bluuebunny/crossref_metadata_2025_split huggingface dataset:
Performance evaluation of UE-controlled intelligent handover algorithm for natural disaster
Authors: Laily Yusof Azita , Eiza Azhar Ainnur , Ya’acob Norsuzila 
Published: August 2020

<span>This paper proposes a UE-controlled intelligent handover algorithm for natural disaster. In this handover algorithm, two variables known as modified Received Signal Strength (RSSm) and Left over Power (LoP) are identified. The RSSm is an improved formulation from RSS where distance fraction coefficient has been introduced. The fraction coefficient of 0.2 is used where the affected areas is reduced so that the users can receive good signal quality due to its location near to the base station. Meanwhile, the LoP also has been investigated to control power consumption of base station. In this research, 80% RSSm and 20% LoP has been chosen for the proposed handover algorithm as it can maintain good quality of service (QoS) for all users and also can prolong battery life. From the simulation results obtained, the average number of handovers for the proposed handover algorithm outperformed the conventional natural disaster handover algorithm.</span>
Improvements of trapezoid antenna gain using artificial magnetic conductor and frequency selective surface
Authors: Md Ali Siti Adlina , Abu Maisarah , Normi Zabri Siti 
Published: August 2020

<span>This paper presents the performance enhancement of the trapezoid antenna with Artificial Magnetic Conductor (AMC) and Frequency Selective Surface (FSS). The antenna, AMC and FSS structures are printed on 0.254 mm of RT/Duroid 5880 high frequency laminate. The performances of the antenna with and without AMC and FSS were evaluated. Three cases are analyzed; antenna alone, antenna with AMC and antenna with AMC-FSS. The 2x3 arrays of AMC and AMC-FSS were positioned at the back of the antenna with 6 mm air gap. The antenna alone works at 12 GHz, and shifted to 12.35 GHz and 12.33 GHz for case 2 and case 3, respectively. Despite the shift in the resonance, the antenna is still operating well at 12 GHz with a return loss –16.70 dB for case 2 and–16.84 dB for case 3. Case 3 effectively enhanced the antenna gain from 4.43 dB to 6.74 dB and contributed to a directive antenna. Moreover, case 3 also successfully reduced the radiation of the antenna that penetrates into human body as the antenna is applied for on-body applications. </span>
Numerical simulation of DIC drying process on matlab distributed computing server
Authors: Saipan Saipol Hafizah Farhah , Alias Norma 
Published: August 2020

<span>Instant controlled pressure drop, also known as DIC, is one of the drying techniques that has been used for texturing, extracting and drying various food products. Mathematical model has been used to explain the drying process, although most of the studies focused on the statistical regression model approach. Due to the limitations of regression model, which neglects the fundamental of dehydration process, t</span><span>his paper presents the development of mathematical models to detect, solve and visualize the three-dimensional (3D) heat and mass transfer in DIC drying process. </span><span>Finite Difference Method (FDM) with central difference formula is used to discretize the mathematical models. A large sparse of system of linear equation (SLE), which represents the actual drying process, is solved by using some numerical methods, such as Jacobi (JB), Red Black Gauss Seidel (RBGS), Alternating Group Explicit with Douglas (AGED) and Brian (AGEB) methods. Based on the numerical results, high execution time and high computational complexity have been shown. In order to reduce the execution time and computational complexity, the parallel algorithm based on domain decomposition technique has been implemented on the MATLAB Distributed Computing Server (MDCS). The parallel algorithm of the numerical methods was evaluated and compared based on the parallel performance metrics: execution time, speed up, efficiency, effectiveness, temporal performance and granularity. From the parallel performance metrics, it was found that the PAGEB approach had better performance, followed by PAGED, PRBGS and PJB methods.</span>
Controlling of jerk chaotic system via linear feedback control strategies
Authors: Adel Abed Karam 
Published: August 2020

In this paper, the strategies of linear feedback control for jerk system is considered. These strategies consist of four strategies (ordinary feedback control, dislocated feedback control, speed feedback control, and enhancing feedback control). We propose to combine between these strategies and obtained a better result from this combine. Numerical solution achieved the same results.
A review of internet of medical things (IoMT) - based remote health monitoring through wearable sensors: a case study for diabetic patients
Authors: AlShorman Omar , AlShorman Buthaynah , Al-khassaweneh Mahmood , Alkahtani Fahad 
Published: August 2020

<span>The latest advances and trends in information technology and communication have a vital role in healthcare industries. </span><span>Theses advancements led to the Internet of Medical Things (IoMT) which provides a continuous, remote and real-time monitoring of patients. The IoMT </span><span>architectures still face many challenges related to the bandwidth, communication protocols, big data and data volume, flexibility, reliability, data management, data acquisition, data processing and analytics availability, cost effectiveness, data security and privacy, and energy efficiency. The goal of this paper is to find </span><span>feasible </span><span>solutions to enhance the healthcare living facilities using remote health monitoring (RHM) and IoMT. In addition, the enhancement of the prevention, prognosis, diagnosis and treatment abilities using IoMT and RHM is also discussed. </span><span>A case study of monitoring the vital signs of diabetic patients using real-time data processing and IoMT is also presented</span><span>. </span>
Towards IR4.0 implementation in e-manufacturing: artificial intelligence application in steel plate fault detection
Authors: Abdullahi Adeleke , Azah Samsudin Noor , Rasidi Ibrahim Mohd , Syariff Aripin Muhammad , Ahmad Khalid Shamsul Kamal , Ali Othman Zulaiha 
Published: August 2020

<span>Fault detection is the task of discovering patterns of a certain fault in industrial manufacturing. Early detection of fault is an essential task in industrial manufacturing. Traditionally, faults are detected by human experts. However, this method suffers from cost and time. In this era of Industrial revolution IR 4.0, machine learning (ML) methods and techniques are developed to solve fault detection problem. In this study, three standard ML models: LR, NB, and SVM are developed for the classification problem. The experimental dataset used in this study consists of steel plates faults. The dataset is retrieved from UCI machine learning repository. Three standard evaluation methods: accuracy, precision, and recall are validated on the classification models. Logistic regression (LR) model achieved the highest accuracy and precision scores of 94.5% and 0.756 respectively. In addition, the SVM model had the highest recall score of 0.317. The results showed the significant impact of AI/ML approach in steel plates fault diagnosis problem. </span>
An overview of traffic congestion detection and classification techniques in VANET
Authors: Idura Ramli Nurshahrily , Mohamed Rawi Mohd Izani 
Published: August 2020

<span>Vehicular traffic congestion has been and still is a major problem for many countries and knowledge about the traffic condition is important in order to schedule, plan and avoid traffic congestion. With recent development in technology, various efforts and methods are proposed in mitigating traffic congestion. Vehicular Ad-hoc NETwork (VANET) is very much in the hype in addressing this issue due to its capabilities and adaptation to scalability, highly dynamic topology as well as cooperative communication. A popular focus is in detecting and classisying traffic congestion which presents various techniques and methodologies. This paper presents an overview of traffic congestion detection and classification methods of various related techniques in VANET, organized from the research perspective. Qualitative analysis is presented to classify these strategies in its system architecture, detection and classification methods, as well as its simulated mobility environment and simulation tools used. The analysis is useful in understanding all the techniques and methods applied in resolving this issue in the research domain. </span>
Unequal clustering algorithm with IDA* multi-hop routing to prevent hot spot problem in WSNs
Authors: A. Alkadhmawee Ahmed , A. Altaha Mohammed , Mahmood Lafta Wisam 
Published: August 2020

Energy conservation techniques are considered as the primary means of lengthening the lifetime of Wireless Sensor Networks (WSNs). Clustering is a useful technique that achieves long-term operation of the network. Cluster heads that are near the base station are expected to die early because they are responsible for collecting data that comes from far away in addition to their own data, thereby leading to problem of hot spot in the WSN.This paper presents a new protocol that uses an unequal clustering algorithm with an IDA* routing method to address the hot spot problem. The base station divides the network into three levels of unequal sizes of clusters. The base station takes into consideration the energy level and the distance from the base station for cluster-head selection in each cluster. The cluster head will be changed based on the energy threshold for each cluster. The proposed method uses an IDA* algorithm for efficient multi-hop routing in the network. The uneven clustering algorithm reduces the energy consumption of the nodes, thereby minimising the hot spot problem. The obtained simulation results prove that our approach increases the load balancing, improves the stability and prolongs the network lifetime compared with other related approaches.<p> </p>
Characterization of the koch fractal hexagonal loop frequency selective surface for X-band application
Authors: Binti Mohamed Nafis Nur Biha , Bin A. Rahim Mohamad Kamal , Bin Ayop Osman , Bin A MAjid Huda , Tuntrakool Sunti 
Published: August 2020

<p>This paper presented the bandstop Koch fractal hexagonal loop frequency selective surface (FSS) for the X-band application. The simulated transmission coefficient response (S_21) had been obtained by using CST software. The proposed Koch fractal hexagonal loop FSS structure is highly insensitive towards angular stability and also incident polarization up to 60 degree , with deviation of resonant frequency, f_r below than 1%. The parametric analysis on the effect of the periodicity, width, and height of the fractal FSS structure on the S_21 has been illustrated and discussed thoroughly.</p>
Multiple element of miniaturized printed log-periodic second series koch dipole array antenna for wideband chipless RFID tag reader
Authors: Bin Jalil Mohd Ezwan , A. Rahim Mohamad Kamal , Asmawati Samsuri Noor , Tuntrakool Sunti 
Published: August 2020

This paper aims to produce a low profile, wideband, and high gain antenna for chipless RFID tag readers. A miniaturized and wideband printed Log-Periodic Second Series Koch Dipole Array (LPSSKDA) with eleven elements operating over 0.8 GHz-3.2 GHz is designed using the FR4 board. The single LPSSKDA antenna, which acts as the chipless RFID reader antenna having gain between 5.2 and 6.1 dBi and frequency range from 1-3 GHz. A double element of the LPSSKDA antenna is proposed for improving the antenna gain to 6.9-7.9 dBi over the frequency range. The antenna is fabricated to validate the simulation and measurement results in terms of reflection coefficient, radiation pattern, and surface current distribution.
A new hybrid conjugate gradient algorithm for unconstrained optimization with inexact line search
Authors: N. Jardow Fanar , Al-Naemi Ghada M. 
Published: August 2020

Many researchers are interested for developed and improved the conjugate gradient method for solving large scale unconstrained optimization problems. In this work a new parameter will be presented as a convex combination between RMIL and MMWU. The suggestion method always produces a descent search direction at each iteration. Under Strong Wolfe Powell (SWP) line search conditions, the global convergence of the proposed method is established. The preliminary numerical comparisons with some others CG methods have shown that this new method is efficient and robust in solving all given problems.
An efficient traffic contention and control mechanism to improve QoS in heterogeneous wireless sensor networks
Authors: Ganesh Kavitha , Latchoumy P. , Sonya A. 
Published: August 2020

<span>Heterogeneous Wireless Sensor Networks (HWSN) gathers information from a cooperative network. In HWSN, the sensor nodes are scattered and the major challenges are topology control, battery optimization, packet loss and link lifetime. The existing techniques do not concentrate on all the mentioned issues. The objective of this work is to provide congestion-free data transfer with higher throughput and increased packet delivery ratio. In the proposed methodology, three protocols are designed and developed, namely, Hop by Hop Rate Adjustment Protocol (HHRA), Energy Efficient Data Transfer Protocol (EEDT) and Alternative Routing Congestion Control Protocol (ARCC). The HHRA protocol senses the traffic in the channel and adjusts the transmission rate accordingly to avoid congestion. Secondly, the EEDT protocol is used to find specific nodes that are more efficient and transfer packets through those nodes to improve throughput. The ARCC protocol is used to redirect the path of transmission during the occurrence of congestion. Thus, the proposed traffic contention and control mechanisms ensures congestion free transmission and increases the packet delivery ratio by 23% and average throughput by 20% compared to the Dynamic Contention Window based Congestion Control (DCWCC) algorithm. </span>
A proactive metaheuristic model for optimizing weights of artificial neural network
Authors: Hakem Alsaeedi Ali , Hussein Aljanabi Ali , Ebady Manna Mehdi , L. Albukhnefis Adil 
Published: August 2020

<span>This paper proposes the Particle Swarm Optimization model for enhancing the performance of an Artificial Neural Network. The learning process of Artificial Neural Network requires a long time to satisfy requirements because of processing complexity of the backpropagation algorithm that has been used in training Artificial Neural Network. It is a nonlinear complex model that can be used to configure and train an artificial neuron system. Both Artificial Neural Network and Particle Swarm Optimization model have been managed to solve and optimize several nonlinear models. Heuristic Optimization Weight of Artificial Neural Network (HNN) is a proactive metaheuristic model proposed to optimize the performance of Artificial Neural Network. The proposed system applies Particle Swarm Optimization to find the optimum weights of the Artificial Neural Network instead of using the Backpropagation algorithm. Experimentally, the proposed system has required less processing time (average of 76.91 Sec.) than Backpropagation (average of 93.32 Sec). Furthermore, It has provided better classification accuracy (start from 80% to 97.20%) comparing with Backpropagation (start from 75.32% to 94.32%).</span>
Association of Established Blood Pressure Loci With 10‐Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension
Authors: Poveda Alaitz , Atabaki‐Pasdar Naeimeh , Ahmad Shafqat , Hallmans Göran , Renström Frida , Franks Paul W. 
Published: August 2020

Background
Genome‐wide association studies have identified >1000 genetic variants cross‐sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure‐associated variants with long‐term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population.

Methods and Results

We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRS
SBP
): 554 variants; diastolic blood pressure GRS (GRS
DBP
): 481 variants; mean arterial pressure GRS (GRS
MAP
): 20 variants; pulse pressure GRS (GRS
PP
): 478 variants; hypertension GRS (GRS
HTN
): 22 variants; combined GRS (GRS
com
b
): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRS
comb
was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.10‒1.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.99‒1.25) while controlling for traditional risk factors. The addition of GRS
comb
to a model containing traditional risk factors only marginally improved discrimination (Δarea under the ROC curve = 0.001–0.002).

Conclusions
GRSs based on discovered blood pressure‐associated variants are associated with long‐term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.
Carotid Lumen Diameter Is Associated With All‐Cause Mortality in the General Population
Authors: Fritze Felix , Groß Stefan , Ittermann Till , Völzke Henry , Felix Stephan B. , Schminke Ulf , Dörr Marcus , Bahls Martin 
Published: August 2020

Background
Common carotid intima–media thickness (cIMT) is a biomarker for subclinical atherosclerosis and is associated with all‐cause as well as cardiovascular mortality. Higher cIMT is accompanied by a compensatory increase in lumen diameter (LD) of the common carotid arteries. Whether cIMT or LD carry more information with regard to mortality is unclear.

Methods and Results

A total of 2751 subjects (median age 53 years; 52% female) were included. During a median follow‐up of 14.9 years (range: 12.8–16.5) a total of 506 subjects died. At baseline, cIMT and LD were assessed by carotid ultrasound scans. Multivariable Cox regression models were used to relate cIMT, LD, LD adjusted for cIMT (LD+cIMT), and LD/cIMT ratio with all‐cause, cardiovascular, and noncardiovascular mortality. All models were ranked using Akaike's information criterion. Harrel's c statistic was used to compare the models' predictive power for mortality. A 1‐mm increase in LD was related to a higher risk for all‐cause mortality (hazard ratio [HR], 1.29; 95% CI, 1.14–1.45,
P
<0.01). This association remained significant when cIMT was added to the model (HR, 1.26; 95% CI, 1.11–1.42;
P
<0.01). A 1‐mm higher cIMT was also related with greater mortality risk (HR, 1.73; 95% CI, 1.09–2.75). The LD/cIMT ratio was not associated with all‐cause mortality. LD had the lowest Akaike's information criterion regarding all‐cause mortality and improved all‐cause mortality prediction compared with the null model (
P
=0.01). CIMT weakened all‐cause mortality prediction compared with the LD model.

Conclusions
LD provided more information for all‐cause mortality compared with cIMT in a large population‐based sample.
Intermittent Hypoxia Triggers Early Cardiac Remodeling and Contractile Dysfunction in the Time‐Course of Ischemic Cardiomyopathy in Rats
Authors: Bourdier Guillaume , Détrait Maximin , Bouyon Sophie , Lemarié Emeline , Brasseur Sandrine , Doutreleau Stéphane , Pépin Jean‐Louis , Godin‐Ribuot Diane , Belaidi Elise , Arnaud Claire 
Published: August 2020

BACKGROUND
Sleep‐disordered breathing is associated with a poor prognosis (mortality) in patients with ischemic cardiomyopathy. The understanding of mechanisms linking intermittent hypoxia (IH), the key feature of sleep‐disordered breathing, to ischemic cardiomyopathy progression is crucial for identifying specific actionable therapeutic targets. The aims of the present study were (1) to evaluate the impact of IH on the time course evolution of cardiac remodeling and contractile dysfunction in a rat model of ischemic cardiomyopathy; and (2) to determine the impact of IH on sympathetic activity, hypoxia inducible factor‐1 activation, and endoplasmic reticulum stress in the time course of ischemic cardiomyopathy progression.

METHODS AND RESULTS
Ischemic cardiomyopathy was induced by a permanent ligature of the left coronary artery in male Wistar rats (rats with myocardial infarction). Rats with myocardial infarction were then exposed to either IH or normoxia for up to 12 weeks. Cardiac remodeling and function were analyzed by Sirius red and wheat germ agglutinin staining, ultrasonography, and cardiac catheterization. Sympathetic activity was evaluated by spectral analysis of blood pressure variability. Hypoxia‐inducible factor‐1α activation and burden of endoplasmic reticulum stress were characterized by Western blots. Long‐term IH exposure precipitated cardiac remodeling (hypertrophy and interstitial fibrosis) and contractile dysfunction during the time course evolution of ischemic cardiomyopathy in rodents. Among associated mechanisms, we identified the early occurrence and persistence of sympathetic activation, associated with sustained hypoxia‐inducible factor‐1α expression and a delayed pro‐apoptotic endoplasmic reticulum stress.

CONCLUSIONS
Our data provide the demonstration of the deleterious impact of IH on post–myocardial infarction remodeling and contractile dysfunction. Further studies are needed to evaluate whether targeting sympathetic nervous system or HIF‐1 overactivities could limit these effects and improve management of coexisting ischemic cardiomyopathy and sleep‐disordered breathing.