bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive Factors of Positive Circumferential and Longitudinal Margins in Early T3 Colorectal Cancer Resection
Authors: Balbaa M. Ashraf , Elkady Noha , Abdelrahman Emad M.
Published: June 2020

Background. Malignant involvement of circumferential resection margin (CRM) and longitudinal resection margin (LRM) after surgical resection of colorectal cancer (CRC) are associated with higher rates of recurrence and development of distant metastasis. This can influence the overall patient’s prognosis. The aim of the current study was to identify pathological factors as predictors for the involvement of resection margins in early T3 CRC.Patients and Methods.Fifty patients radiologically diagnosed to have cT3a/b (CRC) were included in the study. After resection, the pathological examination was performed to identify patients with positive CRM and/or LRM. Relations between the different pathological parameters and the CMR and LRM involvements were assessed.Results. Positive CRM was present in 17 cases (34%), while positive LRM was found in 6 cases (12%). The involvement of both margins was significantly associated with rectal tumors and tumors with infiltrative gross appearance, grade III, deeper invasion, and positive lymph node metastases. Also, there was a significant association between both margins’ positivity and other pathological parameters as signet ring carcinoma, tumor budding, perineural and vascular invasion, high microvessel density (MVD), and sinusoidal vascular pattern, while the presence of necrosis and infiltrative advancing tumor front was significantly associated with CRM involvement only. The depth of tumor invasion and signet ring carcinoma were identified as independent predictor factors for positive CRM and LRM, respectively.Conclusion. Preoperative identification of these pathological parameters can be a guide to tailor the management plan accordingly.
Peripheral Medulloepithelioma: A Rare Entity to Know
Authors: Matrane W. , Cherkaoui S. , Regragui M. , Bennani Guebessi N. , Karkouri M. , Salam S. , Madani A. , Quessar A. , Khoubila N.
Published: June 2020

According to the World Health Organization, medulloepithelioma belongs to the embryonal neoplasm entity. It is a very rare, highly malignant tumor typically affecting infants and young children. Usually, the tumor arises in the eye or in the central nervous system; a peripheral location has been rarely reported without an established treatment. The recognition and separation of this neoplasm from other differential tumors are mandatory for better understanding of its biology and determination of optimal treatment. This paper reports a case of an ectopic intrapelvic medulloepithelioma with liver metastasis in a 3-year-old girl.
Stochastic Risk Assessment with a Lagrangian Solution for the Optimal Cost Allocation in High-Speed Rail Networks
Authors: Zuo Jing , Dang Jianwu , Lyu Min
Published: June 2020

In large-scale high-speed rail networks (HSRNs), the occurrence of occasional malfunctions or accidents is unavoidable. The key issue considered in this study is the optimal allocation of the maintenance costs, based on the stochastic risk assessment for HSRNs. Inspired by the theoretical risk evaluation methods in the complex network, three major factors, including the local effects, global effects, and component self-effects are considered in the process of assessing the impact on the network components (nodes or lines). By introducing the component failure occurrence probability, which is considered to be an exponential function changing with the component maintenance costs, a feasible stochastic risk assessment model of the HSRNs together with the component impact assessment is proposed that can better unify the impact assessment of both the high-speed rail stations and railways. An optimal allocation algorithm based on a Lagrangian relaxation approach is designed. Correspondingly, the optimal cost allocation scheme can be determined using the algorithm to eliminate the various HSRN risks under the given costs. Furthermore, a real-world case study of the HSRNs in eastern China is illustrated. Compared with the genetic algorithm, the simulation shows that the approach can solve the optimal cost allocation problem to more effectively reduce the risks of large-scale HSRNs in practice.
Identification of Key Genes of Human Advanced Diabetic Nephropathy Independent of Proteinuria by Transcriptome Analysis
Authors: Cai Fanghao , Zhou Xujie , Jia Yan , Yao Weijian , Lv Jicheng , Liu Gang , Yang Li
Published: June 2020

Background. Diabetic nephropathy (DN) is the leading cause of ESRD. Emerging evidence indicated that proteinuria may not be the determinant of renal survival in DN. The aim of the current study was to provide molecular signatures apart from proteinuria in DN by an integrative bioinformatics approach. Method. Affymetrix microarray datasets from microdissected glomerular and tubulointerstitial compartments of DN, healthy controls, and proteinuric disease controls including minimal change disease and membranous nephropathy were extracted from open‐access database. Differentially expressed genes (DEGs) in DN versus both healthy and proteinuric controls were identified by limma package, and further defined by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Hub genes were checked by protein‐protein interaction networks. Results. A total of 566 glomerular and 581 tubulointerstitial DEGs were identified in DN, which were commonly differentially expressed compared to normal controls and proteinuric disease controls. The upregulated DEGs in both compartments were significantly enriched in GO biological process associated with fibrosis, inflammation, and platelet dysfunction, and largely located in extracellular space, including matrix and extracellular vesicles. Pathway analysis highlighted immune system regulation. Hub genes of the upregulated DEGs negatively correlated with estimated glomerular filtration rate (eGFR). While the downregulated DEGs and their hub genes in tubulointerstitium were enriched in pathways associated with lipid metabolism and oxidation, which positively correlated with eGFR. Conclusions. Our study identified pathways including fibrosis, inflammation, lipid metabolism, and oxidative stress contributing to the progression of DN independent of proteinuria. These genes may serve as biomarkers and therapeutic targets.
Fracturing and Porosity Channeling in Fluid Overpressure Zones in the Shallow Earth’s Crust
Authors: Koehn Daniel , Piazolo Sandra , Sachau Till , Toussaint Renaud
Published: June 2020

At the time of energy transition, it is important to be able to predict the effects of fluid overpressures in different geological scenarios as these can lead to the development of hydrofractures and dilating high-porosity zones. In order to develop an understanding of the complexity of the resulting effective stress fields, fracture and failure patterns, and potential fluid drainage, we study the process with a dynamic hydromechanical numerical model. The model simulates the evolution of fluid pressure buildup, fracturing, and the dynamic interaction between solid and fluid. Three different scenarios are explored: fluid pressure buildup in a sedimentary basin, in a vertical zone, and in a horizontal layer that may be partly offset by a fault. Our results show that the geometry of the area where fluid pressure is successively increased has a first-order control on the developing pattern of porosity changes, on fracturing, and on the absolute fluid pressures that sustained without failure. If the fluid overpressure develops in the whole model, the effective differential and mean stress approach zero and the vertical and horizontal effective principal stresses flip in orientation. The resulting fractures develop under high lithostatic fluid overpressure and are aligned semihorizontally, and consequently, a hydraulic breccia forms. If the area of high fluid pressure buildup is confined in a vertical zone, the effective mean stress decreases while the differential stress remains almost constant and failure takes place in extensional and shear modes at a much lower fluid overpressure. A horizontal fluid pressurized layer that is offset shows a complex system of effective stress evolution with the layer fracturing initially at the location of the offset followed by hydraulic breccia development within the layer. All simulations show a phase transition in the porosity where an initially random porosity reduces its symmetry and forms a static porosity wave with an internal dilating zone and the presence of dynamic porosity channels within this zone. Our results show that patterns of fractures, hence fluid release, that form due to high fluid overpressures can only be successfully predicted if the geometry of the geological system is known, including the fluid overpressure source and the position of seals and faults that offset source layers and seals.
Overexpression of lncRNA SNGH3 Predicts Unfavorable Prognosis and Clinical Outcomes in Human Cancers: Evidence from a Meta‐Analysis
Authors: Jiang Yaofei , Le Lulu
Published: June 2020

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in human disease, especially in tumor development and progression. Small nucleolar RNA host gene (SNHG3), a newly identified lncRNA, has been found dysregulated in various cancers. Nevertheless, the results remain controversial. Thus, we aim to analyze the comprehensive data to elaborate the association between SNHG3 expression and clinical outcomes in multiple cancers. We searched PubMed, Web of Science, Cochrane Library, Embase, and MEDLINE database to identify eligible articles. STATA software was applied to calculate the hazard ratio (HR) and odds ratio (OR) with 95% confidence interval (95% CI) for survival outcomes and clinical parameters, respectively. Besides, the data from The Cancer Genome Atlas (TCGA) dataset was extracted to verify the results in our meta‐analysis. There were thirteen studies totaling 919 cancer patients involved in this meta‐analysis. The results demonstrated that high SNHG3 expression was significantly associated with poor overall survival (OS) (HR = 2.53, 95% CI: 1.94‐3.31) in cancers, disease‐free survival (DFS) (HR = 3.89, 95% CI: 1.34‐11.3), and recurrence‐free survival (RFS) (HR = 2.42, 95% CI: 1.14‐5.15) in hepatocellular carcinoma. Analysis stratified by analysis method, sample size, follow‐up time, and cancer type further verified the prognostic value of SNHG3. Additionally, patients with high SNHG3 expression tended to have more advanced clinical stage, higher histological grade, earlier distant metastasis, and earlier lymph node metastasis. Excavation of TCGA dataset valuated that SNHG3 was upregulated in various cancers and predicted worse OS and DFS. Overexpressed SNHG3 was strongly associated with poor survival and clinical outcomes in human cancers and therefore can serve as a promising biomarker for predicting patients’ prognosis.
A Heterogeneous Image Fusion Method Based on DCT and Anisotropic Diffusion for UAVs in Future 5G IoT Scenarios
Authors: Hao Shuai , An Beiyi , Wen Hu , Ma Xu , Yu Keping
Published: June 2020

Unmanned aerial vehicles, with their inherent fine attributes, such as flexibility, mobility, and autonomy, play an increasingly important role in the Internet of Things (IoT). Airborne infrared and visible image fusion, which constitutes an important data basis for the perception layer of IoT, has been widely used in various fields such as electric power inspection, military reconnaissance, emergency rescue, and traffic management. However, traditional infrared and visible image fusion methods suffer from weak detail resolution. In order to better preserve useful information from source images and produce a more informative image for human observation or unmanned aerial vehicle vision tasks, a novel fusion method based on discrete cosine transform (DCT) and anisotropic diffusion is proposed. First, the infrared and visible images are denoised by using DCT. Second, anisotropic diffusion is applied to the denoised infrared and visible images to obtain the detail and base layers. Third, the base layers are fused by using weighted averaging, and the detail layers are fused by using the Karhunen–Loeve transform, respectively. Finally, the fused image is reconstructed through the linear superposition of the base layer and detail layer. Compared with six other typical fusion methods, the proposed approach shows better fusion performance in both objective and subjective evaluations.
Canine Leishmaniosis Control through the Promotion of Preventive Measures Appropriately Adopted by Citizens
Authors: Simonato Giulia , Marchiori Erica , Marcer Federica , Ravagnan Silvia , Danesi Patrizia , Montarsi Fabrizio , Bononi Carlo , Capelli Gioia , Pietrobelli Mario , Cassini Rudi
Published: June 2020

Canine leishmaniosis (CanL) is a disease caused by the protist Leishmania infantum and transmitted to dogs by sand fly (Diptera: Phlebotominae) bites. In 2005, a new autochthonous focus of CanL was recognised in the southern part of Euganei hills (northeastern Italy). In subsequent years, this outbreak was monitored, testing dogs and evaluating sand fly population. Moreover, dog owners were sensitized on the adoption of preventive measures, thanks to the collaboration of local administration, health authorities, and private veterinarians. This study includes serological tests on dogs, questionnaires submitted to dog owners regarding the use of preventive measures on their animals, and the evaluation of sand fly abundance. Data collected were statistically compared with those of previous years. The canine seroprevalence was significantly lower than that recorded at the beginning of the outbreak, despite the fact that sand fly abundance did not significantly decrease. In addition, most of the dog owners declared using regularly the topical insecticides on their dogs during the sand fly season. This experience demonstrated that a collaborative approach among scientific researchers, local authorities, and private veterinarians can achieve excellent results in the management of a leishmaniosis outbreak.
A Case of Gastric Intramural Hematoma Caused by Anisakis Infection
Authors: Lee Sang Jin
Published: June 2020

A sixty-year-old lady admitted complaining of epigastric pain and hematemesis. On admission, esophagogastroduodenoscopic examination revealed ruptured intramural hematoma on the antrum of stomach. Eight days later, follow-up EGD showed improving ruptured intramural hematoma and one anisakis larva. Therefore, the gastric intramural hematoma was considered to be caused by anisakis infection. She recovered after ten days of conservative treatment.
Screening of Abdominal Aortic Aneurysm Using Portable Transthoracic Echocardiography among Patients with Acute Coronary Syndrome
Authors: Shukha Yousef , Koren Ofir , Or Tsafrir , Turgeman Yoav , Mahamid Mahmud , Jabaren Mohamed
Published: June 2020

Background. Abdominal aortic aneurysm (AAA) and acute coronary syndrome (ACS) share common risk factors. Objectives. To assess the abdominal aortic diameter (AAD) among patients with ACS using transthoracic echocardiography (TTE). Methods. Patients with ACS admitted to our intensive cardiac care unit from December 2013 to June 2014 were screened prospectively for AAA via AAD measurement in the subcostal TTE view. AAA was defined as an aneurysm with a transverse diameter of ≥30 mm. Results. Sixty seven patients were included. The male-to-female sex ratio was 7 : 1. The vast majority of patients were admitted due to STEMI (73%), and the rest were equally divided as NSTEMI and unstable angina. The mean patient age was 58.4 ± 10.4 years. AAD measurements were feasible in 57 patients (85%); among them, AAA was diagnosed in six patients (10.5%). The average additional time required to measure the abdominal aorta was 4 ± 1 min. All patients with AAA were men and had a higher prevalence of smoking (83.3% vs. 60.6%, p<0.003) and a lower incidence of diabetes mellitus than those without aneurysm. The prevalence of AAA tended to be related to age (12.5% in those older than 60 years and 18.7% in those older than 65 years). Conclusions. The overall prevalence of AAA is significantly high among patients with ACS and increases with age. AAA screening as a part of routine cardiac TTE can be easily, rapidly, and feasibly performed and yield accurate findings. AAD measurement in the subcostal view should be implemented as a part of routine TTE in patients with ACS.
Genomic Analysis of the SUMO-Conjugating Enzyme and Genes under Abiotic Stress in Potato (Solanum tuberosum L.)
Authors: Ghimire Shantwana , Tang Xun , Zhang Ning , Liu Weigang , Qi Xuehong , Fu Xue , Si Huaijun
Published: June 2020

SUMO-conjugating enzymes (SCE) and SUMO (Small Ubiquitin-Like Modifiers) genes are important components of SUMOylation. SCE has a crucial role during the SUMOylation process which acts as a catalyst to transfer SUMO to the target protein. Comprehensive studies on SCE and SUMO have been performed in some plants, but studies on these genes remain limited in potato. This study is aimed at exploring the role of StSCE and StSUMO genes in abiotic stress conditions. Nine and seven putative StSCEs and StSUMO genes, respectively, were identified using different methods and databases available for potato. Chromosomal localization showed that SCE and StSUMO genes are unevenly distributed on 7 different chromosomes. Potato genome database was accessed for the expression profile of StSCE and StSUMO genes, and these genes were differentially expressed in different tissues and organs during different phases of plant growth. The expression patterns on different treatments were further evaluated using qRT-PCR for all the StSCE and StSUMO genes. The expression was upregulated in StSCE1/5/6 and 7 under salt and PEG treatment. StSUMO 1/2 and 4 were upregulated under salt stress whereas StSCE9 and StSUMO2 and 4 were observed downregulated under PEG treatment. The results of this study could be useful to explore the role of StSCE genes in potato improvement.
Transient, Recurrent Central Nervous System Clinical Manifestations of X-Linked Charcot-Marie-Tooth Disease Presenting with Very Long Latency Periods between Episodes: Is Prolonged Sun Exposure a Provoking Factor?
Authors: Tziakouri Andria , Natsiopoulos Konstantinos , Kleopa Kleopas A. , Michaelides Costas
Published: June 2020

Charcot-Marie-Tooth disease is one of the most common inherited neurological disorders affecting the peripheral nervous system. The common clinical manifestations of the disease are distal muscle weakness and atrophy, often associated with a characteristic steppage gait and foot deformities. Transient acute and recurrent or chronic central nervous system manifestations, predominantly, dysarthria, dysphagia, motor weakness, and ataxia, have been recognized as a feature of the X-linked type 1 of CMT (CMTX1). The CNS symptoms occur typically in young age and often precede the clinical manifestation of the polyneuropathy. Several predisposing factors such as exercise, fever, and returning from areas of high altitude have been described as triggers of the CNS symptoms; however, in many cases, a substantial cause remains undetermined. In this report, we describe a patient with three attacks of transient CNS deficits at the ages of 11, 21, and 38 years, respectively, which were also accompanied by transient white matter abnormalities on MRI. Two of the attacks occurred after prolonged exposure to sunlight. In our knowledge, this is the first documented case with such long latency periods between CNS attacks as well as the only report describing intense sun exposure as a possible provoking factor.
Grid search of exponential smoothing method: a case study of Ho Chi Minh City load demand
Authors: Tran Ngoc Thanh , Van Dai Le
Published: June 2020

The exponential smoothing method is one of the widely used methods for load forecasting. The taxonomy of exponential smoothing method shows that its trend and seasonal component affect the results of exponential smoothing method. This paper proposed a framework for grid search with the optimal model of exponential smoothing method based on math formulas. The training process will specify the optimal models which satisfy requirement of minimum of akaike information criterion, accuracy scores of the root mean square error, mean absolute percentage error, and mean absolute error. The testing process will evaluate the accuracy scores between the optimal models and all other ones. The results indicated that the optimal models have accuracy scores near the minimum values. The load demand data collected in Ho Chi Minh City were used to verify the accuracy and reliability of the grid search framework.
An automatic multi-axis solar tracking system in Ramadi city: design and implementation
Authors: AL-Jumaili Mustafa Hamid , Haglan Hussein M , Mohammed Mohammed K , Eesee Qusay H
Published: June 2020

In this paper, a complete design and implementation of an automatic Multi-Axis solar tracking system has been introduced. The main purpose of this system is to track Sun location and gain the maximum energy output of the solar panels. The system is Multi-axis using microcontroller and photocells to control the direction of the penal, whereas the penal is facing the sun at all times of the day. The system is a combination of hardware and software parts that work concurrently to achieve a precise angular Sun tracking. A Base, Penal Frame, Super Jack Motors, high-efficiency Solar Panel, Arduino Uno microcontroller, Relays, Rechargeable battery, Light Dependent Resistor (LDR) have been used for the system’s hardware part. These hardware parts need a high-level programming code, as a software part, to be embedded in the microcontroller to get an effective and precise solar tracking system. The results of the presented system were compared to a fixed direction system. The results show significant efficiency improvement of 24% over the static one. For a city like Ramadi, which has a high irradiance all over the year, it is very fruitful to use such tracking systems along with photovoltaic installation systems.
 
A distributed trust mechanism for malicious behaviors in VANETs
Authors: Kamil Ahmed Ali , Najm Abdulwahed Mohanad , Farzaneh Behnam
Published: June 2020

Vehicular Ad-hoc Networks (VANETs) are one of the most important types of networks which are widely used in recent years. Along with all the benefits of Quality of Service (QoS) improvements, vulnerability analysis for this type of networks is an important issue. For instance, a Gray-hole attack decreases network performance. We proposed a novel solution to help to secure these networks against this vulnerability. The proposed method can detect and prevent the Gray-hole attack. Anywhere in the network, each node (vehicle) can distinguish between the Gray-hole attack and the failed link. Some topology related information helps us to detect attacks more accurately. Also, the proposed method uses the most reliable path in terms of link failure when there is no malicious node. In this paper, we used the TOPSIS method for choosing the most trusted node for routing intelligently. We validated our proposal using a simulation model in the NS-2 simulator. Simulation results show that the proposed method can prevent Gray-hole attack efficiently with low overhead.
Coaxial treatment chamber for liquid food treatment through pulsed electric field
Authors: Arshad Rai Naveed , Malek Zulkurnain Abdul , Ahmad Mohd. Hafizi , Buntat Zolkafle , Kumara C L G Pavan , Abdulameer Asaad Zuhair
Published: June 2020

Over the last couple of decades, pulsed electric field (PEF) attained substantial consideration in the food industry with an effort to generate replacements to conventional thermal treatment. It is recognised to produce secure and chill-stable liquid food samples with fresh and nutritional qualities. The uniform electric field in the treatment zone has been recognised as the main handling parameter. The design of the treatment chamber shows an essential impact on the effectiveness of the procedure by controlling homogenous treatment. This study revealed the homogeneity of the electric field strength of the different existing treatment chambers through COMSOL Multiphysics. It adopted a study to design a co-axial treatment chamber for continuous treatment of liquid samples. This research helps to take some fundamental designing steps for a new treatment chamber with a uniform distribution of the electric field.
A self-rectifying memristor model for simulation and ReRAM applications
Authors: Sabah Sinan , Sulaiman Nasri Bin
Published: June 2020

In this paper, a self-rectifying memristor (SRM) model is proposed for memristive circuit simulations. This model is based on the behavior of voltage controlled, bipolar memristors that exhibit diode-like rectification behavior when reverse biased. Such unique feature can solve the sneak path problem in crossbar memristive memory structures without requiring additional cell selectors. The results show that the proposed model satisfies the basic memristor’s i-v characteristics and fits many different memristor devices adequately. The proposed model is implemented in Verilog-A so that it is conveniently incorporated into various memristor applications with different circuit simulators
Design of a contactless body temperature measurement system using Arduino
Authors: Rahimoon Asif A. , Abdullah Mohd Noor , Taib Ishkrizat
Published: June 2020

The recent advances in electronics and microelectronics devices allow the development of newly low-cost monitoring tools used by peoples for health preventive purposes. Sensors used in medical equipments convert various forms of human body vital signs into electrical signals. Therefore, the healthcare monitoring systems considering non-invasive and wearable sensors with integrated communication mediums allow an efficient solution to live a comfortable home life.  This paper presents the remote monitoring of human body temperature (HBT) wirelessly by means of Arduino controller with different sensors and open source internet connection. The proposed monitoring system uses an internet network via wireless fieldity (wifi) connection to be linked with online portal on smart phone or computer. The proposed system is comprised of an Arduino controller, LM-35 (S1), MLX-90614 (S2) temperature sensors and ESP-wifi shield module. The obtained result has shown that real time temperature monitoring data can be transferred to authentic observer by utilizing internet of things (IoT) applications. The findings from this research indicates that the difference of average temperature in between Sensor S1 and S2 is about 15 0C
Mitigation of overvoltage due to high penetration of solar photovoltaics using smart inverters volt/var control
Authors: Almeida Dilini , Pasupuleti Jagadeesh , Ekanayake Janaka , Karunarathne Eshan
Published: June 2020

The modern photovoltaic (PV) inverters are embedded with smart control capabilities such as Volt/Var and Volt/Watt functions to mitigate overvoltage issues. The Volt/Var control has gained a significant attention in regulating grid voltage through reactive power compensation. However, the reactive power capability of a PV inverter is limited during peak irradiance and could be improved by curtailing the active power generation and by oversizing the PV inverter. This paper analyzes the performance of Volt/Var function of smart PV inverters in mitigating overvoltage issues due to high PV integration and thus increasing the hosting capacity of low voltage distribution networks (LVDNs). The study is conducted on a real Malaysian LVDN considering two different Volt/Var set points under different PV penetration levels. Results demonstrate that the oversized smart PV inverter could enhance the Volt/Var functionality by increasing its reactive power capability than a typical smart PV inverter. Further it reveals that adaptation of sensitive Volt/Var set points with shorter deadbands increase the PV hosting capacity of LVDNs.
A chaos-based medical image encryption method
Authors: Wang Xuehong , Tu Chunling
Published: June 2020

The information in the e-health system involves the patient’s privacy which is extremely sensitive. For instance, these information record social security numbers and detailed medical history.  When the breach happens, there are illegal, or disclosure behaviors taken to privacy that should be compromised security. In this paper, the medical digital images are protected by the proposed chaos-based encryption method in the process of transmission and utilization. Then the authentication is granted to patients and telemedicine staffs by the decryption method proposed. The Qi 3-D four wing chaotic system is employed in this method. The proposed method promises the keys with higher complexity and unpredictability than traditional cryptography methods by introducing the chaotic dynamics in the new cryptography. Digital medical images are used to validate the proposed method under the brute and the differential attacks. The pixels of the image are scrambled completely based on cat map and the sub-blocks of the image are diffused in the way that the original image is changed into a chaotic image robust to all kinds of attacks. The experiments show that the proposed method has higher performance and higher computation for decryption.
Comparative Analysis of Sokal’s Equations versus Load-Pull Implementation of Class E Low-Pass Network
Authors: Kirish Boodhoo , Zubir Farid , A. Rahim Mohamad Kamal , Mohd Shah Shaharil
Published: June 2020

In this paper, Class E power amplifiers (PA) aimed at frequency bandwidth of 3.4 GHz to 3.6 GHz (LTE 42) and 3.6 GHz to 3.8 GHz (LTE 43) respectively are designed with objective of attaining high efficiency. The viability of Sokal’s equations for present communication systems aimed at GHz are analyzed for high efficiency using HEMT (High-electron-mobility transistor) on Nitronex NPTB00004 as opposed to the Bipolar Junction Transistor used by Sokal in 1975. Load-pull configuration techniques aimed at the drain is implemented at the output matching network (OMN) and benchmarked against Sokal’s equation. At the OMN, to suppress harmonics, band-pass filters are employed for the LTE 42 and 43 respectively. Sokal’s equation shows that the drain must be conjugately matched before his equations are applied at the OMN. The efficiency at 3.4 GHz obtained for Sokal’s circuit is at 67 % and gain of 9.3 dB. More than 65% efficiency is obtained from load-pull network at 3.4 GHz to 3.76 GHz before filter implementation while showing gain above 7.8 dB. After filter addition at OMN, the efficiency is above 65% and gain above 8 dB for dual - band having bandwidth of 3.4389 GHz - 3.542GHz and 3.6569GHz - 3.8GHz.
Implementation of DSSS system of image using MATLAB
Authors: Mohammed Samir Jasim , Kaittan Kadhim Hassan
Published: June 2020

In direct sequence spread spectrum systems, pseudo sequence random (PN) are used to spreading data bits. There are various type of PN sequences are available with good correlation properties, on mostly are generating pn by linear feedback shift register (LFSR). Will examine in this paper we describe spreading binary random and spreading the image As well as studying probability bit error rate of DSSS system with change of the channel (Add white Gaussian noise channel, Rayleigh fading channel, Rician fading channel). Our study will be performed using MATLAB. Terms of completed my articles in building system developed to security transmitter and receiver the information of theft against communication digital system talk as well as the increase of data rate information. Was this design a way process of his used in applications military and have a major role also in the most applications requiring protect high for many information binary data and image. So that the system designed as fits practice and prevent the overlap the outside after it has become send signals in communication system exhibition penetration and Intentional attacks or other breaches.
IoT blood pressure monitoring system
Authors: Hashim Norlezah , Norddin Nurbahirah , Idris Fakrulradzi , Mohd Yusoff Siti Nur Ilmani , Zahari Madiha
Published: June 2020

The number of patients in hospital keep increasing every year and, some patients’s blood pressure must be measured by medical staff regularly. This means that the medical staff need to attend to the patient routinely and several readings are required in each session to make sure the results are accurate. Therefore, there is a need to simplify the monitoring process inside hospital in Malaysia. In this work, IoT Blood Pressure Monitoring System (IBPMS) is designed to monitor patient’s blood pressure remotely. This project use Raspberry Pi as a gateway to view the value of blood pressure online. Result showed that the design is capable to transfer data from blood pressure detector through the network using USB TTL serial cable which is directly attached to the Raspberry Pi. User can also view the blood pressure reading continuously from Telegram application and email service. Furthermore, the system can measure the value of blood pressure accurately when user is in sitting position.
Performance evaluation of a single mode optical fiber tip sensor for glucose detection
Authors: Mohd Razali Nazirah , Said Ja'afar Puteri Nadiah Syamimi , Ambran Sumiaty
Published: June 2020

Glucose must be carefully regulated to ensure its safety and quality. Nowadays, chemists often face difficulty to measure glucose concentrations as the current methods for the analysis are expensive and require complex procedures which have reduced the interest among chemists to use these techniques. This study evaluated the performance of a single mode optical fiber tip sensor for glucose detection. The sensing mechanism mainly depends on the Fresnel’s reflection that occurs at the flat fiber tip region while the sensor performance was evaluated based on its sensitivity and linearity. The sensor was tested in glucose solution at different concentration range; high range (0% - 14%), medium range (0% - 1.4%) and low range (0% - 0.14%). The sensor showed a good performance when sensing the glucose solution at high and medium concentration range with strong linearity of more than 90% and an average sensitivity of 0.0979 dBm/% and 0.1019 dBm/%, respectively. However, the low concentration range showed no significant changes during sensing. Based on the findings obtained in this study, the optical fiber tip sensor has the potential to be utilized for glucose detection and suitable for high and medium concentration range measurement.
Dynamic spectrum access using markov chain technique for regional area network
Authors: Pawar Jayant P , V. Ingole Prashant
Published: June 2020

Cognitive Radio Network is the effective solution to the spectrum scarcity.  Dynamic spectrum access is a paradigm used to access the spectrum dynamically. A Markov Chain is a stochastic model describing a sequence of possible events in which probability of each event depends only on the state attained in the previous event. We model the dynamics of cognitive user with 2-D Markov chain. The resource distribution probability (RDP) verses addition/ elimination rate of the channels in the network is also plotted. The RDP verses utilization factor of the queue, which is the secondary user in the network, is also plotted. This plot helps to maintain the total arrival and departure rate based on the RDP. The base station of the network will use this relation to maintain the proper RDP for the devices. The dynamics of each cognitive user and its correlation with Markov Chain is an interesting approach. Here we considered the DSA at Base Station as a Markov chain and analyzed it. This analysis helps us to determine the behavior of the cognitive radio and also helps to find the fault in the cognitive devices. 
Design and implementation of fast floating point units for FPGAs
Authors: Hassan Mohammed Falih , Hussein Karime Farhood , Al-Musawi Bahaa
Published: June 2020

Due to growth in demand for high-performance applications that require high numerical stability and accuracy, the need for floating-point FPGA has been increased. In this work, an open-source and efficient floating-point unit is implemented on a standard Xilinx Sparton-6 FPGA platform. The proposed design is described in a hierarchal way starting from functional block descriptions toward modules level design. Our implementation used minimal resources available on the targeting FPGA board, tested on Sparton-6 FPGA platform and verified on ModelSim. The open-source framework can be embedded or customized for low-cost FPGA devices that do not offer floating-point units.
Interaction between updated FR-CG algorithms with optimal Cuckoo algorithm
Authors: Alkawaz Rana Z. , AlBayati Abbas Y. , Jameel Marwan S.
Published: June 2020

In this article we have derived two versions, ξk and ρk were derived from an algorithm based on the first suggested modified Fletcher-Reeves method in the article for the two-term CG method and another term to get a downward search towards the function minimum point with the search for an inaccurate line and we have proved rapprochement. These two algorithms combined with the Cuckoo algorithm to achieve a remarkable performance in reducing the number of repetitions in order to reach the minimization of 10 functions is unconstrained in the numerical results.

 
Gender stereotype and hostile sexism among young korean gamers based on teammate selection strategy and game style preferences
Authors: Song Doo Heon , Rhee Hae Kyung , Kim Jeong Hoon
Published: June 2020

Female gamers are growing rapidly worldwide especially in young age groups and in mobile platform. Since that population change appears in recent 10 years, formerly male-oriented gaming community has confronted gender issues. In this paper, we witness that a strong gender stereotype exists for both genders in Korea by two surveys. In the first survey, subjects show that they have different expectations of opposite gender’s favorable game style where both genders have exactly same favorite styles. In the second survey, we investigate how members of hostile sexism community groups choose teammates in Overwatch game if they have privilege to select teammates for specific roles. Ilbe and Womad as two far extreme misogyny and misandry groups show hostile sexism in teammate selection. The result implies that hostile sexism and gender stereotype shown in game playing may be induced from other social factors than the amount of the game playing experiences.       
Age group differences on perception of autoplay in mobile game playing among korean gamers
Authors: Song Doo Heon , Lee Seunghun
Published: June 2020

Autoplay functions are embedded in most mobile role playing games and mobile multiplayer online battle arena games recently. Theoretically, there are different views on autoplay function in that it may be a ‘fake play’ from the traditional view and it is economical and gives functional benefits for game developing companies on balancing from functionalists’ view. In this paper, we investigate how this autoplay functions are perceived to the Korean mobile gamers. We report that there exists a strong age group effect on it and age 25 is the inflection point. Among 304 subjects including 69 females participated in this survey, the positive perception rate is positively proportional to the age from 36% to 73%. The reasons they choose to play autocombat function are convenience and utilizing sack times but the older groups (over 30) emphasize playing while doing other personal doings. Those who do not use autoplay function sustain the traditional view of game playing in that autoplay is ‘not’ the real game playing and there exists an age effect in that the inclination rate of autoplay function is negatively proportional to the age.
New multi-step three-term conjugate gradient algorithms with inexact line searches
Authors: Al-Bayati Abbas Younis , M. Ali Muna M.
Published: June 2020

This work suggests several multi-step three-term Conjugate Gradient (CG)-algorithms that satisfies their sufficient descent property and conjugacy conditions. First, we have  considered a number of well-known three-term CG-method, and we have, therefore, suggested two new classes of this type of algorithms which was based on Hestenes and Stiefel (HS) and Polak-Ribière (PR) formulas with four different versions. Both descent and conjugacy conditions for all the proposed algorithms are satisfied, at each iteration by using the strong Wolfe line search condition and it's accelerated version. These new suggested algorithms are some sort of modifications to the original  HS and PR  methods. These CG-algorithms are considered as a sort of the  memoryless BFGS update.  All of our new suggested methods are proved to be a  global convergent and numerically, more efficient than the similar methods in same area based on our selected set of used numerical problems.
Implementation of combined new optimal cuckoo algorithm with a gray wolf algorithm to solve unconstrained optimization nonlinear problems
Authors: Al-Arabo Ali Abbas , Alkawaz Rana Zaidan
Published: June 2020

In this article, a combined optimization algorithm was proposed which combines the optimal adaptive Cuckoo algorithm (OACS) which is Nature-inspired algorithm with Gray Wolf optimizer algorithm (GWO). Sometimes considering the cuckoo algorithm alone, may fail to find the local minimum-point and also fails to reach to the solution because of the slow speed of its convergence property. Therefore, considering the new proposed adaptive combined algorithm gave a strong improvement for using this to reach the minimum point in solving (23) nonlinear test problems. This is suitable to solve a large number of nonlinear unconstraint optimization test functions with obtaining good and robust numerical results.
Rice false smut detection based on faster R-CNN
Authors: Sethy Prabira Kumar , Barpanda Nalini Kanta , Rath Amiya Kumar , Behera Santi Kumari
Published: June 2020

Rice false smut is one of the most dangerous diseases in rice at the ripening phase caused by Ustilaginoidea Virens. It is one of the most important grain diseases in rice production worldwide. Its epidemics not only lead to yield loss but also reduce grain quality because of multiple mycotoxins generated by the causative pathogen. The pathogen infects developing spikelets and specifically converts individual grain into rice false smut ball. Rice false smut balls seem to be randomly formed in some grains on a panicle of a plant in the paddy field. In this study, we suggest a novel approach for the detection of rice false smut based on faster R-CNN. The process of faster R-CNN comprises regional proposal generation and object detection. The both tasks are done in same convolutional network. Because of such design it is faster for object detection. The faster R-CNN is able to detect the RFS using rectangular labelling from on-field images. The proposed approach is the initial steps to make a prototype for the automatic detection of RFS.
A computing model for trend analysis in stock data stream classiﬁcation
Authors: Razak Abdul , C. R Nirmala
Published: June 2020

For several decades, many statistical and scientiﬁc efforts took place for the better analysis or prediction of stock trading. But still it is open to offer new avenues for the scientists to rethink and discover new inferences by adopting latest technological scenarios. In this regard, this paper is trying to apply classiﬁcation techniques on stock data stream through feature extraction for the trend analysis. The proposed work is involving k-means for clustering samples into two clusters (the stocks in trend as one cluster and another on as stocks not in trend). The trend analysis is done based on density estimation of the stocks with respect to sectors. A well-known data representation method that is histogram is used to represent the sector which is in trend. This work has been implemented and experimented by considering live NSE (india) data using python and its related tools.
Web design structure with wordpress content management for sports centre booking system
Authors: Ghani Nor Sajidah Ab , Kassim Murizah , Awang Aziati Husna
Published: June 2020

Sports center booking system need to be more systematic to increase its efficiency. The World Wide Web (WWW) had been a revolution and it has been utilized to be tools of automation in many applications, including managing booking and payment system in this area of services.  However, existing system needs an ID booking to book the facilities at the Court Centre and does not delegate any confirmation to users on their booking. This paper aims at integrating stripe payment method by using the WordPress platform where it is one of the content management system (CMS) by using XAMPP. MySQL has been used to store the database while PHP and HTML have been designed to generate QR code. This system was designed based on some function needed for the new member, staffs, and students. The procedure is that the new members will register and pay their members fees. Existing student and staff will just need to sign in using their ID Number. This system has provided a booking system which presented the availability of time and date as well as the payment for the new members. Upon booking and payment, email and QR code are given to the user after the confirmation booking by an administrator.  The result shows the increase of efficiency after implementing the new features on the web system which shows 86.66% of increases in term of using the website to book the facilities at the Sports Centre from the existing system.
Fuzzy time series forecasting in determining inventory policy for a small medium enterprise (SME) company
Authors: Shariff S.Sarifah Radiah , Abdul Halim Nurul Nadiah , Zahari Siti Meriam , Derasit Zuraidah
Published: June 2020

Fuzzy time series models have been widely used to handle forecasting problems, such as forecasting consumer demand and production volume. It is of greater benefits if we have good forecasting accuracy rates especially in managing inventory in a Small and Medium Enterprise (SME) company.  This study focuses on multiple products with single production line.  The aims of this study are to propose the appropriate the forecasting method for the products, to develop new inventory policy that minimizes the total inventory cost for the company.  Simple forecasting methods like trend line, three month moving average (MA (3) and fuzzy time series forecasting are used in this study.  The result shows that fuzzy time series forecasting model is suitable to be used in forecasting future demand for all products.  The proposed inventory policy is based on the number of cycle per year and the number of production for each product has helped the company to minimize total inventory cost and schedule the production process accordingly.  The proposed inventory policy resulted in lower total inventory cost when compared to current practice.

 
On the review of image and video-based depression detection using machine learning
Authors: Ashraf Arselan , Surya Gunawan Teddy , Subhan Riza Bob , Haryanto Edy Victor , Janin Zuriati
Published: June 2020

Machine learning has been introduced in the sphere of the medical field to enhance the accuracy, precision, and analysis of diagnostics while reducing laborious jobs. With the mounting evidence, machine learning has the capability to detect mental distress like depression. Since depression is the most prevalent mental disorder in our society at present, and almost the majority of the population suffers from this issue. Hence there is an extreme need for the depression detection models, which will provide a support system and early detection of depression. This review is based on the image and video-based depression detection model using machine learning techniques. This paper analyses the data acquisition techniques along with their databases. The indicators of depression are also reviewed in this paper. The evaluation of different researches, along with their performance parameters, is summarized. The paper concludes with remarks about the techniques used and the future scope of using the image and video-based depression prediction. 