photoconductivity of Trimethyl Phenyl Diamine Thin Films
Authors: Nayan Nazrul Anuar , Anuar A. Rahman Khairul
Published: March 2020

Organic materials were previously used as insulators in electrical technology. These materials, however, are currently used as conductors once their photoconductivity is confirmed and studied. From the literature, it has shown that the photoconductivity of trimethyl phenyl diamine (TPD) increases in the air and decreased in the atmosphere of the vacuum. To the best of our knowledge, there is no detailed study of the effects of gas in the air that affect TPD photoconductivity. In this study we investigate the effects of nitrogen (N2) and oxygen (O2) gases on photoconductivity, degradation and residual decay of photoconductivity for thin film TPD. The results of the study show that in the atmosphere of O2, TPD produces about seven times higher photoconductivity compared to N2 conditions. It also shows that, N2 and O2 provide more effective response time during photoconductivity residual decay. Photoconductivity degradation occurs in all conditions and its recovery takes more than 65 hours.
Creating Color Image Features Using Local Contrast Method
Authors: Al-Rawashdeh Ayman , Al-Qadi Ziad
Published: March 2020

Digital color images are now one of the most popular data types used in the digital processing environment. Color image recognition plays an important role in many vital applications, which makes the enhancement of image recognition or retrieval system an important issue. Using color image pixels to recognize or retrieve the image, but the issue of the huge color image size that requires accordingly more time and memory space to perform color image recognition and/or retrieval. In the current study, image local contrast was used to create local contrast victor, which was then used as a key to recognize or retrieve the image. The proposed local contrast method was properly implemented and tested. The obtained results proved its efficiency as compared with other methods.
Development of Respiratory Rate Estimation Technique Using Electrocardiogram and Photoplethysmogram for Continuous Health Monitoring
Authors: Nayan Nazrul Anuar , Jaafar Rosmina , Sabrina Risman Nur
Published: March 2020

Abnormal vital signs often predict a serious condition of acutely ill hospital patients in 24 hours. The notable fluctuations of respiratory rate (RR) are highly predictive of deteriorations among the vital signs measured. Traditional methods of detecting RR are performed by directly measuring the air flow in or out of the lungs or indirectly measuring the changes of the chest volume. These methods require the use of cumbersome devices, which may interfere with natural breathing, are uncomfortable, have frequently moving artifacts, and are extremely expensive. This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules. Algorithms have been validated by using PhysioNet’s Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II)’s patient datasets. RR estimation provides the value of mean absolute error (MAE) for ECG as 1.25 bpm (MIMIC-II) and 1.05 bpm for the acquired data. MAE for PPG is 1.15 bpm (MIMIC-II) and 0.90 bpm for the acquired data. By using 1-minute windows, this method reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals. Smaller MAE for PPG signals results from fewer artifacts due to easy sensor attachment for the PPG because PPG recording requires only one-finger pulse oximeter sensor placement. However, ECG recording requires at least three electrode placements at three positions on the subject’s body surface for a single lead (lead II), thereby increasing the artifacts. A reliable technique has been proposed for RR estimation.
Sabah Traditional Chinese Medicine Database
Authors: Baharum Aslina , Yee Jin Neoh , Hayati A. Wahab Shaliza , Helmy Abd Wahab Mohd , Ambar Radzi , Hidayah Mat Zain Nurul
Published: March 2020

As technology grows, people tend to use or apply anything digitalized instead of printed, especially for references. This is because the printed form references are not easy to find. Even if the references are found successfully, it has already cost a lot of time, money, energy, etc. At the same time, people also put more emphasize on health issues. They are beginning to be more alert in fields that they have ignored before, such as traditional medicine and Chinese medicine. Based on these two points, it can be said that the effort of transforming Traditional Chinese Medicine (TCM) from printed based reference into online reference as a database is a public beneficial effort. There are a lot of online TCM database outside of Malaysia, especially from the People’s Republic of China, Hong Kong, and Taiwan. Those herbal remedies from overseas are somewhat different from the herbal remedies in Malaysia due to the habits and occurrences of the herbs. Through this project, it is hoped that this database will help the local people to discover and identify the herbs that they could find in the surrounding area. The objectives of this project are to identify the validity of the information of the Sabah TCM using mixed method, to develop the Sabah TCM database, and finally to evaluate the usability of the database designed using meCUE. The methodology used was 4D Appreciative Inquiry Model, which included discovery, dream, design, and destiny phases. The advantage of this model was to take a positive core to make any changes instead of finding the weaknesses of the project. Hopefully through the developed database, local Sabahan can take the advantage in identifying the proper usage of existing herbs in their surroundings.
SGSC Framework: Smart Government in Supply Chain Based on FODA
Authors: Fajar Ahmad Nurul , Nugeraha Utama Ditdit
Published: March 2020

Smart System has implemented in government sector. There are varies Implementation that was utilized by research activities for numerous domains is very broad. Besides that, the Industry, transportation and health, also where such a system is incredibly beneficial. This study discuss supply chain and governmental link issue, coordination of all stakeholder in supply chain has to reflect the government role. It support with the condition in Indonesian government environment is unique. It is a challenge to construct smart system based on Feature Oriented Domain Analysis (FODA) approach. It can produce software product line (SPL). We proposed framework for develop software product line for smart supply chain in government sector. It is used to enhance and improve the development of software systems by multiple software system developers. It will be a guidance for construct smart government, and more specificity in supply chain for government system area environment. It is called SGSC Framework. It consists of four layers, such as optimization layer, integration layer, supply chain layer and data layer.
E-Learning Effectiveness Analysis in Developing Countries: East Nusa Tenggara, Indonesia Perspective
Authors: Sfenrianto Sfenrianto , Tantrisna Ellen , Akbar Habibullah , Wahyudi Mochamad
Published: March 2020

The adoption of e-learning in developing countries like Indonesian Universities have been focused in urban areas like the big cities, especially in Java island. There is a lack of development of e-learning in a remote city like Kupang East Nusa Tenggara Indonesia which is located far away from the capital city. This research aims to assess the effectiveness of e-learning by analyzing three factors in one of the higher institution in Kupang city, i.e. Sekolah Tinggi Kesehatan Citra Mandiri Husada Kupang (STIKes CHMK). The factors include culture, technology and infrastructure, and content satisfaction. The data were collected using questionnaires. Research shows that with proper preparation for e-learning, the acceptance of e-learning in rural areas is significantly high. This finding suggests that e-learning can greatly benefit the students like Kupang city in developing countries.
A low quiescent current low dropout voltage regulator with self-compensation
Authors: Lee Chu-Liang , Sidek Roslina Mohd , Sulaiman Nasri , Rokhani Fakhrul Zaman
Published: March 2020

This paper proposed a low quiescent current low-dropout voltage regulator (LDO) with self-compensation loop stability. This LDO is designed for Silicon-on-Chip (SoC) application without off-chip compensation capacitor. Worst case loop stability phenomenon happen when LDO output load current (Iload) is zero. The second pole frequency decreased tremendously towards unity-gain frequency (UGF) and compromise loop stability. To prevent this, additional current is needed to keep the output in low impedance in order to maintain second pole frequency. As Iload slowly increases, the unneeded additional current can be further reduced. This paper presents a circuit which performed self-reduction on this current by sensing the Iload. On top of that, a self-compensation circuit technique is proposed where loop stability is selfattained when Iload reduced below 100μA. In this technique, unity-gain frequency (UGF) will be decreaed and move away from second pole in order to attain loop stability. The decreased of UGF is done by reducing the total gain while maintaining the dominant pole frequency. This technique has also further reduced the total quiescent current and improved the LDO’s efficiency. The proposed LDO exhibits low quiescent current 9.4μA and 17.7μA, at Iload zero and full load 100mA respectively. The supply voltage for this LDO is 1.2V with 200mV drop-out voltage. The design is validated using 0.13μm CMOS process technology.
IoT-based electricity energy monitoring system at Universiti Teknikal Malaysia Melaka
Authors: Shamshiri Meysam , Gan Chin Kim , Baharin Kyairul Azmi , Arif Mohd Azman Mohd
Published: March 2020

Electricity bill is one of the major operating expenses in most of the commercial buildings and industrial plants. Thus, the buildings’ energy management system is an essential element that should be utilized to optimize the energy usage and hence, contributes to carbon footprint reduction. To achieve this, one needs to first understand how the energy is being used in the buildings before any saving measures can be identified and proposed. Therefore, this paper presents the development of an Internet of Things (IoT) enabled device that can communicate with different digital energy meters through modbus protocol. The prototype has been successfully installed in three locations in the main campus of Universiti Teknikal Malaysia Melaka (UTeM). The proposed solution enables the campus-wide energy usage to be monitored and stored efficiently and economically as opposed to the capital-intensive SCADA system.
Task mapping and routing optimization for hard real-time Networks-on-Chip
Authors: Norazizi Sham Mohd Sayuti M. , Hazwani Mohd Ridzuan Farida , Hilmi Abdullah Zul
Published: March 2020

Interference from high priority tasks and messages in a hard real-time Networks-on-Chip (NoC) create computation and communication delays. As the delays increase in number, maintaining the system’s schedulability become difficult. In order to overcome the problem, one way is to reduce interference in the NoC by changing task mapping and network routing. Some population-based heuristics evaluate the worst-case response times of tasks and messages based on the schedulability analysis, but requires a significant amount of optimization time to complete due to the complexity of the evaluation function. In this paper, we propose an optimization technique that explore both parameters simultaneously with the aim to meet the schedulability of the system, hence reducing the optimization time. One of the advantages from our approach is the unrepeated call to the evaluation function, which is unaddressed in the heuristics that configure design parameters in stages. The results show that a schedulable configuration can be found from the large design space.
Investigation of output power in ring CW fiber laser using graphene saturable absorber
Authors: Ahmed Hamida Belal , Eltaif Tawfig , Daniel Bin Mohd Noh Farhan , Khan Sheroz
Published: March 2020

This paper reported the effect of different coupling ratio in continuous wave fiber laser in a ring cavity configuration. Different coupling ratios of 10/90 and 50/50 were tested. Where the output power may vary depending on the ratio and it can be applied to specific area that requires either high or low output power. In addition, generation of passive Q-switched erbium doped fiber laser (EDFL) using graphene based saturable absorber in ring cavity using different coupling ratio was experimentally investigated. As a result, wavelength centered at 1566.62nm is obtain from EDFL cavity. Moreover, the cavity using coupler of 50/50 is capable to achieve Q-switched pulses as compared to the cavity using coupler of 10/90. Where the maximum output power recorded is 336mW with pulse repetition rate of 23.74 kHz. In addition, the pulse width is 3.84µs, and pulse energy is 14.15nJ.
Video streaming over Ad hoc on-demand distance vector routing protocol
Authors: O. Khalifa Othman , Eldin Mustafa Ahmed Diaa , Hassan Abdalla Hashim Aisha , Yagoub Mudathir
Published: March 2020

Video streaming is content sent in compressed form over the netwoks and viwed the users progressively. The transmission of video with the end goal that it can be prepared as consistent and nonstop stream. The point is that to give client support to client at anyplace and at whatever time. Mobile Ad hoc Networks (MANETs) are considered an attractive nertwork for information transmission in many applications where the customer programme can begin showing the information before the whole record has been transmitted. Ad hoc On-demand Distance Vector (AODV) protocol is considered as one of the most important routing protocols in MANET. However, routing protocols assume a crucial part in transmission of information over the network. This paper investigates the performance of AODV Routing Protocol under video traffic over PHY IEEE 802.11g. The protocol model was developed in OPNET. Different outcomes from simulation based models are analyzed and appropriate reasons are also discussed. A different scenarios of video streaming were used. The metric in terms of throughput, end to end delay, packet delivery ratio and routing overhead were measured. A comparision with GRP and GRP are also reported.