bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiple Venous Malformations as a Cause of Pulsatile Tinnitus
Authors: Al Afif Ayham , Alamoudi Uthman , Al-Sayed Ahmed A. , Bance Manohar
Published: August 2020

Introduction. Pulsatile tinnitus is a relatively common presentation in otolaryngology clinics, most cases of which have a treatable cause. This presentation warrants a thorough workup to identify treatable, and rule out life-threatening, etiologies. We present a case of a patient with pulsatile tinnitus arising from multiple dilated venous channels in the head and neck.Case Presentation.We present the case of a 65-year-old Caucasian female with a two-year history of progressive, bilateral pulsatile tinnitus, which had become debilitating. Computed-tomographic angiography (CTA) studies ruled out an intracranial vascular cause for her symptoms. However, computed tomography (CT) scanning and magnetic resonance imaging (MRI) revealed multiple dilated bilateral, low-flow, venous channels throughout the head and neck. The proximity of such dilated venous channels to the temporal bone provides a route for sound to be transmitted to the inner ear.Conclusion. Arterial, venous, and systemic etiologies can cause pulsatile tinnitus. Arteriovenous malformations (AVMs) of the head and neck represent less than 1% of cases. In our patient, dilated low-flow venous malformations are the likely source of her symptoms, which is the first reported case in the literature.
Toxoplasmosis Presenting as Nonhealing Cutaneous Ulcer
Authors: Adhikari M. , Dhakal S. , Bhattarai S. , Rai U.
Published: August 2020

Introduction. Systemic manifestation of toxoplasmosis is commonly seen in immune-compromised individuals. Skin manifestations are seen commonly in conjunction with systemic features. Isolated cutaneous toxoplasmosis is extraordinarily rare in immunocompetent patients. Case Description. A 64-year-old female presented to the Dermatology Outpatient Department (OPD), with a nonhealing ulcer over dorsum of the left hand for one year. The patient did not have any systemic diseases. Serology tests were negative. An incisional biopsy of the lesion revealed dense inflammatory cell infiltrates comprising predominantly of plasma cells and lymphocytes, multinucleated giant cells, and focal abscess formation in the dermis. Periodic Acid Schiff (PAS) stain showed organisms in the dermis with morphological resemblance to tachyzoites of Toxoplasma gondii. Conclusion. Though rare, a possibility of primary cutaneous toxoplasmosis should always be considered and looked for, even in immunocompetent patients presenting with chronic nonhealing ulcers.
Endometriosis-Associated Massive Ascites in an Asian Woman: A Case Report of a Rare Clinical Entity
Authors: Eamudomkarn Nuntasiri , Likitdee Naratassapol , Kleebkaow Pilaiwan , Kietpeerakool Chumnan
Published: August 2020

Massive ascites as a presentation of endometriosis is a rare clinical entity that is most commonly seen in black nulliparous females. Herein, we describe a case of a 32-year-old multiparous Thai woman who presented with a two-year history of abdominal distension. Computerized tomography of the abdominopelvic region showed an infiltrative enhancing lesion involving the cul-de-sac and perirectal region with massive loculated ascites, suggesting carcinomatosis peritonei. Abdominal paracentesis was performed to yield fluid samples for evaluation, which revealed no malignant cells, and polymerase chain reaction (PCR) was negative for tuberculosis. The patient underwent exploratory laparotomy which revealed a large amount of serosanguinous ascites, thickened matted bowel loops, and necrotic debris covering the entire surface of the peritoneum and visceral organs. The surgical procedures included drainage of 6.5 liters of ascites, lysis adhesion, biopsy of the peritoneum, and right salpingo-oophorectomy. Histologic examination revealed benign endometrial glands with stroma at the peritoneum tissue and broad ligament. Other causes of ascites were excluded. The ascites responded to drainage and hormonal suppression. A final diagnosis of endometriosis was made based on these findings. Endometriosis should therefore be considered in differential diagnosis in women of childbearing age who present with ascites.
Spectral Radiative Properties of a Liquid n-Octane Droplet in the Midinfrared Region
Authors: Zhao Liang , Jing Chaoyu , Jin Yu , Chen Jiangping , Yin Ke , Yang Sujun , Liu Bingqing , Han Xiao , Tan Jianyu
Published: August 2020

The optical constants of a liquid hydrocarbon such as liquid n-octane are basic material properties that may be used to evaluate their thermal radiation transfer capabilities. In this study, the ellipsometry method was used to measure the optical constants of liquid n-octane in the midinfrared wavelength range of 2.0–16.0 μm at temperatures of 20, 50, and 80°C. Experimental analyses indicate the significant effect of temperature on the refractive index, although it has little effect on the absorption index. With increasing temperature, the refractive index shows a linear decrease, and reduced density leads to weaker absorption intensities. The radiative properties of n-octane droplets, including the absorption and scattering efficiency factors of single droplets with droplet radii r = 10, 20, 50, and 100 μm and the absorption and scattering coefficients in a droplets-air system of droplet volume fractions fv = 2%, 3%, and 4%, were calculated using Mie theory. The numerical results indicate that, with increasing temperature, the absorption efficiency factor slightly decreases, and the variation trend of the scattering efficiency factor is more complicated. With increasing droplet radius, the absorption efficiency factor increases within the studied wavelength range, except for certain absorption peaks, but the scattering efficiency factor tends to decrease. While the absorption is greater, the scattering is weaker for a given droplet radius. With an increasing volume fraction of n-octane droplets, the absorption and scattering coefficients increase linearly within the studied wavelength range.
Qingxin Kaiqiao Fang Inhibits Aβ25-35‐Induced Apoptosis in Primary Cultured Rat Hippocampal Neuronal Cells via the p38 MAPK Pathway: An Experimental Validation and Network Pharmacology Study
Authors: Wang Tian-Qi , Lai Xiao-Xiao , Xu Lu-Ting , Shen Yan , Lin Jian-Wei , Gao Shi-Yu , Hu Hai-Yan
Published: August 2020

Qingxin kaiqiao fang (QKF), a traditional Chinese medicine compound, has been applied to treat Alzheimer’s disease (AD) for many years and has exhibited remarkable effects. However, the underlying mechanism is still not explicit. The current study aims to investigate whether QKF exerts an antiapoptotic role through the p38 MAPK pathway in the course of AD. Network pharmacology analysis was applied to study the effective components, possible therapeutic targets, and AD‐related pathway of QKF. Further, the AD cell model was established using amyloid‐beta (Aβ)25-35 peptide and primary hippocampal neuronal cells extracted from newborn Sprague‐Dawley rats. Microtubule‐associated protein‐2 (MAP‐2) imaging was used to detect the morphology of hippocampal neurons. Western blot (WB) analysis was applied to detect the protein expression levels of p38 MAPK, p‐p38 MAPK, Bcl‐2, Bax, caspase‐3, and cleaved caspase‐3. Cell viability and apoptosis were determined using cell counting kit‐8 (CCK‐8) and terminal deoxynucleotidyl transferase‐mediated dUTP nick end‐labeling (TUNEL) assays, respectively. SB203580 and U46619 were used to detect changes in cell morphology, cell viability, and apoptosis upon inhibiting or activating p38 MAPK. Our present work showed that QKF protects hippocampal neuronal morphology, enhances cell viability, and reduces the number of TUNEL‐positive cells. In addition, our results showed that QKF increased the expression levels of antiapoptotic proteins and decreased the expression of proapoptotic proteins. QKF at 25 mg·mL−1 best inhibited neuronal apoptosis among the three doses of QKF by suppressing p38 MAPK activity. Collectively, QKF plays an antiapoptotic role via the p38 MAPK pathway.
n-Coherence Relative to a Hereditary Torsion Theory
Authors: Zhanmin Zhu
Published: August 2020

Let R be a ring, τ=T,ℱ a hereditary torsion theory of mod-R, and n a positive integer. Then, R is called right τ-n-coherent if every n-presented right R-module is τ,n+1-presented. We present some characterizations of right τ-n-coherent rings, as corollaries, and some characterizations of right n-coherent rings and right τ-coherent rings are obtained.
Association of Metformin Use with Asthma Exacerbation in Patients with Concurrent Asthma and Diabetes: A Systematic Review and Meta-Analysis of Observational Studies
Authors: Wen Li , Zhong Wang , Chai Yihui , Zhong Qin , Gao Jie , Guan Liancheng , Zhang mengzhi  , Huaiquan Liu , Haiyang Yu , Qingxue Wang , Changfu Yang , Yunzhi Chen
Published: August 2020

Background. Asthma and diabetes are both diseases that affect a wide range of people worldwide. As a common treatment for diabetes, metformin has also been reported to be effective in improving asthma outcomes. We conducted a combined analysis to examine the efficacy of metformin in reducing asthma exacerbation in patients with concurrent asthma and diabetes. Methods. We searched the PubMed, Embase, and CENTRAL databases for articles published prior to April 2020 to find observational studies of individuals with concurrent asthma and diabetes that compared the risk of asthma exacerbation between metformin users and nonusers. Two researchers separately screened the studies, extracted data, and evaluated the risk of bias. The primary outcome was the adjusted risk of asthma exacerbation. The secondary outcomes were the adjusted risk of asthma-related hospitalization and emergency room visits. Review Manager was used for data analysis and plotting. I2 and χ2 tests were used to estimate heterogeneity. A random effects or fixed effects model was used depending on the heterogeneity. Odds ratios were calculated for dichotomous variables. Results. We included two studies with a total of 25252 patients. The pooled effect size showed that metformin was inversely associated with a risk of asthma exacerbation (OR = 0.65, 95% CI 0.28–1.48; χ2 = 5.42, P=0.02; I2 = 82%), asthma-related emergency department visits (OR = 0.81, 95% CI 0.74–0.89; χ2 = 0.36, P=0.55; I2 = 0%), and hospitalizations (OR = 0.43, 95% CI 0.14–1.29; χ2 = 4.01, P=0.05; I2 = 75%). Conclusion. This meta-analysis suggested that metformin decreased the risk of asthma-related emergency room visits for patients with concurrent asthma and diabetes. Metformin reduced the risk of asthma-related hospitalization and exacerbation but was not statistically significant. More randomized trials involving larger samples should be considered, and the mechanisms of these effects need to be fully elucidated.
Study on the Multitarget Mechanism of Sanmiao Pill on Gouty Arthritis Based on Network Pharmacology
Authors: Qian Huiqin , Jin Qianqian , Liu Yichen , Wang Ning , Chu Yuru , Liu Bingbing , Liu Yan , Jiang Wanli , Song Yong
Published: August 2020

Sanmiao pill (SMP), a Chinese traditional formula, had been used to treat gouty arthritis (GA). However, the active compounds and underlying mechanism remained unclear. Hence, network pharmacology and molecular docking were utilized to explore bioactive compounds and potential mechanism of action of SMP in treating GA. In the study, the compounds of SMP, corresponding targets, and GA‐related targets were mined from various pharmacological databases. Then, herb‐compound‐target, compound‐target, PPI, and target‐pathway networks were constructed. Ultimately, molecular docking was carried out to verify the predicted results. The results indicated that 47 active compounds, 338 targets, and 144 disease targets were collected. Network analysis implied that Phellodendron chinense Schneid. played a vital role in the whole formula. Moreover, 7 compounds (quercetin, kaempferol, wogonin, rutaecarpine, baicalein, beta‐sitosterol, and stigmasterol) and 4 targets (NFKB1, RELA, MAPK1, and TNF) might be the kernel compounds and targets of SMP against GA. According to GOBP and KEGG pathway enrichment analysis and target‐pathway network, SMP might exert a therapeutic role in GA by regulating numerous biological processes and pathways, including lipopolysaccharide‐mediated signaling pathway, positive regulation of transcription, Toll‐like receptor signaling pathway, JAK‐STAT signaling pathway, NOD‐like receptor signaling pathway, and MAPK signaling pathway. The results of molecular docking showcased that 11 pairs of compound with targets had tight binding strength. Thereinto, 4 compounds of MAPK1 and 5 compounds of NFKB1 possessed a better combination, suggesting that MAPK1 and NFKB1 might be considered as therapeutic targets in treatment of GA. This study verified that SMP had synergistic effect on GA by multicomponents, multitargets, and multipathways.
Interplay Between V-ATPase G1 and Small EV-miRNAs Modulates ERK1/2 Activation in GBM Stem Cells and Nonneoplastic Milieu
Authors: Bertolini Irene , Storaci Alessandra Maria , Terrasi Andrea , Cristofori Andrea Di , Locatelli Marco , Caroli Manuela , Ferrero Stefano , Altieri Dario C. , Vaira Valentina
Published: August 2020

The ATP6V1G1 subunit (V1G1) of the vacuolar proton ATPase (V-ATPase) pump is crucial for glioma stem cells (GSC) maintenance and in vivo tumorigenicity. Moreover, V-ATPase reprograms the tumor microenvironment through acidification and release of extracellular vesicles (EV). Therefore, we investigated the role of V1G1 in GSC small EVs and their effects on primary brain cultures. To this end, small EVs were isolated from patients-derived GSCs grown as neurospheres (NS) with high (V1G1HIGH-NS) or low (V1G1LOW-NS) V1G1 expression and analyzed for V-ATPase subunits presence, miRNA contents, and cellular responses in recipient cultures. Our results show that NS-derived small EVs stimulate proliferation and motility of recipient cells, with small EV derived from V1G1HIGH-NS showing the most pronounced activity. This involved activation of ERK1/2 signaling, in a response reversed by V-ATPase inhibition in NS-producing small EV. The miRNA profile of V1G1HIGH-NS–derived small EVs differed significantly from that of V1G1LOW-NS, which included miRNAs predicted to target MAPK/ERK signaling. Mechanistically, forced expression of a MAPK-targeting pool of miRNAs in recipient cells suppressed MAPK/ERK pathway activation and blunted the prooncogenic effects of V1G1HIGH small EV. These findings propose that the GSC influences the brain milieu through a V1G1-coordinated EVs release of MAPK/ERK-targeting miRNAs. Interfering with V-ATPase activity could prevent ERK-dependent oncogenic reprogramming of the microenvironment, potentially hampering local GBM infiltration.

Implications:

Our data identify a novel molecular mechanism of gliomagenesis specific of the GBM stem cell niche, which coordinates a V-ATPase–dependent reprogramming of the brain microenvironment through the release of specialized EVs.
Platelet Inhibition and Anticoagulation in Visceral Interventions
Authors: Fischbach Wolfgang
Published: August 2020

Background: Platelet inhibition and anticoagulation are widely used therapeutic approaches in many patients. Despite their undoubted cardiovascular benefits, they may cause gastrointestinal harm either spontaneously or as part of endoscopic procedures. Strategies which harmonize both aspects are, therefore, of clinical interest. Method: The websites of the German (DGVS), European (ESGE), and American (ASGE) Societies of Gastroenterology and Endoscopy were searched for guidelines on antithrombotic agents and endoscopic procedures. Over and beyond this, PubMed was analyzed for originals and reviews by using the keywords “hemostasis affecting drugs,” “antithrombotic drugs,” “platelet inhibition,” “anticoagulation,” AND endoscopy. Conclusion: If elective endoscopy is planned, we should consider postponing the procedure in cases of temporally restricted platelet inhibition therapy or anticoagulation. Urgent endoscopy must balance the procedural risk against the risk of continuing or stopping the medication, with respect to thromboembolic events on the one hand and gastrointestinal bleeding on the other. There are decision criteria which facilitate individual risk stratification as a basis for diagnostic and therapeutic algorithms. Key Message: If endoscopic interventions under platelet inhibition and/or anticoagulation cannot be postponed for a limited period of time, diagnostic and therapeutic strategies have to be performed against the background of well-defined decision criteria. These include the procedural risk (low vs. high) and the risk of thromboembolic events occurring (low vs. high) if the medication is stopped. In cases where both risks are considered to be high, an interdisciplinary approach should be favored.
Rationale for Medium Cutoff Membranes in COVID-19 Patients Requiring Renal Replacement Therapy
Authors: Ronco Claudio , Reis Thiago , Cozzolino Mario
Published: August 2020

The current pandemic of coronavirus disease 2019 (COVID-19) spotlighted the vulnerability of patients with chronic kidney disease stage 5 on maintenance hemodialysis (HD) to the viral infection. Social distancing is the most effective preventive measure to reduce the risk of infection. Nonetheless, the necessity to frequently reach the dialysis center and the inherent social gathering both impede social distancing and also self-quarantine for infected individuals. A baseline hyperinflammatory state driven by factors such as the retention of uremic toxins afflicts these patients. Concomitantly, a condition of relative immunosuppression is also attributed to similar factors. The use of high-flux (HF) dialyzers for HD is the standard of care. However, with HF membranes, the removal of large middle molecules is scant. Medium cutoff (MCO) dialyzers are a new class of membranes that allow substantial removal of large middle molecules with negligible albumin losses. Recent trials confirmed long-term safety and long-term sustained reduction in the concentration of large uremic toxins with MCO dialyzers. Herein, we discuss the rationale for applying MCO membranes in COVID-19 patients and its possible immunoadjuvant effects that could mitigate the burden of COVID-19 infection in dialysis patients. We also discuss the direct cytopathic effect of the virus on renal tissue and extracorporeal blood purification techniques that can prevent kidney damage or reduce acute kidney injury progression.
SMC based DTC-SVM control of five-phase permanent magnet synchronous motor drive
Authors: Mehedi Fayçal , Taleb Rachid , Belhadj Djilali Abdelkadir , Yahdou Adil
Published: August 2020

This article presents an improved Direct Torque Control (DTC) technique with space vector modulation (SVM) for a five-phase permanent magnet synchronous motor (PMSM) using a sliding mode speed control (SMC).The proposed control scheme of the five-phase PMSM combines the advantages of SMC control and the SVM algorithm. The SMC method insensitive to uncertainties, in particular external disturbances and parameter variations. In this paper, the SMC controller is used to control the rotor speed of the five-phase PMSM based on DTC-SVM. The rotor speed response, torque and stator flux are determined and compared with traditional control method. The simulations results confirm the validity and effectiveness of the proposed control technique in terms of performance and robustness against machine parameter variations (inertia variation). The efficiency of the proposed method applied on the five-phase PMSM is verified by the MATLAB/Simulink.
Neutral expression synthesis using kernel active shape model
Authors: Peter Marcella , Minoi Jacey-Lynn , Ab Rahman Suriani
Published: August 2020

This paper presents a modified kernel-based Active Shape Model for neutralizing and synthesizing facial expressions. In recent decades, facial identity and emotional studies have gained interest from researchers, especially in the works of integrating human emotions and machine learning to improve the current lifestyle. It is known that facial expressions are often associated with face recognition systems with poor recognition rate. In this research, a method of a modified kernel-based active shape model based on statistical-based approach is introduced to synthesize neutral (neutralize) expressions from expressional faces, with the aim to improve the face recognition rate. An experimental study was conducted using 3D geometric facial datasets to evaluate the proposed modified method. The experimental results have shown a significant improvement on the recognition rates.
Factors influencing low intension detection rate in a non-invasive EEG-based brain computer interface system
Authors: Maswanganyi Clifford , Tu Chungling , Owolawi Pius , Du Shengzhi
Published: August 2020

Motor imagery (MI) responses extracted from the brain in the form of EEG signals have been widely utilized for intention detection in brain computer interface (BCI) systems. However, due to the non-linearity and the non-stationarity of EEG signals, BCI systems suffer from low MI prediction rate with both known and unknown influncing factors. This paper investigates the impact of visual stimulus, feature dimensions and artifacts on MI task detection rate, towards improving MI prediction rate. Three EEG datasets were utilized to facilitate the investigation. Three filters (band-pass, notch and common average reference) and the independent component analysis (ICA) were applied on each datasets, to eliminate the impact of artifact. Three sets of features where extracted from artifact free ICA components, from which more relevant features were selected. Moreover, the selected feature subsets were incorporated into three classifiers, NB, Regression Tree and K-NN to predict four MI and hybrid tasks. K-NN classifier outperformed the other two classifies in each dataset. The highest classification accuracy is obtained in hybrid task EEG dataset. Moreover, accurately predicted EEG classes were applied to a robotic arm control.
Filtering and analyzing normal and abnormal electromyogram signals
Authors: Elouaham S. , Dliou A. , Laaboubi Mostafa , Latif R. , Elkamoun N. , Zougagh H.
Published: August 2020

The electromyogram (EMG) is an important measurement to assess the health of muscles and the nerve cells that control them. The appearance of noise in electromyography (EMG) signals may unquestionably minimize the efficiency of the analysis of the signal. The denoising techniques are inevitable for minimizing noise affecting the EMG signals; these methods are Complete Ensemble Empirical Mode Decompositions with Adaptive Noise (CEEMDAN) and the Ensemble Empirical Mode Decomposition (EEMD). After that, we analyze these signals by time-frequency techniques as Adaptive Optimal Kernel (AOK) and Choi-Williams. Firstly, the obtained results illustrate the effectiveness of the CEEMDAN that permits reducing noise that interferes with normal and abnormal EMG signals with higher resolution than other techniques used as EEMD. Secondly, they show that the AOK technique is adapted to the detection and classification of these types of normal and abnormal EMG signals by the good localization of the Motor Unit Action Potentials (MUAPs) in the time-frequency plan. This paper shows the efficiency of the combination of the AOK and CEEMDAN techniques in analyzing the EMG signals. 
Real time FPGA implemnation of SAR radar reconstruction system based on adaptive OMP compressive sensing
Authors: Ashraf Eslam , A. M. Khalaf Ashraf , M. Hassan Sara
Published: August 2020

Synthetic Aperture Radar (SAR) is an imaging system based on the processing of radar echoes. The produced images have a huge amount of data which will be stored onboard or transmitted as a digital signal to the ground station via downlink to be processed. Therefore, some methods of compression on the raw images provides an attractive option for SAR systems design. One of these techniques which used for image reconstruction is the Orthogonal Matching Pursuit (OMP). OMP is an iterative algorithm which need high computational operations. The computational complexity of the iterative algorithms is high due to updating operations of the measurement vector and large number of iterations that are used to reconstruct the images successfully. This paper presents a new adaptive OMP algorithm to overcome this issue by using certain threshold. The new adaptive OMP algorithm is compared with the classical OMP algorithm using the Receiver Operating Characteristic (ROC) curves. The MATLAB simulations show that the new adaptive OMP algorithm improves the probability of detection at lower SNRs, reduce the computational operations as well as the number of required iterations. FPGA implementation of both the classical OMP and the adaptive OMP algorithm are also presented in this paper.
Performance evaluation of UE-controlled intelligent handover algorithm for natural disaster
Authors: Laily Yusof Azita , Eiza Azhar Ainnur , Ya’acob Norsuzila
Published: August 2020

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.
Spectrum handoff analysis for multiple secondary users in cognitive radio networks
Authors: Mahmud Shawkat Ban Bakhtyar , Jassim Al-Hindawi Asaad M. , Hatam Shadir Akram
Published: August 2020

The cognitive radio network permits secondary users to reach unused spectrum of primary users. In this paper, a mixed preemptive/non-preemptive resume priority M/G/1 queuing model is proposed for characterizing multiple handoff delay and to minimize the extended data delivery time of secondary users that has experienced multiple spectrum handoff during its transmission. The proposed queuing model supports delay-sensitive secondary user applications. The secondary users’ traffic is classified into two priority classes, the highest priority class for delay sensitive services and the lowest priority class for delay insensitive services. Furthermore, the proposed model assigns higher priority for the interrupted secondary users over uninterrupted secondary users for each class of secondary users in order to minimize the handoff delays for secondary users that experience multiple interruptions. Analytical formulas for the average extended data delivery time are derived for two different proactive spectrum handoff strategies (always stay and always change strategies) for both classes of secondary users. Simulation of proposed system model was performed to validate the analytical results and a good agreement was obtained. The performance of the suggested model is assessed and compared with other spectrum handoff models. Numerical results illustrate that the proposed system model outperforms existing models and can reduce the extended data delivery time for the secondary users.
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

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. 
Real-time object control system using open source platform
Authors: Cgseong Chang-Gyu , Kim Jung-Yee , Park Doo-Jin
Published: August 2020

Recently, the Internet of things(IoT) has received great attention, and the demand for IOT applications in various fields is increasing. But drawbacks of IoT, such as having to use dedicated equipment and having to pay for a flat fee monthly, do not satisfy the consumers’ demands. These shortcomings of IoT is causing the appearance of users who try to design the environment of IoT that responds their demands and naturally, attempts to have monitoring system through open-source hardware like Arduino. Open source hardware has attracted a great deal of attention for the diffusion of the Internet of things as a key element of the Internet construction. The emergence of open source hardware, which has the advantage of low cost and easy and fast development, has made it possible to embody the idea of object Internet application services. In this paper, we design and implement a system that controls the objects in real time using open source hardware and MQTT protocol.
Numerical simulation of DIC drying process on matlab distributed computing server
Authors: Saipan Saipol Hafizah Farhah , Alias Norma
Published: August 2020

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, this paper presents the development of mathematical models to detect, solve and visualize the three-dimensional (3D) heat and mass transfer in DIC drying process. 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.
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.
Optimal power scheduling for economic dispatch using moth flame optimizer
Authors: M. Kamari N. A. , A. Zulkifley M. , F. Ramli N. , Musirin I.
Published: August 2020

This paper proposes the optimal generator allocation to solve Economic Dispatch (ED) problem in power system using Moth Flame Optimizer (MFO). With this approach, the optimum power for each unit generating in the system will be searched based on the power constraints per unit and the amount of power demand. The objective function of this study is to minimize the total cost of generation. The amount of power loss is measured to determine the effectiveness of the proposed technique. The performance of the MFO technique is also compared to the evolutionary programming (EP) and Particle Swarm Optimization (PSO) methods. Five- and thirty-bus power system networks are selected as test systems and simulated using MATLAB. Based on simulation results, MFO provides better results in regulating the optimum power generation with minimum generation cost and power loss, compared to EP and PSO.
Measuring perceptions of students toward game and recreational activity using fuzzy conjoint analysis
Authors: Siryani Sofian Siti , Sham Rambely Azmin
Published: August 2020

The effectiveness of game and recreational activity (GaRA) can be determined from the application of fuzzy conjoint analysis (FCA). The analysis was used due to fuzziness in determining individual perceptions. This study involved a survey collected from 1494 students who participated in a Mathematics Discovery Camp organized by a UKM research group. The aim of this research is to determine the effectiveness of modules delivered to cultivate affection and confidence in Mathematics through different factors. There were 11 games conducted for the participants, and their perceptions based on the evaluation of six attributes were measured. A seven-point Likert scale method representing seven linguistic terms was used to collect students’ preferences to indicate their perceptions of each GaRA module. Scores of perceptions were transformed into degrees of similarity. Results found that interest, effort and team work were the strongest values obtained from GaRA as participants strongly agreed that these attributes fulfilled their preferences in most module. The evaluation using fuzzy conjoint model implicated the successfulness of a fuzzy approach to evaluate fuzziness obtained in the Likert-scale, and has shown its ability in ranking the attributes from most preferred to least preferred.
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

The latest advances and trends in information technology and communication have a vital role in healthcare industries. Theses advancements led to the Internet of Medical Things (IoMT) which provides a continuous, remote and real-time monitoring of patients. The IoMT 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 feasible 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. A case study of monitoring the vital signs of diabetic patients using real-time data processing and IoMT is also presented. 
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

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. 
An overview of traffic congestion detection and classification techniques in VANET
Authors: Idura Ramli Nurshahrily , Mohamed Rawi Mohd Izani
Published: August 2020

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. 
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.
 
Vehicle plate localization and extraction based on hough transform and bilinear operations
Authors: Abed Uthaib Masar , Sadik Croock Muayad
Published: August 2020

In general, the extraction of the vehicle plate is a previous step of plate recognition, and it actively studied for several decades. Plate localization is used in various security and traffic applications. In this paper, the proposed method is efficient to localize a plate for the multinational countries. The proposed method consists of three levels. The first level is the preprocessing that contains several steps. The digital camera capture images have been taken about twenty meters from the car with zooming two to three meters. Images are resampled using the zooming technique (bilinear interpolation) that makes the dimension of image (1024 x 768) pixels. The resampled images are resized to (940x 730). These images are converted to grayscale (green channel), and the bilateral filter is applied for removing noise. The second level is plate detection that adopts morphological operations, image subtraction, and vertical edge detection (Sobel). At the last Connected component analysis and Hough transform are used. The third level is the Deskew plate that notifies the plate may skew so that Hough transform is used to detect the largest line segment. Then, the images are rotated using bilinear interpolation. About 860 images are tested for different countries (Iraq, Belarus, Armenia, Hungary), and the accuracy is 98.99 % for extraction of the plate and 100% for the Deskew plate. Thus, the proposed system shows high efficiency in achievement.
The effect of optimizers in fingerprint classification model utilizing deep learning
Authors: F. Alkhalid Farah
Published: August 2020

Fingerprint is the most popular way to identify persons, it is assumed a unique identity, which enable us to return the record of specific person through his fingerprint, and could be useful in many applications; such as military applications, social applications, criminal applications… etc. In this paper, the study of a new model based deep learning is suggested. The focus is directed on how to enhance the training model with the increase of the testing accuracy by applying four scenarios and comparing among them. The effects of two dedicated optimizers are shown and their contrast enhancement is tested. The results prove that the testing accuracy is 85.61% for “Adadelta” optimizer, whereas for “Adam” optimizer, it is 91.73%.
Circuit-based grounding electrode considering frequency dependence for different input current
Authors: Othman Ruqayyah , Abdul-Malek Zulkurnain
Published: August 2020

This paper presents a simulation work of circuit-based grounding electrode considering frequency dependence of soil parameters for three input currents which are impulse, AC 50 Hz, and DC. The circuit parameters were determined by using Dwight and Sunde equations where a single horizontal grounding electrode was considered. Scott model was used for the frequency dependent model, to determine the frequency dependent soil resistivity and relative permittivity. It is found that the voltage response of the impulse current was highly affected (75.2%) by the frequency compared to the voltage response of AC 50 Hz and DC. The impulse current response also gave the lowest peak in the analysis by the influence of frequency which make it better compared to the two other inputs. Therefore, it can be concluded that the frequency dependent of soil parameters is crucial and need to be considered in the transient analysis for any kind of input current to obtain accurate results.
Reduction cost and energy consumption for LED smart lighting street technology in Iraq
Authors: K. Mohammed Jabbar
Published: August 2020

The idea of replacing the old lighting system with energy-efficient ones has been given excessive attention, particularly in the territorial and Arabic world. This move is significant for its helpful effects on both the economy and the environment, especially in Iraq which smarts from light-related problems. It correspondingly aids the light distribution offices as it will save them from several light generation troubles and their effects on the hours of electrical power supply. The light consumers will also benefit from reduced bills due to approximately 50% reduction in power consumption by the energy-efficient system. The energy-efficient lighting system has replaced the traditional technical lighting owing to its energy saving capability and environmental friendliness. These problems would enhance the use of efficient energy programmer to reduce energy consumption as the world switches to the use of renewable energy. This study presents the use of modernized lighting system with an emphasis on its economic and environmental benefits. The results are applied by MATLAB version17b prototypical is built to evaluate the behavior of smart lighting street technology and renewable energy to reduce cost and energy consumption. During the study, 100 modernized LED electric lamps of 150W capacity were used to replace 100 High Pressure Sodium (HPS) lamps of 400W. The economic cost of the replacement was calculated based on the price of the LED lamps compared to those of the HPS lamps. The environmental impact was determined by calculating the global cost of the electrical energy consumed by the LED lamps compared to those consumed by the HPS lamps in Iraq.
Implementation of space vector modulation for two level Three-phase inverter using dSPACE DS1104
Authors: Bouyakoub Ismail , Taleb Rachid , Mellah Hacene , Zerglaine Abdelaziz
Published: August 2020

With increasing research and advancement in solid-state power electronic devices and microprocessors, various inverter control techniques employing Pulse Width Modulation (PWM) are becoming popular especially in AC motor drive applications. The most commonly used techniques are Sinusoidal PWM (SPWM) and Space Vector modulation PWM (SVPWM). SVPWM is considered to be superior to the SPWM because of better DC bus utilization. In this paper, a real-time digital implementation of SVPWM algorithm for three-phase two level inverter using dSPACE DS1104. The results obtained from the experimentation are closer to that of simulation, which confirms the validity of the implemented algorithm.
Capacitance-based microfluidic device for early ammonia detection in river water
Authors: Bin Ramli Muhammad Muhaimin , Bin Ahmad Mohd Ridzuan
Published: August 2020

This paper proposes a design of a microfluidic device for early detection of ammonia in river water based on capacitance measurement. A microfluidic device is designed and simulated to measure the content of ammonia in river water by using the COMSOL finite element analysis (FEA) software. This paper describes the system in detail from the conceptual idea to the hardware implementation. The microfluidic device works by inserting the sample of water into the device to be tested. A pair of electrodes is connected to the electrical circuit and the value of the capacitance of the water sample is measured. The tested samples are normal river water and contaminated river water which have ammonia in it. Several investigations have been done via the simulation, i.e. the size of the electrode, the difference in water flow gap, the distance between the electrode, speed of the water and the capacitance of the water. The results show that the proposed microfluidic design is capable to detect ammonia inside river water under 2 ppm concentration.