bluuebunny/crossref_metadata_2025 huggingface dataset:
Seizures in Premature Infants Born at Less than 28 Weeks’ Gestation
Authors: Meledin Irina , Tzur-Sebton Hilla , Noyman Iris , Friger Michael , Hazan Guy , Shany Eilon
Published: January 2019

Background: The incidence of seizures in the neonatal period is thought to be high due to a lower seizure threshold of the immature brain. Data on seizures in extremely premature infants are scarce. Objectives: The aim of this study was to determine whether seizures are an independent risk factor for in-hospital death and to determine the incidence of seizures in extremely premature infants. Methods: This was a retrospective cohort study. Included were infants born under 28 weeks’ gestation and monitored with amplitude-integrated electroencephalography (aEEG) over the first 3 days of life. The number and duration of seizures was retrieved from aEEG recordings together with clinical data. The association of seizures and other parameters with mortality was assessed using univariable analyses methods. Relevant parameters were used for a multivariable Cox regression analysis. Results: Overall, 229 infants were included in the study. Forty-six infants had at least one seizure episode yielding an incidence of 20%. In univariable analyses, gestational age (p < 0.001), birthweight Z-score (p < 0.001), seizures (p = 0.025), suppressed background aEEG (p < 0.001), and severe intraventricular hemorrhage (IVH; p < 0.001) were associated with death before discharge. In multivariable analysis, gestational age (HR = 0.61, p < 0.001), background aEEG activity (HR = 0.30, p < 0.001), birth weight Z-score (HR = 0.51, p = 0.04), and severe IVH (HR = 2.60, p < 0.001) were found to be significant predictors of mortality while the presence of seizures in the first 3 days of life trended to significantly predict an increased risk of mortality (HR = 1.53, p = 0.09). Conclusions: Although seizure incidence was relatively high in this cohort of extremely preterm infants and infants with seizures were more likely to die, seizures alone are not a predictor for early death. However, they may be an important indicator of pathologies that are not immediately diagnosed yet could eventually lead to death among this vulnerable population.
Increase Risk of Multiple Sclerosis in Patients with Psoriasis Disease: An Evidence of Observational Studies
Authors: Islam Md. Mohaimenul , Poly Tahmina Nasrin , Yang Hsuan-Chia , Wu Chieh-Chen , Li Yu-Chuan
Published: January 2019

Background: Psoriasis, a common chronic inflammatory disease, increases the risk of developing multiple sclerosis (MS), but evidence for this outcome is still unclear. However, we performed a meta-analysis of relevant studies to quantify the magnitude of the association between psoriasis and MS. It will help to assess the current state of knowledge, fill the gaps in our existing concern, and make a recommendation for future research. Methods: PubMed, EMBASE, and the bibliographies of articles were searched for studies published between January 1, 1990, and November 1, 2017, which reported on the association between psoriasis and MS. Articles were included if they (1) were published in English, (2) reported patients with psoriasis, and the outcome of interest was MS, (3) provided OR/RR/HR with 95% CI or sufficient information to calculate the 95% CI, and (4) if ≥50 patients. All abstracts, full-text articles, and sources were reviewed, with duplicate data excluded. Summary relative risk (ORs) with 95% CI was pooled using a random-effects model. Subgroup and sensitivity analyses were also conducted. Results: We selected 11 articles out of 785 unique abstracts for full-text review using our predetermined selection criteria, and 9 out of these 11 studies met all of our inclusion criteria. The overall pooled increased of developing MS in patients with psoriasis was RR 1.607 (95% CI 1.322–1.953, p < 0.0001) with low heterogeneity (I2 = 37.41%, Q = 12.782, τ2 = 0.027) for the random effect model. In the subgroup analysis, the MS risk in the patient with psoriasis was also significantly higher in the 6 studies from Europe RR 1.57 (95% CI 1.26–1.94, p < 0.001) with moderate heterogeneity (I2 = 50.66%, Q = 10.13, τ2 = 0.03) for the random effect model. Conclusion: Our results showed that psoriasis is significantly associated with an increased risk of developing MS. Physicians should carefully be observed symptoms and empower their patients to improve existing knowledge and quality of life. Further studies are warranted to establish the mechanisms underlying this relationship.
A Novel Study on Bipolar High Voltage Direct Current Transmission Lines Protection Schemes
Authors: Agarwal Shobha , Panigrahi C. K. , Sahoo Aishwarya , Mishra Sanitha
Published: January 2019

In long dc transmission lines identification of fault is important for transferring a large amount of power. In bipolar Line commutated converter transmission lines are subjected to harsh weather condition so accurate and rapid clearance of fault is essential. A comparative study of the bipolar system with both converters healthy and one converter tripped is studied. Most of the research paper has focussed on transmission line faults in bipolar mode but none of them had focussed when HVDC system works in monopolar mode after the fault. In the proposed scheme the voltage signals are extracted from both poles of the rectifier ends and are processed to identify the faults in transmission lines.The Artificial neural network is utilised in detecting the fault in both bipolar and monopolar system. Since it can identify the relationship between input and output data to detect the fault pattern it can be utilised under all conditions. Moreover, benefits of the proposed method are its accuracy, no requirement of the communication system as it acquires data from one end and has a reach setting of 99%.
Nanometric Modelization of Gas Structure, Multidimensional using COMSOL Software
Authors: Bouneb I. , Kerrour F.
Published: January 2019

In structures with GaAs, which are the structures most used, because of their physical and electronic proprieties, nevertheless seems a compromise between the increase of doping and reduced mobility. The use of quantum hetero structures can overcome this limitation by creating a 2D carrier gas. Using the COMSOL software this work present three models: the first model computes the electronic states for the heterojunction AlGaAs/GaAs in 1D dimension, the second model computes the electronic states for the heterojunction AlGaAs/GaAs but in 2D dimension (nanowire) and the third model we permitted the study of this hetero junction (steep) wich inevitably involves the resolution of the system of equations Schrödinger-Poisson due to quantum effects that occur at the interface. The validity of this model can be effectuated with a comparison of our results with the result of different models developed in the literature of the related work, from this point of view the validity of our model is confirmed.
Low Noise Amplifier using Darlington Pair At 90nm Technology
Authors: Singh Rashmi , Mehra Rajesh
Published: January 2019

The demand of low noise amplifier (LNA) has been rising in today’s communication system. LNA is the basic building circuit of the receiver section satellite. The design concept demonstrates the design trade off with NF, gain, power consumption. This paper reports on with analysis of wideband LNA. This paper shows the schematic of LNA by using Darlington pair amplifier. This LNA has been fabricated on 90nm CMOS process. This paper is focused on to make comparison of three stage and single stage LNA. Here, the phase mismatch between these patameters is quantitavely analyzed to study the effect on gain and noise figure (NF). In this paper, single stage LNA has shown the 23 dB measured gain, while the three stages LNA has demonstrated 29 dB measured gain. Here, LNA designed using darlington pair shows low NF of 3.3-4.8 dB, which comparable to other reported single stage LNA designs and appreciably low compared to the three stages LNA. Hence, findings from this paper suggest the use of single stage LNA designed using Darlington pair in transceiver satellite applications.
Image Analysis of Periapical Radiograph for Bone Mineral Density Prediction
Authors: Widyaningrum Rini , Lestari Sri , Jie Ferry
Published: January 2019

Osteoporosis is a systemic skeletal disease. Parameter from any bone site in the body has possibility to be developed as a predictor of osteoporosis. The alteration in the mandible trabecular bone is visible in periapical radiographs. The aim of this study was to correlate the area parameter and the integrated density of periapical radiograph with bone mineral density. Image analysis of periapical radiograph i.e. measurement of area parameter and integrated density was done on Region of Interest (ROI) by using canny edge detection method. Result of this study showed that the area parameter has asignificant (α<0.05) negative correlation with the bone mass density (BMD) of the lumbar spine (r = -0.371) and T-score of the lumbar spine (r = -0.383). The linear regression test showed that the area parameter only can be used to predict T-score of the lumbar spine (F=5.822, α<0.05). The integrated density showed a significant (α < 0.05) negative correlation with T-score of hip (r = -0.332) and T-score of lumbar spine (r = -0.377). It can be concluded that the area parameter can be used as one of input parameters for computer-aided system of osteoporosis early detection by using periapical radiograph.
Evaluation of the Medical Image Compression using Wavelet Packet Transform and SPIHT Coding
Authors: Benyahia Ismahane , Beladgham Mohammed , Bassou Abdesselam
Published: January 2019

Wavelet transforms and wavelet packets are widely imposed in the analysis and resolution of problems related to science and technical engineering. Decomposition wavelet packet allows several frequency bands according to various levels of resolutions. We apply this transform (PWT) coupled with the SPIHT coder to reduce the limitations of conventional wavelet filter bank. The results obtained using the applied algorithm, are very satisfactory and encouraging compared to many of the best coders cited in the literature and show a visual and numerical superiority over conventional methods. These the promising results are confirmed by visual evaluation parameters (PSNR, MSSIM and VIF).
A New Hybrid Robust Fault Detection of Switching Systems by Combination of Observer and Bond Graph Method
Authors: Ghasem Kazemi Mohammad , Montazeri Mohsen
Published: January 2019

In this paper, the problem of robust Fault Detection (FD) for continuous time switched system is tackled using a hybrid approach by combination of a switching observer and Bond Graph (BG) method. The main criteria of an FD system including the fault sensitivity and disturbance attenuation level in the presence of parametric uncertainties are considered in the proposed FD system. In the first stage, an optimal switching observer based on state space representation of the BG model is designed in which simultaneous fault sensitivity and disturbance attenuation level are satisfied using H􀀀=H1 index. In the second stage, the Global Analytical Redundancy Relations (GARRs) of the switching system are derived based on the output estimation error of the observer, which is called Error-based Global Analytical Redundancy Relations (EGARRs). The parametric uncertainties are included in the EGARRs, which define the adaptive thresholds on the residuals. A constant term due to the effect of disturbance is also considered in the thresholds. In fact, a two-stage FD system is proposed wherein some criteria may be considered in each stage. The efficiency of the proposed method is shown for a two-tank system.
Controlling a DC Motor through Lypaunov-like Functions and SAB Technique
Authors: Rincón Alejandro , Angulo Fabiola , Hoyos Fredy
Published: January 2019

In this paper, state adaptive backstepping and Lyapunov-like function methods are used to design a robust adaptive controller for a DC motor. The output to be controlled is the motor speed. It is assumed that the load torque and inertia moment exhibit unknown but bounded time-varying behavior, and that the measurement of the motor speed and motor current are corrupted by noise. The controller is implemented in a Rapid Control Prototyping system based on Digital Signal Processing for dSPACE platform and experimental results agree with theory.
Fairness Comparison of TCP Variants over Proactive and Reactive Routing Protocol in MANET
Authors: Nigar Nahida , Anwarul Azim Muhammad
Published: January 2019

Mobile ad hoc networks (MANETs) are applicable in an infrastructureless environment where the mobile devices act as routers and intermediate nodes are used to transfer segments to their final destination. As Transmission control protocol (TCP) was originated for Internet with fundamentally different properties, faces serious challenges when used in mobile ad hoc networks. TCP functionality degrades, due to special properties of MANET such as route failure because of significant change of network topology and link errors. TCP uses Congestion Control Algorithms; TCP Vegas is one of them which claim to have better throughput comparing with other TCP variants in a wired network. Fairness issues of TCP Variants in MANET including existing routing protocol are still unsolved. To determine the best TCP Variants in MANET environment over renowned routing protocol is the main objective of this paper. A Study on the throughput fairness of TCP Variants namely, Vegas, Reno, New Reno, SACK, FACK, and Cubic are performed via simulation experiment using network simulator (ns-2) over existing routing protocol, named, AODV, AOMDV, DSDV, and DSR. This fairness evaluation of TCP flows arranged a contrast medium for the TCP Variants using stated routing protocol in MANET. However, TCP Vegas obtain unfair throughput in MANET. The simulation results show that TCP Reno outperforms other TCP variants under DSDV routing protocol.
Joint Routing and Congestion Control in Multipath Channel based on Signal to Noise Ratio with Cross Layer Scheme
Authors: Istikmal Istikmal , Kurniawan Adit , Hendrawan Hendrawan
Published: January 2019

Routing protocol and congestion control in Transmission Control Protocol (TCP) have important roles in wireless mobile network performance. In wireless communication, the stability of the path and successful data transmission will be influenced by the channel condition. This channel condition constraints come from path loss and the multipath channel fading. With these constraints, the algorithm in the routing protocol and congestion control is confronted with the uncertainty of connection quality and probability of successful packet transmission, respectively. It is important to investigate the reliability and robustness of routing protocol and congestion control algorithms in dealing with such situation.  In this paper, we develop a detailed approach and analytical throughput performance with a cross layer scheme (CLS) between routing and congestion control mechanism based on signal to noise ratio (SNR) in Rician and Rayleigh as multipath fading channel. We proposed joint routing and congestion control TCP with a cross layer scheme model based on SNR (RTCP-SNR). We compare the performance of RTCP-SNR with conventional routing-TCP and routing-TCP that used CLS with routing aware (RTCP-RA) model. The analyses and the simulation results showed that RTCP-SNR in a multipath channel outperforms conventional routing-TCP and RTCP-RA.
Evaluation of a Multiple Regression Model for Noisy and Missing Data
Authors: Jittawiriyanukoon Chanintorn
Published: January 2019

The standard data collection problems may involve noiseless data while on the other hand large organizations commonly experience noisy and missing data, probably concerning data collected from individuals. As noisy and missing data will be significantly worrisome for occasions of the vast data collection then the investigation of different filtering techniques for big data environment would be remarkable. A multiple regression model where big data is employed for experimenting will be presented. Approximation for datasets with noisy and missing data is also proposed. The statistical root mean squared error (RMSE) associated with correlation coefficient (COEF) will be analyzed to prove the accuracy of estimators. Finally, results predicted by massive online analysis (MOA) will be compared to those real data collected from the following different time. These theoretical predictions with noisy and missing data estimation by simulation, revealing consistency with the real data are illustrated. Deletion mechanism (DEL) outperforms with the lowest average percentage of error.
A Comprehensive Survey on Exiting Solution Approaches towards Security and Privacy Requirements of IoT
Authors: Chetan Rajani , Shahabadkar Ramesh
Published: January 2019

‘Internet of Things (IoT)’emerged as an intelligent collaborative computation and communication between a set of objects capable of providing on-demand services to other objects anytime anywhere. A large-scale deployment of data-driven cloud applications as well as automated physical things such as embed electronics, software, sensors and network connectivity enables a joint ubiquitous and pervasive internet-based computing systems well capable of interacting with each other in an IoT. IoT, a well-known term and a growing trend in IT arena certainly bring a highly connected global network structure providing a lot of beneficial aspects to a user regarding business productivity, lifestyle improvement, government efficiency, etc. It also generates enormous heterogeneous and homogeneous data needed to be analyzed properly to get insight into valuable information. However, adoption of this new reality (i.e., IoT) by integrating it with the internet invites a certain challenges from security and privacy perspective. At present, a much effort has been put towards strengthening the security system in IoT still not yet found optimal solutions towards current security flaws. Therefore, the prime aim of this study is to investigate the qualitative aspects of the conventional security solution approaches in IoT. It also extracts some open research problems that could affect the future research track of IoT arena.
Feature Selection Approach based on Firefly Algorithm and Chi-square
Authors: Mashhour Emad Mohamed , El Houby Enas M. F. , Wassif Khaled Tawfik , Salah Akram I.
Published: January 2019

Dimensionality problem is a well-known challenging issue for most classifiers in which datasets have unbalanced number of samples and features. Features may contain unreliable data which may lead the classification process to produce undesirable results. Feature selection approach is considered a solution for this kind of problems. In this paperan enhanced firefly algorithm is proposed to serve as a feature selection solution for reducing dimensionality and picking the most informative features to be used in classification. The main purpose of the proposedmodel is to improve the classification accuracy through using the selected features produced from the model, thus classification errors will decrease. Modeling firefly in this research appears through simulating firefly position by cell chi-square value which is changed after every move, and simulating firefly intensity by calculating a set of different fitness functionsas a weight for each feature. K-nearest neighbor and Discriminant analysis are used as classifiers to test the proposed firefly algorithm in selecting features. Experimental results showed that the proposed enhanced algorithmbased on firefly algorithm with chi-square and different fitness functions can provide better results than others. Results showed that reduction of dataset is useful for gaining higher accuracy in classification.
Services Modeling based on SOA and BPM for Information System Flexibility Improvement
Authors: Fajar Ahmad Nurul , Legowo Nilo
Published: January 2019

The lack of  identify services mechanism which is related to the development of information systems could be impact in wasting time, over budget and can not adapt to the changing environment. This phenomenon is happened by the belief that lack of capturing user requirement. This is due to consider the business environment is always running normally. In fact, the development of the system needs a way to anticipate the business environment that unpredictable changes.Therefore, the phenomenon on the need for modeling services can able to respond to the changing needs of users still have a chancein this study. It explores modeling services to synergize SOA and BPM.Several previous studies generally use a business driven approach, technical partially driven to develop the service modeling. This leads to the question of how a service should be modeled so that it can be applied in different contexts and business processes also. It is support user needs in diversity and heterogeneous system environments. This Conditions occurs in corporate university. The case studies in this research is a Learning Management System (LMS) in Academic Enterprise System (EAS). The research stages are: (1) Analysis of Synergy in SOA and BPM, (2) Analysis of User Experience in LMS Academic Enterprise System (L-EAS),
 (3) Analysis of Modeling Framework, (4) Proposed Framework that aligning SOA and BPM. The result of this study is proposed system framework based on services to increase the flexibility of information systems at LMS Academic Enterprise System (L-EAS).
Coal-Fired Boiler Fault Prediction using Artificial Neural Networks
Authors: Mohd Nistah Nong Nurnie , Lim King Hann , Gopal Lenin , Ismail Alnaimi Firas Basim
Published: January 2019

Boiler fault is a critical issue in a coal-fired power plant due to its high temperature and high pressure characteristics. The complexity of boiler design increases the difficulty of fault investigation in a quick moment to avoid long duration shut-down. In this paper, a boiler fault prediction model is proposed using artificial neural network. The key influential parameters analysis is carried out to identify its correlation with the performance of the boiler. The prediction model is developed to achieve the least misclassification rate and mean squared error. Artificial neural network is trained using a set of boiler operational parameters. Subsequenlty, the trained model is used to validate its prediction accuracy against actual fault value from a collected real plant data. With reference to the study and test results, two set of initial weights have been tested to verify the repeatability of the correct prediction. The results show that the artificial neural network implemented is able to provide an average of above 92% prediction rate of accuracy.
K-NN Classification of Brain Dominance
Authors: Abu Nawas Khairul Amrizal , Mustafa Mahfuzah , Samad Rosdiyana , Pebrianti Dwi , Hasma Abdullah Nor Rul
Published: January 2019

The brain dominance is referred to right brain and left brain. The brain dominance can be observed with an Electroencephalogram (EEG) signal to identify different types of electrical pattern in the brain and will form the foundation of one’s personality. The objective of this project is to analyze brain dominance by using Wavelet analysis. The Wavelet analysis is done in 2-D Gabor Wavelet and the result of 2-D Gabor Wavelet is validated with an establish brain dominance questionnaire. Twenty-one samples from University Malaysia Pahang (UMP) student are required to answer the establish brain dominance questionnaire has been collected in this experiment. Then, brainwave signal will record using Emotiv device. The threshold value is used to remove the artifact and noise from data collected to acquire a smoother signal. Next, the Band-pass filter is applied to the signal to extract the sub-band frequency components from Delta, Theta, Alpha, and Beta. After that, it will extract the energy of the signal from image feature extraction process. Next the features were classified by using K-Nearest Neighbor (K-NN) in two ratios which 70:30 and 80:20 that are training set and testing set (training: testing). The ratio of 70:30 gave the highest percentage of 83% accuracy while a ratio of 80:20 gave 100% accuracy. The result shows that 2-D Gabor Wavelet was able to classify brain dominance with accuracy 83% to 100%.
Dielectric Resonator Reflectarray Antenna Unit Cells for 5G Applications
Authors: Sallehuddin Nur Fazreen , Jamaluddin Mohd Haizal , Kamarudin Muhammad Ramlee , Dahri Muhammad Hashim , Tajol Anuar Siti Umairah
Published: January 2019

This paper presents an investigation for the performance comparison of three different unit cell configurations operating at 26 GHz for 5G applications. The unit cells are cross shape dielectric resonator, cross microstrip patch and cross hybrid dielectric resonator. Verification of the comparison has been done by simulations using commercial Computer Simulation Technology Microwave Studio (CST MWS). The simulated results for reflection phase, slope variation, reflection loss and 10% bandwidth were analyzed and compared. The results indicate that the optimum configuration to be deployed for the reflectarray’s unit element in order to fulfill the 5G requirements of a wide bandwidth is the cross hybrid DRA. This configuration is a combination of cross DRA with cross microstrip patch as the parasitic element in order to tune the phase and provide a wide phase range with smooth variation slope. Cross hybrid DRA provided a wide phase range of 520° with 0.77 dB loss and 10% bandwidth of 160 MHz.
Scattering Regimes for Underwater Optical Wireless Communications using Monte Carlo Simulation
Authors: Jasman F. , Zaiton A. M. , Ahmad Z. , Rihawi Z.
Published: January 2019

Optical wireless communications has shown tremendous potential for underwater applications as it can provide higher bandwidth and better security compared to acoustic technologies. In this paper,  an investigation on scattering regimes for underwater links using Monte Carlo simulation has been presented.While the focus of this paper is on diffuse links, the simulation results of collimated links is also provided for comparison purpose. Three types of water namely clear, coastal and turbid water are being used in the simulation. It is shown that the effect of scattering on the path loss cannot be accurately modeled by the existing channel model; ie. Beers-Lambert (BL) law.  It has been shown that  the distance at which the unscattered light drops to zero can be used to estimate the transition point for the scattering regimes in case of diffuse links. The transition point for diffuse links in coastal water and turbid water can be estimated to be around 22 m and 4 m respectively. Further analysis on the scattering order probability at different scattering regimes illustrates how scattering is affected by beam size, water turbidity and distance. From the frequency response plot, it is estimated that the bandwidth of several order of GHz can be achieved when the links are operating in the minimal scattering region and will reduce to several hundreds of MHz when the link is operating in multiple scattering region.
Characteristic and Surge Impedance Variation Impact on Transmission Line Performance
Authors: H. Rawa Muhyaddin J.
Published: January 2019

Modeling of power systems is essential to perform various network analyses. Voltage regulation, line losses and transmission line efficiency are greatly affected by transmission line parameters. Hence, accurate modeling of transmission line is required. The aim of this paper is to study the impact of characteristic and surge impedances on voltage profile, voltage regulation and transmission line efficiency.
Neural Network Model Development with Soft Computing Techniques for Membrane Filtration Process
Authors: Yusuf Zakariah , Wahab Norhaliza Abdul , Sahlan Shafishuhaza
Published: January 2019

Membrane bioreactor employs an efficient filtration technology for solid and liquid separation in wastewater treatment process. Development of membrane filtration model is significant as this model can be used to predict filtration dynamic which is later utilized in control development. Most of the available models only suitable for monitoring purpose, which are too complex, required many variables and not suitable for control system design. This work focusing on the simple time seris model for membrane filtration process using neural network technique. In this paper, submerged membrane filtration model developed using recurrent neural network (RNN) train using genetic algorithm (GA), inertia weight particle swarm optimization (IW-PSO) and gravitational search algorithm (GSA). These optimization algorithms are compared in term of its accuracy and convergent speed in updating the weights and biases of the RNN for optimal filtration model. The evaluation of the models is measured using three performance evaluations, which are mean square error (MSE), mean absolute deviation (MAD) and coefficient of determination (R2). From the results obtained, all methods yield satisfactory result for the model, with the best results given by
 IW-PSO.
Performance Evaluation of Two Port and Four Port Measurement for Twisted Pair Cable
Authors: Bin Asrokin Azhari , Bin A. Rahim Mohamad Kamal
Published: January 2019

A balance-unbalance (balun) transformer is commonly used to connect the balance 100 Ohm twisted pair cable to the unbalance 50 Ohm network analyzer ports, but due to the limitations of the core (i.e. ferrite) inside the balun, the balun can only effectively operates at a certain band of frequencies. This limitation can be eliminated by using a 4-port vector network analyzer (VNA) which is done by connecting the VNA’s ports to each conductor end. The extracted S-parameters will then be transformed to a 2-port S-parameters in differential mode at both ports. To validate the measurement technique, S-parameter measurement by using the 4-Port Network Analyzer without any balun will be compared to the measurement which used the 2-Port Network Analyzer with the balun transformers. Two twisted pair cable distances are selected as reference which are 500, and 1000 meters with nominal copper diameter of 0.5mm. Based on the measurement results, the 4-ports measurement shows good correlation with the 2-ports measurement especially at 500m distance. This shows that the 4-ports measurement setup is suitable to be used to measure twisted pair copper cable and possible to measure at a higher frequency band such as up to 500 MHz but at a shorter twisted pair cable distance.
High Voltage Durability of Bambusa Vulgaris as a Bio-composite Material
Authors: Mat Zain M. Y. , Ali M.T. , Hussin A. N. H.
Published: January 2019

This study is conducted in order to measure and identify the ability of a bio-composite material to the high voltage. According to it, the developed bio-composite material is tested to ensure the maximum voltage that the material can hold. The bio-composite material which made from a mixture of Bambusa Vulgaris and a selected polymer named as High Density Polyethylene (HDPE). The Bambusa Vulgarisis going through several processes before mixed together with HDPE using wood plastic composite (WPC) technique which also consists of several stages. There are several samples of bio-composite substance are fabricated. The difference among them is the composition of the raw materials (Bambusa Vulgaris and HDPE) used. In this research, the high voltage measurement which also called as breakdown voltage measurement of the bio-composite material is examined by using appropriate experiments. All the experimental results are presented and discussed in this paper.
Probabilistic Performance Index based Contingency Screening for Composite Power System Reliability Evaluation
Authors: K Venkata Satheesh Babu , V Madhusudan , V Ganesh
Published: January 2019

Composite power system reliability involves assessing the adequacy of generation and transmission system to meet the demand at major system load points. Contingency selection was being the most tedious step in reliability evaluation of large electric systems. Contingency in power system might be a possible event in future which was not predicted with certainty in earlier research. Therefore, uncertainty may be inevitable in power system operation. Deterministic indices may not guarantee the randomness in reliability assessment. In order to account for volatility in contingencies, a new performance index proposed in the current research. Proposed method assimilates the uncertainty in computational procedure. Reliability test systems like Roy Billinton Test System-6 bus system and IEEE-24 bus reliability test systems were used to test the effectiveness of a proposed method.
Low Speed Estimation of Sensorless DTC Induction Motor Drive Using MRAS with Neuro Fuzzy Adaptive Controller
Authors: R Mini , P. Shabana Backer , Satheesh B. Hariram , N Dinesh M.
Published: January 2019

This paper presents a closed loop Model Reference Adaptive system (MRAS) observer with artificial intelligent Nuero fuzzy controller (NFC) as the adaptation technique to mitigate the low speed estimation issues and to improvise the performance of the Sensorless Direct Torque Controlled (DTC) Induction Motor Drives (IMD). Rotor flux MRAS and reactive power MRAS with NFC is explored and detailed analysis is carried out for low speed estimation. Comparative analysis between rotor flux MRAS and reactive power MRAS with PI as well as NFC as adaptive controller is performed and results are presented in this paper. The comparative analysis among these four speed estimation methods shows that reactive power MRAS with NFC as adaptation mechanism shows reduced speed estimation error and actual speed error at steady state operating conditions when the drive is subjected to low speed operation. Simulation carried out using MATLAB-Simulink software to validate the performance of the drive especially at low speeds with rated and variable load conditions.
Challenges and Opportunities of Internet of Things in Healthcare
Authors: Rghioui Amine , Oumnad Abdelmajid
Published: January 2019

The Internet of  Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems. 
Wave File Features Extraction using Reduced LBP
Authors: Al-Qaisi Aws , Khawatreh Saleh A. , Sharadqah Ahmad A. , Alqadi Ziad A.
Published: January 2019

In this work, we present a novel approach for extracting features of a digital wave file. This approach will be presented, implemented and tested. A signature or a key to any wave file will be created.  This signature will be reduced to minimize the efforts of digital signal processing applications. Hence, the features array can be used as key to recover a wave file from a database consisting of several wave files using reduced Local binary patterns (RLBP). Experimental results are presented and show that The proposed RLBP method is at least 3 times faster than CSLBP method, which mean that the proposed method is more efficient.
Keyframe Selection of Frame Similarity to Generate Scene Segmentation Based on Point Operation
Authors: Widiarto Wisnu , Hariadi Mochamad , Yuniarno Eko Mulyanto
Published: January 2019

Video segmentation has been done by grouping similar frames according to the threshold. Two-frame similarity calculations have been performed based on several operations on the frame: point operation, spatial operation, geometric operation and arithmatic operation. In this research, similarity calculations have been applied using point operation: frame difference, gamma correction and peak signal to noise ratio. Three-point operation has been performed in accordance with the intensity and pixel frame values. Frame differences have been operated based on the pixel value level. Gamma correction has analyzed pixel values and lighting values. The peak signal to noise ratio (PSNR) has been related to the difference value (noise) between the original frame and the next frame. If the distance difference between the two frames was smaller then the two frames were more similar. If two frames had a higher gamma correction factor, then the correction factor would have an increasingly similar effect on the two frames. If the value of PSNR was greater then the comparison of two frames would be more similar. The combination of the three point operation methods would be able to determine several similar frames incorporated in the same segment
Detection of Real Time QRS Complex Using Wavelet Transform
Authors: Yasmeen Fatima , Mallick Mohammad Arifuddin , Uzzaman Khan Yusuf
Published: January 2019

This paper presents a novel method for QRS detection. To accomplish this task ECG signal was first filtered by using a third order Savitzky Golay filter. The filtered ECG signal was then preprocessed by a Wavelet based denoising in a real-time fashion to minimize the undefined noise level. R-peak was then detected from denoised signal after wavelet denoising. Windowing mechanism was also applied for finding any missing R-peaks. All the 48 records have been used to test the proposed method. During this testing, 99.97% sensitivity and 99.99% positive predictivity is obtained for QRS complex detection.
Real Time Implementation of Fuzzy Adaptive PI-sliding Mode Controller for Induction Machine Control
Authors: Habbab Mohamed , Hazzab Abdeldjebar , Sicard Pierre
Published: January 2019

In this work, a fuzzy adaptive PI-sliding mode control is proposed for Induction Motor speed control. First, an adaptive PI-sliding mode controller with a proportional plus integral equivalent control action is investigated, in which a simple adaptive algorithm is utilized for generalized soft-switching parameters. The proposed control design uses a fuzzy inference system to overcome the drawbacks of the sliding mode control in terms of high control gains and chattering to form a fuzzy sliding mode controller. The proposed controller has implemented for a 1.5kW three-Phase IM are completely carried out using a dSPACE DS1104 digital signal processor based real-time data acquisition control system, and MATLAB/Simulink environment. Digital experimental results show that the proposed controller can not only attenuate the chattering extent of the adaptive PI-sliding mode controller but can provide high-performance dynamic characteristics with regard to plant external load disturbance and reference variations. 
Improved p-q Harmonic Detection Method for Hybrid Active Power Filter
Authors: Thuyen Chau Minh
Published: January 2019

The accuratedetermination of the load harmonic current is one of the important factors, it decides to effect of harmonic filtering and reactive power compensation for Hybrid Active Power Filter. The p-q harmonic detection method has been widely used in determining the harmonic currents of Hybrid Active Power Filter. However, when using this method, the dynamic response of Hybrid Active Power Filter in the transient period will have a large transient time and overshoot whenever the load changes abruptly. Therefore, in this paper an improved p-q harmonic current detection method based on fuzzy logic is proposed, which aims to reduce the overshoot and transient time in transient duration of Hybrid Active Power Filter. In order to compare the dynamic response of conventional and improved p-q harmonic detection methods, simulation results have demonstrated that: the proposed method has a shorter response time, the magnitude of the supply current in the transient time is smaller and the overshoot of the fundamental active and reactive power components is very small. This has a practical significance that contributes to the stability of the Hybrid Active Power Filter system
A Statistical Approach to Adaptive Playout Scheduling in Voice Over Internet Protocol Communication
Authors: Chandran Priya , Lingam Chelpa
Published: January 2019

Factors like network delay, latency and bandwidth significantly affect the quality of communication using Voice over Internet Protocol. The use of jitter buffer at the receiving end compensates the effect of varying network delay up to some extent. But the extra buffer delay given for each packet plays a major role in playing late packets and thereby improving voice quality. As the buffer delay increases packet loss rate decreases, which in general is a very good sign. However, an increase of buffer delay beyond a certain limit affects the interactive quality of voice communication. In this paper, we propose a statistical framework for adaptive playout scheduling of voice packets based on network statistics, packet loss rate and availability of packets in the buffer. Experimental results show that the proposed model allocates optimal buffer delay with the lowest packet loss rate when compared with other algorithms.
Sensing and Sharing Schemes for Spectral Efficiency of Cognitive Radios
Authors: Kaushik M. K. , Yoganandam Y. , Sahoo SK
Published: January 2019

Increase in data traffic, number of users and their requirements laid to a necessity of more bandwidth. Cognitive radio is one of the emerging technology which addresses the spectrum scarcity issue. In this work we study the advantage of having collaboration between cognitive enabled small cell network and primary macrocell. Different from the existing works at spectrum sensing stage we are applying enhanced spectrum sensing to avoid probability of false alarms and missed detections which has impact on spectral efficiency. Later power control optimization for secondary users known as Hybrid spectrum sharing is used for further improvement of spectral efficiency. Furthermore, the failed packets of Primary users are taken care by high ranked relays which in turn decreases the average Primary user packet delay by 20% when compared between assisted Secondary user method and non-assisted Secondary user method. 
Experimental Analysis of Web Browser Sessions Using Live Forensics Method
Authors: Umar Rusydi , Yudhana Anton , Nur Faiz Muhammad
Published: January 2019

In today's digital era almost every aspect of life requires the internet, one way to access the internet is through a web browser. For security reasons, one developed is private mode. Unfortunately, some users using this feature do it for cybercrime. The use of this feature is to minimize the discovery of digital evidence. The standard investigative techniques of NIST need to be developed to uncover an ever-varied cybercrime. Live Forensics is an investigative development model for obtaining evidence of computer usage. This research provides a solution in forensic investigation effectively and efficiently by using live forensics. This paper proposes a framework for web browser analysis. Live Forensics allows investigators to obtain data from RAM that contains computer usage sessions. 
Adaptive Multi-state Millimeter Wave Cell Selection Scheme for 5G communication
Authors: Attiah Mothana L , Md Isa Azmi Awang , Zakaria Zahriladha , Abdullah Nor Fadzilah , Ismail Mahamod , Nordin Rosdiadee
Published: January 2019

Millimeter wave bands have been introduced as one of the most promising solutions to alleviate the spectrum secrecy in the upcoming future cellular technology (5G) due the enormous amount of raw bandwidth available in these bands. However, the inherent propagation characteristics of mmWave frequencies could impose new challenges i.e. higher path loss, atmospheric absorption, and rain attenuation which in turn increase the outage probability and hence, degrading the overall system performance. Therefore, in this paper, a novel flexible scheme is proposed namely Adaptive Multi-State MmWave Cell Selection (AMSMC-S) through adopting three classes of mmWave base stations, able to operate at various mmWave carrier frequencies (73, 38 and 28 GHz). Two mmWave cellular Grid-Based cell deployment scenarios have been implemented with two inter-site-distances 200 m and 300 m, corresponding to target area of (2.1 km2) and (2.2 km2). The maximum SINR value at the user equipment (UE) is taken in to consideration to enrich the mobile user experience. Numerical results show an improvement of overall system performance, where the outage probability reduced significantly to zero while maintaining an acceptable performance of the 5G systems with approximately more than 50% of the mobile stations with more than 1Gbps data rate. 
Modified Ultra Wideband (UWB) Antipodal Vivaldi Antenna for 5
Authors: Pramono Subuh , S. Budi Basuki , Hariyadi Tommi
Published: January 2019

This paper presents a half triangular Comb-shaped slits edge Antipodal Vivaldi Antenna (Comb-AVA) as compared to the conventional Antipodal Vivaldi Antenna (AVA) design. This proposed antenna covers 20-40 GHz spectrum. This Comb-AVA antenna is designed for the 5G application which is addressed to cover a dualband 28/38 GHz frequencies. A half triangular comb-shaped slits edge structure is employed to investigate its effects on antenna parameters. This proposed Comb-AVA occupies a 25x8 mm2 of FR 4 substrate (𝜀𝛾 = 4.4, tan δ=0.02, thinkness 1.6 mm). It has impedance bandwidth (S11≤-10 dB) along 20-40 GHz spectrum and fractional bandwidth (FBW) ≥0.5. It means that the bandwidth is categorized as ultra wideband (UWB). In addition, there is 11 dB refinement of return loss in the CombAVA design at 38 GHz frequency. VSWR value is in range of 1.054 to 1.396. This proposed antena also has a wider angular width (3 dB) than the AVA. Higher directivity and gain is generated by Comb-AVA at 28 GHz. This proposed antenna has good performances and suitable for 5G application. 
A Study of Mobile User Movements Prediction Methods
Authors: Subramanian J. Venkata , Govindarajan S.
Published: January 2019

For a decade and more, the Number of smart phone users count increasing day by day. With the drastic improvements in Communication technologies, the prediction of future movements of mobile users needs also have important role. Various sectors can gain from this prediction. Communication management, City Development planning, and locationbased services are some of the fields that can be made more valuable with movement prediction. In this paper, we propose a study of several Location Prediction Techniques in the following areas
HII: Histogram Inverted Index For Fast Images Retrieval
Authors: Munarko Yuda , Eko Minarno Agus
Published: January 2019

This work aims to improve the speed of search by creating an indexing structure in CBIR system. We utilised an inverted index structure that usually used in text retrieval with a modification. The modified inverted index is built based on histogram data that generated using Multi Texton Histogram (MTH) and Multi Texton Co-Occurrence Descriptor (MTCD) from 10,000 images of Corel dataset. When building the inverted index, we normalised value of each feature into a real number and considered pairs of feature and value that owned by a particular number of images. Based on our investigation, on MTCD histogram of 5,000 data test, we found that by considering histogram variable values which owned by maximum 12% of images, the number of comparison for each query can be reduced by 67.47% in a rate, the precision is 82.2%, and the rate of access to disk is 32.83%. Furthermore, we named our approach as Histogram Inverted Index (HII). 