bluuebunny/crossref_metadata_2025 huggingface dataset:
Mobile IPv6 Vertical Handover Specifications, Threats, and Mitigation Methods: A Survey
Authors: Praptodiyono Supriyanto , Firmansyah Teguh , Alaydrus Mudrik , Santoso M. Iman , Osman Azlan , Abdullah Rosni
Published: August 2020

Internet users have grown substantially over the last decade, especially following the emergence of mobile technology. Most Internet connections nowadays are accessed using mobile devices in order to stay connected all the time and everywhere. Owing to the limited coverage of such access points as well as base stations, mobile devices are required to handover connectivity if there is a move to other locations. Horizontal handover is conducted when the movement is within the same network. Otherwise, there must be vertical handover when external network infrastructure is encountered. However, as the Internet is an open network that naturally lacks trust between users, the mobile nodes that move to an external network are susceptible to various attacking activities. Compromising mobile nodes may cause users to lose their data as well as destroy their mobile devices in terms of both software and hardware. Securing mobile devices is crucial in order to avoid losses in terms of not only money but also facilities. Although mobile nodes have been developed with certain security features, some researchers have found vulnerabilities. This paper surveys in detail the security vulnerabilities of mobile IPv6 vertical handover and the current relevant mitigation methods. Furthermore, we describe the mechanism of mobile IPv6 vertical handover and its security vulnerability as well as security mechanisms proposed by researchers. Based on the survey, there are apparently weaknesses in current security features that are in need of solutions to minimize the effect of malicious activities. An open direction of future research on mobile IPv6 vertical handover security is elaborated at the end of this paper.
Probiotic Potential of Lactic Acid Starter Cultures Isolated from a Traditional Fermented Sorghum-Millet Beverage
Authors: Byakika Stellah , Mukisa Ivan Muzira , Byaruhanga Yusuf Byenkya , Muyanja Charles
Published: August 2020

The purpose of this study was to establish the probiotic potential of lactic acid bacteria (LAB) starter cultures, Lb. plantarum MNC 21, L. lactis MNC 24, and W. confusa MNC 20, isolated from a traditionally fermented sorghum-millet beverage from Uganda. The cultures were examined for tolerance to acid and bile salts, bile salt hydrolase (BSH) activity, antibiotic susceptibility, biogenic amine production, mucin degradation, hydrophobicity, auto-aggregation, adherence to the ileum, coaggregation, and antimicrobial properties against selected pathogenic species. Lb. rhamnosus yoba 2012, a known probiotic, was the reference. The isolates were tolerant to acid (pH = 3) and bile (1%). W. confusa MNC 20 and Lb. plantarum MNC 21 exhibited medium BSH activity (11–15 mm diameter of hydrolysis zone) while L. lactis and Lb. rhamnosus yoba 2012 exhibited low BSH activity (<10 mm diameter of hydrolysis zone). All isolates lacked mucolytic activity. Lb. plantarum MNC 21 and W. confusa MNC 20 produced agmatine. The candidate and reference microorganisms were resistant to 10 of 21 and 5 of 21 antibiotics, respectively. The isolates exhibited hydrophobic, auto-aggregation and coaggregation properties. These three properties were exhibited more (p<0.05) by the reference than the potential probiotics. The ability of the potential probiotics to attach onto the goat ileum (7.3–8.0 log cfu/cm2) was comparable to that of Lb. rhamnosus yoba 2012 (7.6 log cfu/cm2). The four LAB inhibited E. coli, S. aureus, and S. enterica to the same extent (p<0.05). The findings indicated potential probiotic activity of the starter cultures. However, further in vivo examination of these isolates is required to confirm their probiotic capabilities.
A Machine Learning Approach to Predict Air Quality in California
Authors: Castelli Mauro , Clemente Fabiana Martins , Popovič Aleš , Silva Sara , Vanneschi Leonardo
Published: August 2020

Predicting air quality is a complex task due to the dynamic nature, volatility, and high variability in time and space of pollutants and particulates. At the same time, being able to model, predict, and monitor air quality is becoming more and more relevant, especially in urban areas, due to the observed critical impact of air pollution on citizens’ health and the environment. In this paper, we employ a popular machine learning method, support vector regression (SVR), to forecast pollutant and particulate levels and to predict the air quality index (AQI). Among the various tested alternatives, radial basis function (RBF) was the type of kernel that allowed SVR to obtain the most accurate predictions. Using the whole set of available variables revealed a more successful strategy than selecting features using principal component analysis. The presented results demonstrate that SVR with RBF kernel allows us to accurately predict hourly pollutant concentrations, like carbon monoxide, sulfur dioxide, nitrogen dioxide, ground-level ozone, and particulate matter 2.5, as well as the hourly AQI for the state of California. Classification into six AQI categories defined by the US Environmental Protection Agency was performed with an accuracy of 94.1% on unseen validation data.
“Isolated” Amelogenesis Imperfecta Associated with DLX3 Mutation: A Clinical Case
Authors: Bonnet Anne-Laure , Sceosole Kevin , Vanderzwalm Arabelle , Silve Caroline , Collignon Anne-Margaux , Gaucher Celine
Published: August 2020

Amelogenesis imperfecta (AI) represents rare tooth anomalies that affect the quality and/or quantity of the enamel. Clinical phenotypes display a wide spectrum, ranging from mild color changes to severe structural alterations with daily pain. However, all affect the quality of life because of mechanical, psychological, esthetic, and/or social repercussions. Several gene mutations have been linked to AI as a nonsyndromic (isolated) phenotype or a wider syndrome. This case report aimed to present a family with dental structure anomalies followed up in the dental department of the Louis Mourier Hospital (APHP, France) for their extremely poor dental condition. The proband and his mother were clinically diagnosed with AI, and genetic analysis revealed an already described variant in DLX3. Then, the family was further examined for tricho-dento-osseous syndrome. This report illustrates the challenge of diagnosing dental structure anomalies, specifically AI, in adults and highlights the need for an accurate and accessible molecular diagnosis for those anomalies to discriminate between isolated and syndromic pathologies.
Application of Infrared Heating for Roasting Nuts
Authors: Bagheri Hadi
Published: August 2020

Roasting is a key process in production of nuts. Improving the flavor and crispiness of texture in nuts is considered as a purpose of roasting, which increases the overall acceptance of the product. This review aims to introduce the infrared method as a new technique of roasting and evaluate the quality characteristics of some nuts after infrared roasting. Usually, the traditional roasting methods are time-consuming with high energy consumption and low production efficiency. One of the best ways to decrease roasting time and energy consumption is to provide heat by infrared (IR) radiation. However, the low penetration power of infrared radiation is one of the limitations of this method. The combination of infrared with other thermal methods can overcome this limitation. Studies have been done on roasting of nuts and other foods by different IR roasting methods such as IR, IR-hot air, and IR-microwave roasting methods. This paper reviews the effect of different IR roasting methods on the quality characteristics of roasted pistachio, peanut, hazelnut, almond, sunflower, soybean, and other food products. IR heating has been applied successfully to the roasting of some nuts. The use of infrared roasting has several advantages in comparison with traditional convective roasting methods. According to the results of most of these studies, the combination of infrared with other thermal methods to roast nuts has distinctly improved the potential of the technology as compared to the IR roasting alone.
BLATTA: Early Exploit Detection on Network Traffic with Recurrent Neural Networks
Authors: Pratomo Baskoro A. , Burnap Pete , Theodorakopoulos George
Published: August 2020

Detecting exploits is crucial since the effect of undetected ones can be devastating. Identifying their presence on the network allows us to respond and block their malicious payload before they cause damage to the system. Inspecting the payload of network traffic may offer better performance in detecting exploits as they tend to hide their presence and behave similarly to legitimate traffic. Previous works on deep packet inspection for detecting malicious traffic regularly read the full length of application layer messages. As the length varies, longer messages will take more time to analyse, during which time the attack creates a disruptive impact on the system. Hence, we propose a novel early exploit detection mechanism that scans network traffic, reading only 35.21% of application layer messages to predict malicious traffic while retaining a 97.57% detection rate and a 1.93% false positive rate. Our recurrent neural network- (RNN-) based model is the first work to our knowledge that provides early prediction of malicious application layer messages, thus detecting a potential attack earlier than other state-of-the-art approaches and enabling a form of early warning system.
Numerical Simulation of Pervious Concrete Based on Random Pore Model
Authors: Shan Jingsong , He Jinle , Li Feng
Published: August 2020

The features of the pores in pervious concrete have a great influence on the mechanical property of the pervious concrete. In this study, a finite element model (FEM) with random pores has been used to simulate the mechanical characteristics of pervious concrete. First, pervious concrete specimens with two different porosities were prepared in the laboratory. Then, the specimens were cut and the pores features were extracted based on the images of cross‐sections. Thereafter, the ellipse and roundness were introduced into a simulation model to describe the characteristics of pores including the size, area, shape, and inclined angle which have been developed randomly in the FEM using the Monte Carlo method. In the simulation model, the aggregate and cement paste have been simplified into a composite material, and the method of determining the composite modulus of aggregate‐cement paste is discussed. The simulation results show that the shape and distribution of the pores have an obvious influence on the internal stress of the pervious concrete and the pore features can be considered reasonable for the validity of the simulations. In addition, the composite modulus of the aggregate‐cement paste can be determined by comparing the simulation and test results. The recommended composite modulus in the pervious concrete simulation model is much lower than that of common impervious concrete.
Massive Radicular Cyst in the Maxillary Sinus as a Result of Deciduous Molar Tooth Pulp Necrosis
Authors: Chybicki Damian , Lipczyńska-Lewandowska Małgorzata , Ratajek-Gruda Monika , Janas-Naze Anna
Published: August 2020

The article describes a rare case of radicular cyst associated with deciduous right upper molars in a 5 y.o. male patient. The cyst developed asymptomatically in the maxillary sinus, thus causing considerable displacement of both premolar germs. Due to the severity of surgery, the patient was treated under general anesthesia in a one-day surgery system with use of the enucleation method. The extent of the lesion results in necessity of removal of the second premolar germ. Early diagnosis of the lesion would have resulted in a more conservative treatment plan. The purpose of this article is to lay emphasis on the pedodontist’s role in early diagnosis of such lesions.
Characterisation of Vibrio Species from Surface and Drinking Water Sources and Assessment of Biocontrol Potentials of Their Bacteriophages
Authors: Maje Mpho Defney , Kaptchouang Tchatchouang Christ Donald , Manganyi Madira Coutlyne , Fri Justine , Ateba Collins Njie
Published: August 2020

The aim of this study was to characterise Vibrio species of water samples collected from taps, boreholes, and dams in the North West province, South Africa, and assess biocontrol potentials of their bacteriophages. Fifty-seven putative Vibrio isolates were obtained on thiosulfate-citrate-bile-salt-sucrose agar and identified using biochemical tests and species-specific PCRs. Isolates were further characterised based on the presence of virulence factors, susceptibility to eleven antibiotics, and biofilm formation potentials. Twenty-two (38.60%) isolates were confirmed as Vibrio species, comprising V. harveyi (45.5%, n = 10), V. parahaemolyticus (22.7%, n = 5), V. cholerae (13.6%, n = 3), V. mimicus (9.1%, n = 2), and V. vulnificus (9.1%, n = 2). Three of the six virulent genes screened were positively amplified; four V. parahaemolyticus possessed the tdh (18.18%) and trh (18.18%) genes, while the zot gene was harboured by 3 V. cholerae (13.64%) and one V. mimicus (4.55%) isolate. Isolates revealed high levels of resistance to cephalothin (95.45%), ampicillin (77.27%), and streptomycin (40.91%), while lower resistances (4.55%–27.27%) were recorded for other antimicrobials. Sixteen (72.7%) isolates displayed multiple antibiotic-resistant properties. Cluster analysis of antibiotic resistance revealed a closer relationship between Vibrio isolates from different sampling sites. The Vibrio species displayed biofilm formation potentials at 37°C (63.6, n = 14), 35°C (50%, n = 11), and 25°C (36.4%, n = 8). Two phages isolated in this study (vB_VpM_SA3V and vB_VcM_SA3V) were classified as belonging to the family Myoviridae based on electron microscopy. These were able to lyse multidrug-resistant V. parahaemolyticus and V. cholerae strains. These findings not only indicate the presence of antibiotic-resistant virulent Vibrio species from dam, borehole, and tap water samples that could pose a health risk to humans who either come in contact with or consume water but also present these lytic phages as alternative agents that can be exploited for biological control of these pathogenic strains.
A Hybrid Forecasting Model for Nonstationary and Nonlinear Time Series in the Stochastic Process of CO2 Emission Trading Price Fluctuation
Authors: Chai Shanglei , Du Mo , Chen Xi , Chu Wenjun
Published: August 2020

Predicting CO2 emission prices is an important and challenging task for policy makers and market participants, as carbon prices follow a stochastic process of complex time series with nonstationary and nonlinear characteristics. Existing literature has focused on highly precise point forecasting, but it cannot correctly solve the uncertainties related to carbon price datasets in most cases. This study aims to develop a hybrid forecasting model to estimate in advance the maximum or minimum loss in the stochastic process of CO2 emission trading price fluctuation. This model can granulate raw data into fuzzy-information granular components with minimum (Low), average (R), and maximum (Up) values as changing space-description parameters. Furthermore, it can forecast carbon prices’ changing space with Low, R, and Up as inputs to support a vector regression. This method’s feasibility and effectiveness is examined using empirical experiments on European Union allowances’ spot and futures prices under the European Union’s Emissions Trading Scheme. The proposed FIG-SVM model exhibits fewer errors and superior performance than ARIMA, ARFIMA, and Markov-switching methods. This study provides several important implications for investors and risk managers involved in trading carbon financial products.
Serum Endothelin-1 Correlates with Myocardial Injury and Independently Predicts Adverse Cardiac Events in Non-ST-Elevation Acute Myocardial Infarction
Authors: Hartopo Anggoro Budi , Sukmasari Indah , Puspitawati Ira , Setianto Budi Yuli
Published: August 2020

Introduction. Serum endothelin-1 is increasingly released in acute myocardial infarction, by necrotic cardiomyocytes. In non-ST-elevation acute myocardial infarction (Non-STEMI), increased serum endothelin-1 on-admission may have clinical significance during acute hospitalisation events. Objective. The purpose of this study is to investigate whether increased serum endothelin-1 level predict adverse cardiac events in patients hospitalized with Non-STEMI. Methods. The design of this research was a prospective cohort study. Consecutive subjects with Non-STEMI undergoing symptom onset ≤24 hour were enrolled and observed during intensive hospitalization. Serum endothelin-1, troponin-I, and hs-C reactive protein were measured from peripheral blood taken on-admission. In-hospital adverse cardiac events were a composite of death, acute heart failure, cardiogenic shock, reinfarction, and resuscitated VT/VF. Results. We enrolled 66 subjects. The incidence of in-hospital adverse cardiac events is 13.6% (10 out of 66 subjects). Serum endothelin-1 level was significantly higher in subjects with in-hospital adverse cardiac events. Subjects with endothelin-1 level >2.59 pg/mL independently predicted adverse cardiac events in hospitalised Non-STEMI patients (adjusted odds ratio 44.43, 95% confidence interval: 1.44-1372.99, p value 0.03). The serum endothelin-1 level was correlated with serum troponin I level (correlation coefficient of 0.413, p value 0.012). Conclusion. Increased serum endothelin-1 on-admission correlated with increased troponin-I and independently predicted in-hospital adverse cardiac events in patients with Non-STEMI.
Discrete Adaptive Responses to MEK Inhibitor in Subpopulations of Triple-Negative Breast Cancer
Authors: Goulet Daniel R. , Foster Joseph P. , Zawistowski Jon S. , Bevill Samantha M. , Noël Mélodie P. , Olivares-Quintero José F. , Sciaky Noah , Singh Darshan , Santos Charlene , Pattenden Samantha G. , Davis Ian J. , Johnson Gary L.
Published: August 2020

Triple-negative breast cancers contain a spectrum of epithelial and mesenchymal phenotypes. SUM-229PE cells represent a model for this heterogeneity, maintaining both epithelial and mesenchymal subpopulations that are genomically similar but distinct in gene expression profiles. We identified differential regions of open chromatin in epithelial and mesenchymal cells that were strongly correlated with regions of H3K27ac. Motif analysis of these regions identified consensus sequences for transcription factors that regulate cell identity. Treatment with the MEK inhibitor trametinib induced enhancer remodeling that is associated with transcriptional regulation of genes in epithelial and mesenchymal cells. Motif analysis of enhancer peaks downregulated in response to chronic treatment with trametinib identified AP-1 motif enrichment in both epithelial and mesenchymal subpopulations. Chromatin immunoprecipitation sequencing (ChIP-seq) of JUNB identified subpopulation-specific localization, which was significantly enriched at regions of open chromatin. These results indicate that cell identity controls localization of transcription factors and chromatin-modifying enzymes to enhancers for differential control of gene expression. We identified increased H3K27ac at an enhancer region proximal to CXCR7, a G-protein–coupled receptor that increased 15-fold in expression in the epithelial subpopulation during chronic treatment. RNAi knockdown of CXCR7 inhibited proliferation in trametinib-resistant cells. Thus, adaptive resistance to chronic trametinib treatment contributes to proliferation in the presence of the drug. Acquired amplification of KRAS following trametinib dose escalation further contributed to POS cell proliferation. Adaptive followed by acquired gene expression changes contributed to proliferation in trametinib-resistant cells, suggesting inhibition of early transcriptional reprogramming could prevent resistance and the bypass of targeted therapy.

Implications:

We defined the differential responses to trametinib in subpopulations of a clinically relevant in vitro model of TNBC, and identified both adaptive and acquired elements that contribute to the emergence of drug resistance mediated by increased expression of CXCR7 and amplification of KRAS.
Acute Mesenteric Ischemia
Authors: Kühn Florian , Schiergens Tobias S. , Klar Ernst
Published: August 2020

Background: Despite constant improvements in diagnostic as well as interventional and surgical techniques, acute mesenteric ischemia (AMI) remains a life-threatening emergency with high mortality rates. The time to diagnosis of AMI is the most important predictor of patients’ outcome; therefore, prompt diagnosis and intervention are essential to reduce mortality in patients with AMI. The present review was performed to analyze potential risk factors and to help find ways to improve the outcome of patients with AMI. Summary: Whereas AMI only applies to approximately 1% of all patients with an “acute abdomen,” its incidence is rising up to 10% in patients >70 years of age. The initial clinical stage of AMI is characterized by a sudden onset of strong abdominal pain followed by a painless interval. Depending on the extent of disease, the symptoms of nonocclusive mesenteric ischemia (NOMI) and patients with a venous thrombosis can be very different from those of acute occlusive ischemia. Biphasic contrast-enhanced CT represents the gold standard for the diagnosis of arterial and venous occlusion. In case of a central occlusion of the superior mesenteric artery or signs of peritonitis, immediate surgery should be performed. If major bowel resection becomes necessary, critical residual intestinal length limits must be kept in mind. Endovascular techniques for arterial occlusion have taken on a much greater importance today. For stable patients with NOMI, interventional catheter angiography is recommended because it enables diagnosis and treatment with selective application of vasodilators. Depending on its degree, interventional treatment with a transhepatic catheter lysis should be considered for acute and chronic portal vein thrombosis. Key Message: The prompt and targeted use of the appropriate diagnostics and interventions appears to be the only way to reduce the persistently high mortality rates for AMI.
A Case of Coronavirus Disease 2019 Presenting with Seizures Secondary to Cerebral Venous Sinus Thrombosis
Authors: Hussain Suhail , Vattoth Surjith , Haroon Khawaja Hassan , Muhammad Ahmad
Published: August 2020

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2. COVID-19-associated thrombotic events are recognized. A wide variety of neurological presentations have been recently documented. We report the first case of COVID-19 presenting with generalized seizure secondary to cerebral venous sinus thrombosis.
Comparison of 68Ga-PSMA-I/T PET-CT and Multiparametric MRI for Locoregional Staging of Prostate Cancer Patients: A Pilot Study
Authors: Çelen Sinan , Gültekin Aziz , Özlülerden Yusuf , Mete Aslı , Sağtaş Ergin , Ufuk Furkan , Yüksel Doğangün , Yağcı Baki , Zümrütbaş Ali Ersin
Published: August 2020

Background/Aim: The objective of this work was to assess the value of 68Ga-DOTAGA-(3-iodo-y)fk(Sub-KuE) positron emission tomography (68Ga-PSMA-I/T PET-CT) and multiparametric magnetic resonance imaging (mp-MRI) for preoperative staging in prostate cancer (PCa) patients who underwent radical prostatectomy (RP) by validating with postoperative histopathology data. Materials and Methods: We prospectively investigated 30 consecutive PCa patients who had both mp-MRI and 68Ga-PSMA-I/T PET-CT before laparoscopic RP. The seminal vesicle invasion (SVI), lymph node metastasis (LNM), bladder neck invasion (BNI), and extracapsular extension (ECE) were investigated separately. The diagnostic performances of mp-MRI and 68Ga-PSMA-I/T PET-CT were assessed using histopathological results. Results: Both mp-MRI and 68Ga-PSMA-I/T PET-CT were not statistically significant in the evaluation of SVI, BNI, and ECE preoperatively but had statistically significant results in the assessment of LNM. mp-MRI had higher overall sensitivity for ECE, overall specificity for SVI, ECE, and BNI, and positive predictive value for ECE, SVI, BNI. 68Ga-PSMA-I/T PET-CT had higher overall sensitivity for BNI, and negative predictive value for BNI and LNM. Conclusion: mp-MRI has superior specificity, sensitivity, and accuracy for assessing ECE and SVI. Both imaging modalities had similar specificity, sensitivity, and accuracy for determining BNI. However, both imaging modalities had low diagnostic accuracy for LNM on histopathology.
Optimized output-based input shaping for control of single-link flexible manipulator using linear matrix inequality
Authors: Musa Tahir Nura , Muhammad Mustapha , Bala Muhammad Bashir , Liman Haliru , Yahaya Zimit Aminu , Shehu Tijjani Auwal
Published: August 2020

Precise hub angle positioning due to tip deflections, flexible motions and under various payloads is enormous tasks in the control of single-link flexible manipulators. In this paper, output-based command shaping (OBCS) was designed using the system output for tip deflections and residuals vibrations suppression, and this was incorporated with a linear matrix inequality (LMI) closed-loop control scheme for precise hub angle positioning.  The robustness of the hybrid control scheme was tested by changing the payloads from 0g to 30g, and 50g. Simulation results showed that endpoint residuals vibrations and tip deflections due to flexible motions were suppressed and hence precise hub angle positioning under various payloads was achieved. Integral absolute error (IAE), Integral square error (ISE) and Time response analysis (TRA) were used as the performance indexes. Hence, the hybrid control scheme is simple and robust.
Pre-trained classification of scalp conditions using image processing
Authors: Ibrahim Shafaf , Noor Azmy Zarith Azuren , Abu Mangshor Nur Nabilah , Sabri Nurbaity , Ahmad Fadzil Ahmad Firdaus , Ahmad Zaaba
Published: August 2020

Scalp problems may occur due to the miscellaneous factor, which includes genetics, stress, abuse and hair products. The conventional technique for scalp and hair treatment involves high operational cost and complicated diagnosis. Besides, it is becoming progressively important for the payer to investigate the value of new treatment selection in the management of a specific scalp problem. As they are generally expensive and inconvenient, there is an increasing need for an affordable and convenient way of monitoring scalp conditions. Thus, this paper presents a study of pre-trained classification of scalp conditions using image processing techniques. Initially, the scalp image went through the pre-processing such as image enhancement and greyscale conversion. Next, three features of color, texture, and shape were extracted from each input image, and stored in a Region of Interest (ROI) table. The knowledge of the values of the pre-trained features is used as a reference in the classification process subsequently. A technique of Support Vector Machine (SVM) is employed to classify the three types of scalp conditions which are alopecia areata (AA), dandruff and normal. A total of 120 images of the scalp conditions were tested. The classification of scalp conditions indicated a good performance of 85% accuracy. It is expected that the outcome of this study may automatically classify the scalp condition, and may assist the user on a selection of suitable treatment available.
Symmetric-type dispersion maps in dispersion-managed optical link with mid-span spectral inversion
Authors: Chung Jea-Pil , Lee Seong-Real
Published: August 2020

In long-haul optical communication systems consisting of single-mode fiber spans and fiber amplifiers, such as an erbium-doped fiber amplifier, signal distortion causes performance to deteriorate because of group velocity dispersion and fiber nonlinearity. A combination of dispersion management and optical phase conjugation is an effective technique of compensating for the distortion. In an optical link configured with this combination, the dispersion map mainly affects the compensation for the distorted optical signals. Improvements in system performance have been reported for various types of dispersion maps. In this study, a symmetric type of dispersion map with respect to the midway optical phase conjugator is proposed. The effect of the proposed dispersion maps on the compensation for the distorted 24 channel × 40 Gbps wavelength-division-multiplexed signals was assessed through numerical simulation. It was confirmed that antipodal-type dispersion maps are most appropriate for the compensation, as well as for the flexibility of the link configuration.
Fault classification on transmission line using LSTM network
Authors: Saidina Omar Abdul Malek , Khusairi Osman Muhammad , Nizam Ibrahim Mohammad , Hussain Zakaria , Farid Abidin Ahmad
Published: August 2020

Deep Learning has ignited great international attention in modern artificial intelligence techniques. The method has been widely applied in many power system applications and produced promising results. A few attempts have been made to classify fault on transmission lines using various deep learning methods. However, a type of deep learning called Long Short-Term Memory (LSTM) has not been reported in literature. Therefore, this paper presents fault classification on transmission line using LSTM network as a tool to classify different types of faults. In this study, a transmission line model with 400 kV and 100 km distance was modelled. Fault free and 10 types of fault signals are generated from the transmission line model. Fault signals are pre-processed by extracting post-fault current signals. Then, these signals are fed as input to the LSTM network and trained to classify 10 types of faults. The white Gaussian noise of level 20 dB and 30 dB signal to noise ratio (SNR) is also added to the fault current signals to evaluate the immunity of the proposed model. Simulation results show promising classification accuracy of 100%, 99.77% and 99.55% for ideal, 30 dB and 20 dB noise respectively. Results has been compared to four different methods which can be seen that the LSTM leading with the highest classification accuracy. In line with the purpose of the LSTM functions, it can be concluded that the method has a capability to classify fault signals with high accuracy.
The impact of firewall on TCP and UDP throughput in an openflow software defined network
Authors: Khairi Mutaz Hamed Hussien , S. Ariffin Sharifah H. , Abdul Latiff N. M. , Mohamad Yusof Kamaludin , K. Hassan M. , Rava Mohammad
Published: August 2020

Software Defined Networking (SDN) is an emerging networking paradigm that provides more flexibility and adaptability in terms of network definition and control. However, SDN is a logically centralized technology. Therefor the control plane (i.e. controller) scalability in SDN in particular, is also one of the problems that needs further focus. OpenFlow is one of the protocol standards in SDN, which allow the separation of the controller from the forwarding plane. The control plane has an SDN embedded firewall and is able to enforce and monitor the network activity. This firewall can be used to control the throughput. However, it may affect SDN performance. In this paper, throughput will be used as a performance metric to evaluate and assess the firewall impact on two protocols; Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) that passes through the forwarding planes. The evaluations have been verified through simulating the SDN OpenFlow network using MININET. The results show that an implementation of firewall module in SDN creates a significant 36% average drop for TCP and 87% average drop for UDP in the bandwidth which eventually affect the quality of the network and applications.
A coplanar waveguide tapered slot antenna with beam switching capabilities
Authors: Abijuru Delphine , R. Hamid M. , Seman N. , Himdi M.
Published: August 2020

A wideband tapered slot antenna (TSA) with three radiating elements for beam switching purpose is proposed in this study. The integrated radiating taper slots in assistance with metal strips acting as switches provided the proposed design with the capability of switching its beam into three different directions while maintaining the antenna performance stable. To validate the accuracy of the proposed design, the prototype was fabricated and measurements were conducted in terms of reflection coefficient (S11), radiation pattern and realized gain towards the three different operating modes. By sequentially, activating the switches, the antenna main beam rotated 90º in the XY coordinates. A realized gain ranging from 4.3 to 6.4 dBi and a wide operating bandwidth (|S11| ≤-10dB) from 3.3 GHz to 5 GHz  were observed throughout the antenna performance in simulation as well as in experiment. With the covered bands, the proposed antenna can be suitable for Sub -6GHz wireless communications systems. Improvements of Trapezoid Antenna Gain using Artificial Magnetic Conductor and Frequency Selective Surface.
Pet dog disease pre-diagnosis system for caregiver with possibilistic C-means clustering and disease database
Authors: Baek Kim Kwang , Heon Song Doo
Published: August 2020

While the population of pet dogs and veterinary clinics are increasing, there is no reliable and useful software for pet owners/caregivers who have limited knowledge on the pet diseases. In this paper, we propose a pre-diagnosis system working on the mobile platform that the pet owner can take a pre-diagnosis from his/her observation of pet dog’s abnormality. Technically, the system needs a reliable databases for disease-symptom association thus we provide it based on the textbook and encyclopedia. Then, we apply Possibilistic C-Means algorithm that is an unsupervised machine learning algorithm to form the connections between disease and symptoms from database. The system outputs five most probable diseases from the observed symptoms of pet dog. The utility of this system is to alert the owner’s attention on the pet dog’s abnormal behavior and try to find the diseases as soon as possible.
Deep image mining for convolution neural network
Authors: A. Jasm Dhamea , M. Hamad Murtadha , Hussein Alrawi Azmi Tawfek
Published: August 2020

Image mining is the method of searching and discovering valuable information and knowledge from a huge image dataset. Image mining is based on data mining, digital image processing, machine learning, image retrieval, and artificial intelligence. Image mining handled with the hidden information extraction, an association of image data and additional pattern which are not clearly visible in the image. Choosing the proper objects or the feature of the image to be suitable for image mining process is the main challenge would face the programmer. The process includes fine out the most efficient routes at a shorter time and saving the users effort. The main objective of this paper is to design and implement the image classification system with a higher performance, where a CIFAR-10 data set is used to train and testing classification models using CNN. A convolutional neural network is trustworthy, and it could lead to high-quality results. The high accuracy of 98% has been obtained using deep convolutional neural network (DCNN).
Image encryption scheme in public key cryptography based on cubic pells quadratic case
Authors: K. R. Raghunandan , Aithal Ganesh , Shetty Surendra , K. Bhavya
Published: August 2020

Cryptography systems face new threats with the transformation of time and technology. Each innovation tries to contest challenges posed by the previous system by analyzing approaches that are able to provide impressive outcomes. The prime aim of this work is to urge ways in which the concept of Pell’s equation can be used in Public key Cryptography techniques.The main aim of this approach is secure and can be computed very fast. Using Cubic Pell’s equation defined in Quadratic Case, a secure public key technique for Key generation process is showcased. The paper highlights that a key generation time of proposed scheme using Pell’s Quadratic case equation is fast compared to existing methods.The strength and quality  of the proposed method is proved and analyzed by obtaining the results of entropy, differential analysis, correlation analysis and avalanche effect. The superiority of the proposed method over the conventional AES and DES is confirmed by a 50% increase in the execution speed and shows that Standard diviation and Entropy analysis of proposed scheme gives immunity to guess the encryption key and also it is hard to deduce the private key from public key using  Diffrential analysis.
Analysis on the behavior of line differential protective relaying with solar PV penetration
Authors: E. Yusoff M. , Hashim H.
Published: August 2020

Power System Protection is very important in electrical power system as it minimizes power supply interruption to customers, and also prevents damages to electrical equipment.  Lately, renewable energy (RE) penetration in power system helps to support and fulfil the increasing demand of electricity to customers. However, the contribution of power from RE such as solar photovoltaic (PV) will increase the fault level and lead to reverse power flow; thus, it will affect power system protection reliability. This paper focuses on evaluating the reliability of differential protection relay during steady state, internal and external faults conditions when the power system is without and with solar PV penetration. Steady state and three-phase symmetrical line fault will be simulated in IEEE 39 bus test system using Power System Simulation for Engineering (PSS®E) software.
FIBR-OSS: fault injection model for bug reports in open-source software
Authors: Abdulameer Alazawi Sundos , Al-Salam Mohammed Najim
Published: August 2020

For assessment of system dependability, fault injection techniques are used to expedite the presence of an error or failure in the system, which helps evaluate fault tolerance and system failure prediction. Defects classification and prediction is the principal significant advance in the trustworthiness evaluation of complex software systems such as open-source software since it can quickly be affected by the reliability of those systems, improves performance, and lessening the product cost.   In this context, a new prototype of the fault injection model is presented, FIBR-OSS (Fault Injection for Bug Reports in Open-Source Software). FIBR-OSS can support developers to evaluate the system performance during phase's development for its dependability attributes such as reliability and system dependability means such as fault prediction or forecasting. FIBR-OSS is used for fault speed-up to test the system's failure prediction performance. Some machine learning techniques are implemented on bug reports produced existing by the bug tracking system as datasets for failure prediction techniques, some of those machine learning techniques are used in our approach.
Development of a stand-alone and scalable weather monitoring system using two-way vhf radios
Authors: B. Carbonell Maria Lynn , R. Carpio John Michael , C. Medina Juan Carlo , Paul Perote John , J. Tamayo Tristian Jhan , P. Mappatao Gerino
Published: August 2020

As weather-related disasters visit the Philippines regularly and the intensity increases over time, an all-weather system of monitoring the weather and its effects is necessary. Specifically, when super typhoon Yolanda (with international name Haiyan) devastated central Philippines in 2013, almost all public terrestrial communication systems were down. This paper proposes a “back-to-the-basics”, stand-alone and scalable system used to monitor the weather in several locations. The system is not dependent on the public telecommunication systems but rather uses the old but reliable Very High Frequency (VHF) two-way communication system for the transmission of sensor data such as temperature, wind speed and direction, rainwater precipitation and water level. The scalability feature of the system allows the addition of more monitoring stations to cover a wider area. Based on the tests conducted with the prototype composed of a command center and three (3) local monitoring stations, the system was able to demonstrate the transmission of weather data as well as the scalability feature of the system. The system is envisaged that the proposed system can be very useful in weather monitoring in a provincial setting where the command center is in the provincial capitol and the monitoring stations are in municipalities and cities within the province.
Cryptosystems using an improving hiding technique based on latin square and magic square
Authors: Mohammed Sahab Dheyaa , Hasan Taha Mohammed
Published: August 2020

Hackers should be prevented from disclosing sensitive data when sent from one device to another over the network. Therefore, the proposed method was established to prevent the attackers from exploiting the vulnerabilities of the redundancy in the ciphertext and enhances the substitution and permutation operations of the encryption process .the solution was performed by eliminates these duplicates by hiding the ciphertext into a submatrix 4 x4 that chooses randomly from magic square 16x16 in each ciphering process. Two techniques of encrypted and hiding were executed in the encryption stage by using a magic square size 3 × 3   and Latin square size 3 × 3 to providing more permutation and also to ensure an inverse matrix of decryption operation be available. In the hiding stage, the ciphertext was hidden into a 16×16 matrix that includes 16 sub-magic squares to eliminate the duplicates in the ciphertext. Where all elements that uses were polynomial numbers of a finite field of degree Galois Fields GF ( ).  The proposed technique is robust against disclosing the repetition encrypted data based on the result of Avalanche Effect in an accepted ratio (62%) and the results of the output of the proposed encryption method have acceptable randomness based on the results of the p-values (0.629515) of the National Institute of Standards and Technology (NIST) randomness tests. The work can be considered significant in the field of encrypting databases because the repetition of encrypted data inside databases is considered an important vulnerability that helps to guess the plaintext from the encrypted text.
Improved cloud data transfer security using hybrid encryption algorithm
Authors: Zaineldeen Samar , Ate Abdelrahim
Published: August 2020

Cloud computing is a model of sophisticated computing which has a strong effect on data innovation. Cloud computing offers remote access to shared computerized assets in the stored cloud. Operationally cloud servers utilize Web services that give enormus advantage to the user in a variety of applications such as banking and finance, storage, social networking and e-mail. Cloud computing accomplishes many of the features interrelated to elasticity, ease of utility, efficiency and performance with low cost.  There are a number of potential concerns related to security and privacy since the requirement to protect cloud computing expanded, the encryption algorithms play the key part in data and information security systems, on side these algorithms consume a considerable quantity of computing resource.This paper,presenting  a new hybrid encryption algorithm emphasising  on AES and Enhanced Homomorphic Cryptosystem (EHC) as a hybrid encryption  to guarantee the secure exchange of data between the user and the cloud server, and compression study for two proficient homomorphic encryption techniques for encoding Data Encryption Standard (DES), Advance Encryption Stander (AES).With The proposed techniques an evaluation has been conducted for those encryption algorithms at diverse file sizes of data, to evaluate time taking for encryption and decryption, throughput, memory consumption and power consumption. The major finding was thats the proposed method has the extremity throughput; memory consumption and our proposed work took advantage of the least time taken in sec for encryption and decryption.
An efficient hybrid model for secure transmission of data by using efficient data collection and dissemination (EDCD) algorithm based WSN
Authors: Mahmood Akawee Mustafa , Meteab Al-Obaidi Mohanad Ali , Turki Al-Hilfi Haider Mohammed , Jassim Sabbar Insaif , Sutikno Tole
Published: August 2020

Wireless Sensor Network (WSN) is one of the most important elements of the Internet of Things paradigm. Energy consumption is a vital issue in IoT and WSN.  Security primitives in the IoT are energy consuming. Addressed the security issue for transmitted data by IoT sensor node add another challenge in term of energy consumption. finding the satisfactory solutions that reduce power consumption at the same time as making sure the required security services is not always an easy undertaking. Therefore, in this article, we proposed an efficient hybrid model for secure transmission of data from sensor nodes to receivers in WSN applications.  The proposed model includes two algorithms Rivest–Shamir–Adleman (RSA) and efficient data collection and dissemination (EDCD). The key idea behind the proposed model is to prevent to secure sensed data if no significant change between the current data and the last transmitted data by the apply EDCD1 algorithm, which that will help in saving the sensor node energy. The reason for that the size of cipher data is so large compared to the sensed data, which that will increase the energy consumption.  The outcome results shown that the proposed model has a high performance compared to RSA in term of energy consumption.
Zinc oxide-paper based sensor for photoconductive ultraviolet detection
Authors: Che Soh Mohammad Shafiq , Zainal Abidin Mastura Shafinaz , Abd Rahman Shaharin Fadzli , Elangkovan Shuthish , Md Rashid Ahmad Bukhairi
Published: August 2020

Paper based sensor is the new technology to fabricate a simple, portable, and low cost device that exhibits the comparable properties and functions with those fabricated using complex fabrication process. Paper based sensor is usually applied in environmental monitoring, health diagnostics, and food quality control.  This research is focusing on the paper based sensor that will contribute to the development of Ultraviolet (UV) sensor. The fabrication of the sensor was done by using different grade of pencil, namely 6B and 2B on different type of paper. The different grade of pencil corresponds to different percentage of graphite and clay. As for the type of paper, A4 printing paper and Whatman filter paper were used. UV sensing operation was analyzed from the measurement of current-voltage (I-V) characteristics under the exposure of UV light. Zinc oxide (ZnO) was coated on the sensor to facilitate the detection in the presence of UV. The sample fabricated using 6B pencil grade on A4 printing paper and with ZnO coating showed a better UV sensing performance compared to other samples. This is due to the high conduction of 6B pencil grade and smooth surface of A4 printing paper. The ZnO coating increased the sensor sensitivity and response towards the UV light. These findings provide valuable information which can be used in fabricating a low-cost and simple UV paper sensor.