Search results for: fuzzy genetic network programming

Authors: Dongjae Kang, Sokho Son, Jinmee Kim

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Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.

Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Debjani Ghosh, Goutam Chowdhury, Prosenjit Samanta, Asish Kumar Mukhopadhyay

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Acute diarrhoea caused by diarrheagenic Escherichia coli (DEC) is one of the major public health problem in developing countries, mainly in Asia and Africa. DEC consists of six pathogroups, but the majority of the cases were associated with the three pathogropus, enterotoxigenic E. coli (ETEC), enteroaggregative E. coli (EAEC), and enteropathogenic E. coli (EPEC). Hence, we studied the prevalence and antimicrobial resistance of these three major DEC pathogroups in hospitalized diarrheal patients in Kolkata, India, during 2012-2019 with a large sample size. 8,891 stool samples were processed, and 7.8% of them was identified as DEC infection screened by multiplex PCR, in which ETEC was most common (47.7%) followed by EAEC (38.4%) and EPEC (13.9%). Clinical patient history suggested that children <5 years of age were mostly affected with ETEC and EAEC, whereas people within >5-14 years of age were significantly associated with EPEC and ETEC infections. Antibiogram profile showed a high prevalence of multidrug resistant (MDR) isolates among DEC (56.9%), in which 9% were resistant to antibiotics of six different antimicrobial classes. Screening of the antibiotic resistance conferring genes in DEC showed the presence of blaCTX-M (30.2%) in highest number followed by blaTEM (27.5%), tetB (18%), sul2 (12.6%), strA (11.8%), aadA1 (9.8%), blaOXA-1 (9%), dfrA1 (1.6%) and blaSHV (1.2%) which indicates the existence of mobile genetic elements in those isolates. Therefore, the presence of MDR DEC strains in higher number alarms the public health authorities to take preventive measures before the upsurge of the DEC caused diarrhea cases in near future.

Keywords: diarrheagenic escherichia coli, ETEC, EAEC, EPEC

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Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

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Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

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Authors: L. M. Al-Harbi, A. M. Shokry, J. S. M. Sabir, A. Chaudhary, J. Manikandan, K. S. Saini

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Breast cancer is the second most common cause of cancer death worldwide and is the most common malignancy among Saudi females. During breast carcinogenesis, a wide-array of cytogenetic changes involving deletions, or amplification, or translocations, of part or whole of chromosome regions have been observed. Because of the limitations of various earlier technologies, newer tools are developed to scan for changes at the genomic level. Recently, Array Comparative Genomic Hybridization (aCGH) technique has been applied for detecting segmental genomic alterations at molecular level. In this study, aCGH was performed on twenty breast cancer tumors and their matching non-tumor (normal) counterparts using the Agilent 2x400K. Several regions were identified to be either amplified or deleted in a tumor-specific manner. Most frequent alterations were amplification of chromosome 1q, chromosome 8q, 20q, and deletions at 16q were also detected. The amplification of genetic events at 1q and 8q were further validated using FISH analysis using probes targeting 1q25 and 8q (MYC gene). The copy number changes at these loci can potentially cause a significant change in the tumor behavior, as deletions in the E-Cadherin (CDH1)-tumor suppressor gene as well as amplification of the oncogenes-Aurora Kinase A. (AURKA) and MYC could make these tumors highly metastatic. This study validates the use of aCGH in Saudi breast cancer patients and sets the foundations necessary for performing larger cohort studies searching for ethnicity-specific biomarkers and gene copy number variations.

Keywords: breast cancer, molecular biology, ecology, environment

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Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

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Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

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Authors: C. Nathanailides, S. Anastasiou, A. Dimitroglou, P. Logothetis, G. Kanlis

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In the present work we reviewed historical data of the Greek Marine aquaculture industry including adoption of new methods and technological innovation. The results indicate that the industry exhibited a rapid rise in production efficiency, employment and adoption of new technologies which reduced outbreaks of diseases, reduced production risk and the price of the farmed fish. The improvements of total quality practices and technological input on the Greek Aquaculture industry include improved survival, growth and body shape of farmed fish, which resulted from development of new aquaculture feeds and the genetic selection of the bloodstock. Also improvements in the quality of the final product were achieved via technological input in the methods and technology applied during harvesting, packaging, and transportation-preservation of farmed fish ensuring high quality of the product from the fish farm to the plate of the consumers. These parameters (health management, nutrition, genetics, harvesting and post-harvesting methods and technology) changed significantly over the last twenty years and the results of these improvements are reflected in the production efficiency of the Aquaculture industry and the quality of the final product. It is concluded that the Greek aquaculture industry exhibited a rapid growth, adoption of technologies and supply was stabilized after the global financial crisis, nevertheless, the development of the Greek aquaculture industry is currently limited by international trade sanctions, credit crunch, and increased taxation and not by limited technology or resources.

Keywords: innovation, aquaculture, total quality, management

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Authors: Gulfam Haider, sana danish

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Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Le Zhao, Alain Nogaret

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We have built universal Central Pattern Generator (CPG) hardware by interconnecting Hodgkin-Huxley neurons with reciprocally inhibitory synapses. We investigate the dynamics of neuron oscillations as a function of the time delay between current steps applied to individual neurons. We demonstrate stimulus dependent switching between spiking polyrhythms and map the phase portraits of the neuron oscillations to reveal the basins of attraction of the system. We experimentally study the dependence of the attraction basins on the network parameters: the neuron response time and the strength of inhibitory connections.

Keywords: central pattern generator, winnerless competition principle, artificial neural networks, synapses

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Authors: R. S. Al Abri, M. H. Albadi, M. H. Al Abri, U. K. Al Rasbi, M. H. Al Hasni, S. M. Al Shidi

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This paper presents an analysis study on the impacts of the changes of the capacitor banks, the loss of a transformer, and the installation of distributed generation on the voltage total harmonic distortion and harmonic resonance. The study is applied in a real system in Oman, Sohar Industrial Port–C Substation Network. Frequency scan method and Fourier series analysis method are used with the help of EDSA software. Moreover, the results are compared with limits specified by national Oman distribution code.

Keywords: power quality, capacitor bank, voltage total harmonics distortion, harmonic resonance, frequency scan

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Authors: Min Chen, Hui Lin

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VGEs are a kind of typical web- and computer-based geographic environment, with aims of merging geographic knowledge, computer technology, virtual reality technology, network technology, and geographic information technology, to provide a digital mirror of physical geographic environments to allow users to ‘feel it in person’ by a means for augmenting the senses and to ‘know it beyond reality’ through geographic phenomena simulation and collaborative geographic experiments. Many achievements have appeared in this field, but further evolution should be explored. With the exploration of the conception of VGEs, and some examples, this article illustrated the role of VGEs and their contribution to currently GIScience. Based on the above analysis, questions are proposed for discussing about the future way of VGEs.

Keywords: virtual geographic environments (VGEs), GIScience, virtual reality, geographic information systems

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: train formation, wagon flows, marshalling yard, railway technology

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Authors: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

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Authors: M. Ntswane, N. Mbuma, M. Labuschagne, A. Mofokeng, M. Rantso

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Cowpea is an essential legume for the nutrition and health of millions of people in different regions. The production and productivity of the crop are very limited in South Africa due to a lack of adapted and stable genotypes. The improvement of nutritional quality is made possible by manipulating the genes of diverse cowpea genotypes available around the world. Assessing the adaptability and stability of the cowpea mutant genotypes for yield and nutritional quality requires examining them in different environments. The objective of the study was to determine the adaptability and stability of cowpea mutant genotypes under South African conditions and to identify the superior genotypes that combine grain yield components, antioxidants, and nutritional quality. Thirty-one cowpea genotypes were obtained from the Agricultural Research Council grain crops (ARC-GC) and were planted in Glen, Mafikeng, Polokwane, Potchefstroom, Taung, and Vaalharts during the 2021/22 summer cropping season. Significant genotype by location interactions indicated the possibility of genetic improvement of these traits. The genotype plus genotype by environment indicated broad adaptability and stability of mutant genotypes. The principal component analysis identified the association of the genotypes with the traits. Phenotypic correlation analysis showed that Zn and protein content were significant and positively correlated and suggested the possibility of indirect selection of these traits. Results from this study could be used to help plant breeders in making informed decisions and developing nutritionally improved cowpea genotypes with the aim of addressing the challenges of poor nutritional quality.

Keywords: cowpea seeds, adaptability, stability, mineral elements, protein content

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Authors: A. Bouamrane, M. T. Bouziane, K. Boutebba, Y. Djebbar

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This paper aims to develop a decision support tool to provide solutions to the problems of sewer networks management/maintenance in order to assist the manager to sort sections upon priority of intervention by taking account of the technical, economic, social and environmental standards as well as the managers’ strategy. This solution uses the Analytic Network Process (ANP) developed by Thomas Saaty, coupled with a set of tools for modelling and collecting integrated data from a geographic information system (GIS). It provides to the decision maker a tool adapted to the reality on the ground and effective in usage compared to the means and objectives of the manager.

Keywords: multi-criteria decision support, maintenance, Geographic Information System, modelling

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Authors: Shantanu Prakash, Suruchi Shukla, Amita Jain

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Introduction: The hepatitis C virus (HCV) is a major public health problem and a leading cause of chronic liver disease. Injection drug use and individuals receiving blood and blood products are the primary modes of HCV transmission. Our study aims to establish the prevalent genotypes/ subtypes of HCV circulating in Uttar Pradesh, North India, as reported from a tertiary care hospital. Methods: It is a retrospective observational analysis of consecutive 404 HCV RNA positive cases referred to our hospital during September 2014 to April 2017. The study was approved by an institutional ethics committee. Written informed consent was taken from each participant. Clinical and demographic details of these patients were recorded using predesigned questionnaires. All the laboratory testing was carried on stored serum sample of enrolled cases. Genotyping of all 404 strains was done by Sanger’s sequencing of the core region. The phylogenetic analysis of 179 HCV strains with high -quality sequencing data was performed. Results: The distribution of prevalent genotypes/ subtypes as noted in the present study was; Genotype (GT)1a [n-101(25%)], GT1b [n-12(2.9%)], GT1c [1(0.25%)], GT3a [275(68.07%)], GT3b [9(2.2%)], GT3g [2(0.49%)], GT3i [3(0.74%)], and GT4a [1(0.24%)]. HCV genotypes GT2, GT5 and GT6 were not detected from our region. Sequence analysis showed high genotypic variability in HCV GT3. Phylogenetic analysis showed that HCV GT3 and GT1 circulating in our region were related to Indian strains reported earlier. Conclusions: HCV genotypes 3a and 1a are commonest circulating genotypes in Uttar Pradesh (UP), India.

Keywords: Hepatitis C virus, genetic variation, bioinformatics, genotype, HCV

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Authors: Agodo Mugenyi Herbert

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Background: A high prevalence of both HIV infection and mental disorders exists in Sub-Saharan Africa, however there is little integration of care for mental health disorders among HIV-infected individuals. The study aimed at determining the management of common mental disorders among HIV/AIDS clients attending Antiretroviral clinic in Hoima regional referral hospital. Significancy of the study: The information generated by this study would help mental health advocates, ministry of health, Civil society organizations in HIV programming to advocate for enhanced mental health care for PLWHA. The result will be used in policy development and lobbying for integration of mental health care in HIV/AIDS care. Methods: This study applied a cross sectional design. It involved data collection from clients with HIV/AIDS attending ART clinic in Hoima regional referral hospital at one specific point in time. It aimed at providing data on the entire population under study. Data was collected from Hoima Regional Referral Hospital at the ART clinic. Data analysis was performed using SPSS version 24. Results: 66 HIV/AIDS clients and 10 health workers in the ART clinic who participated fully completed the study. The overall prevalence of at least one form of mental disorder was 83%. Majority of the health care practitioner do not use pharmacological, psychological, and social interventions to manage such disorders. Conclusion: These results are suggestive of a significant proportion of the HIV-infected patients experiencing psychological difficulty for which they do not receive treatment Recommendations: Current care practices applied to patients with HIV/AIDS should be integrated more generally to include treatment services to identify and manage common mental disorders.

Keywords: common mental disorders, mental health, mental illness, and severe mental illness

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Authors: Abdullah A. Al Qurashi, Hattan A. Hassani, Bader K. Alaslap

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Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: arrhythmogenic right ventricular dysplasia, cardiac disease, interventional cardiology, cardiac electrophysiology

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Authors: Chijioke Okafor, Malik Maaza, Touhami Mokrani

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Proton exchange membrane, PEM was developed and tested for potential application in fuel cell. Nafion was electrospun to nanofiber network with the aid of poly(ethylene oxide), PEO, as a carrier polymer. The matrix polymer was crosslinked with Norland Optical Adhesive 63 under UV after compacting and annealing. The welded nanofiber mat was characterized for morphology, proton conductivity, and methanol permeability, then tested in a single cell test station. The results of the fabricated nanofiber membrane showed a proton conductivity of 0.1 S/cm at 25 oC and higher fiber volume fraction; methanol permeability of 3.6x10^-6 cm2/s and power density of 96.1 and 81.2 mW/cm2 for 5M and 1M methanol concentration respectively.

Keywords: fuel cell, nafion, nanofiber, permeability

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Authors: Balázs Kulcsár

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Few people now doubt the future of the global energy transition. The only question is whether the pace of renewables' penetration will be sufficient to compete with the rate of warming. Dynamic changes are also taking place in the Hungarian electricity system. In addition to nuclear power, which provides the basic electricity supply, the most dynamic is solar power, which is largely small-scale and residential. The emergence of solar power is outlining the emergence of energy production and supply fabric of municipalities. This creates the potential for over-producing municipalities to supply the electricity needs of neighboring settlements with lower production beyond renewables. By taking advantage of this energy sharing, electricity supply based on pure renewables can be achieved more quickly.

Keywords: renewable energy, energy geography, self-sufficiency, energy transition

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Authors: Reza Miresmaeili, Asghar Heydari Astaraee, Fereshteh Dolati

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In the present study, an analytical model based on dislocation density model was developed to simulate grain refinement in surface mechanical attrition treatment (SMAT). The correlation between SMAT time and development in plastic strain on one hand, and dislocation density evolution, on the other hand, was established to simulate the grain refinement in SMAT. A dislocation density-based constitutive material law was implemented using VUHARD subroutine. A random sequence of shots is taken into consideration for multiple impacts model using Python programming language by utilizing a random function. The simulation technique was to model each impact in a separate run and then transferring the results of each run as initial conditions for the next run (impact). The developed Finite Element (FE) model of multiple impacts describes the coverage evolution in SMAT. Simulations were run to coverage levels as high as 4500%. It is shown that the coverage implemented in the FE model is equal to the experimental coverage. It is depicted that numerical SMAT coverage parameter is adequately conforming to the well-known Avrami model. Comparison between numerical results and experimental measurements for residual stresses and depth of deformation layers confirms the performance of the established FE model for surface engineering evaluations in SMA treatment. X-ray diffraction (XRD) studies of grain refinement, including resultant grain size and dislocation density, were conducted to validate the established model. The full width at half-maximum in XRD profiles can be used to measure the grain size. Numerical results and experimental measurements of grain refinement illustrate good agreement and show the capability of established FE model to predict the gradient microstructure in SMA treatment.

Keywords: dislocation density, grain refinement, severe plastic deformation, simulation, surface mechanical attrition treatment

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: Rade M. Ciric

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The paper shows the development and implementation of the syllabus of the subject 'Distribution and Industrial Networks', attended by the vocational specialist Year 4 students of the Electric Power Engineering study programme at the Higher Education Technical School of Vocational Studies in Novi Sad. The aim of the subject is to equip students with the knowledge necessary for planning, exploitation and management of distributive and industrial electric power networks in an open electricity market environment. The results of the evaluation of educational outcomes on the subject are presented and discussed.

Keywords: engineering education, power distribution network, syllabus implementation, outcome evaluation

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Authors: Shanti Faridah Salleh, Azzahrah Anuar, Hamimah Ujir, Rohana Sapawi, Wan Hashim Wan Ibrahim, Noraziah Abdul Wahab, Majina Sulaiman, Raudhah Ahmadi, Al-Khalid Othman, Johari Abdullah

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Integrated Cumulative Grade Point Average or iCGPA is an evaluation and reporting system that represents a comprehensive development of students’ achievement in their academic programs. Universiti Malaysia Sarawak, UNIMAS has started its implementation of iCGPA in 2016. iCGPA is driven by the Outcome-Based Education (OBE) system that has been long integrated into the higher education in Malaysia. iCGPA is not only a tool to enhance the OBE concept through constructive alignment but it is also an integrated mechanism to assist various stakeholders in making decisions or planning for program improvement. The outcome of this integrated system is the reporting of students’ academic performance in terms of cognitive (knowledge), psychomotor (skills), and affective (attitude) of which the students acquire throughout the duration of their study. The iCGPA reporting illustrates the attainment of student’s attribute in the eight domains of learning outcomes listed in the Malaysian Qualifications Framework (MQF). This paper discusses on the implementation of iCGPA in UNIMAS on the policy and strategy to direct the whole university to implement the iCGPA. The steps and challenges in integrating the exsting Outcome-Based Education and utilising iCGPA as a tool to quantify the students’ achievement are also highlighted in this paper. Finally, the ACADEMIA system, which is a dedicated centralised program ensure the implementation of iCGPA is a success has been developed. This paper discusses the structure and the analysis of ACADEMIA program and concludes the analysis made on the improvement made on the implementation of constructive alignment in all 40 programs involves in iCGPA implementation.

Keywords: constructive alignment, holistic graduates, mapping of assessment, programme outcome

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Authors: Nadjah Chergui, Narhimene Boustia

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Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: context, default, exception, vulnerability

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Authors: Winncy Du, Jeremy Nguyen, Harpinder Dhillon, Reinardus Justin Halim, Clayton Haske, Trent Hughes, Marissa Ortiz, Rozy Saini

Abstract:

Stroke often causes death or cerebro-vascular (CV) brain damage. Most patients with CV brain damage lost their motor control on their limbs. This paper focuses on developing a reliable, safe, and non-invasive EEG-based robot-assistant stroke rehabilitation system to help stroke survivors to rapidly restore their motor control functions for their limbs. An electroencephalogram (EEG) recording device (EPOC Headset) and was used to detect a patient’s brain activities. The EEG signals were then processed, classified, and interpreted to the motion intentions, and then converted to a series of robot motion commands. A six-axis articulated robot (AdeptSix 300) was employed to provide the intended motions based on these commends. To ensure the EEG device, the computer, and the robot can communicate to each other, an Arduino microcontroller is used to physically execute the programming codes to a series output pins’ status (HIGH or LOW). Then these “hardware” commends were sent to a 24 V relay to trigger the robot’s motion. A lookup table for various motion intensions and the associated EEG signal patterns were created (through training) and installed in the microcontroller. Thus, the motion intention can be direct determined by comparing the EEG patterns obtaibed from the patient with the look-up table’s EEG patterns; and the corresponding motion commends are sent to the robot to provide the intended motion without going through feature extraction and interpretation each time (a time-consuming process). For safety sake, an extender was designed and attached to the robot’s end effector to ensure the patient is beyond the robot’s workspace. The gripper is also designed to hold the patient’s limb. The test results of this rehabilitation system show that it can accurately interpret the patient’s motion intension and move the patient’s arm to the intended position.

Keywords: brain waves, EEG sensor, motion control, robot-assistant stroke rehabilitation

Procedia PDF Downloads 388

Authors: Joo-Hyung Oh, Sekwon Kim, Myoungsun Noh, Chaetae Im

Abstract:

The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on All-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. Moreover, in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.

Keywords: LTE, 4G, VoLTE, phone number spoofing

Procedia PDF Downloads 528

Authors: Zhang Lei, Zhan Haiyang, Gu Miao

Abstract:

A universal software platform is developed for improving the defects in the practical one. This software platform has distinct advantages in modularization, information management, and the interfaces. Several technologies such as computer technology, virtualization technology, network technology, etc. are combined together in this software platform, and four working modes are introduced in this article including single mode, distributed mode, cloud mode, and the centralized mode. The application area of the software platform is extended through the switch between these working modes. The software platform can arrange the thermal vacuum test process automatically. This function can improve the reliability of thermal vacuum test.

Keywords: software platform, thermal vacuum test, control and measurement, work mode

Procedia PDF Downloads 421

Authors: Rashad R. Al-Hindi

Abstract:

The aim of this study was to isolate and identify lactic acid bacteria and evaluate their therapeutic and food preservation importance. Ninety-three suspected lactic acid bacteria (LAB) were isolated from thirteen different raw and fermented milk of indigenous sources in the Kingdom of Saudi Arabia. The identification of forty-six selected LAB strains and genetic relatedness were performed based on 16S rDNA gene sequence comparison. The LAB counts in certain samples were higher under microaerobic than anaerobic conditions. The identified LAB belonged to genera Enterococcus (16 strains), Lactobacillus (9 strains), Weissella (10 strains), Streptococcus (8 strains) and Lactococcus (3 strains). Phylogenetic tree generated from the full-length (~1.6 kb) sequences confirmed previous findings. Utilization of shorter 16S rDNA sequences (~1.0 kb) also discriminated among strains of which V2 region was the most effective. None of the strains exhibited resistance to clinically relevant antibiotics or undesirable hemolytic activity, while they differed in other probiotic characteristics, e.g., tolerance to acidic pH, resistance to bile salt, and antibacterial activity. In conclusion, the isolates Lactobacillus casei MSJ1, Lactobacillus casei Dwan5, Lactobacillus plantarum EyLan2 and Enterococcus faecium Gail-BawZir8 are likely the best probiotic LAB and we speculate that studying the synergistic effects of bacterial combinations might result in the occurrence of more effective probiotic potential. We argue that the raw and fermented milk of animals hosted in Saudi Arabia, especially stirred yogurt (Laban) made from camel milk, are rich in LAB with promising probiotics potential.

Keywords: fermented foods, lactic acid bacteria, probiotics, Saudi Arabia

Procedia PDF Downloads 201

Authors: Guesh Mulaw, Haile Beruhulay, Anteneh Tesfaye, Tesfaye Sisay Diriba Muleta

Abstract:

Probiotics are live microorganisms that, when administered in adequate amounts, promote the health of a consumer. The present work aims to study the whole genome sequence of probiotic strains of lactic acid bacteria (LAB) isolated from traditional Ethiopian fermented kocho for bacteriocin production and to evaluate their probiotic properties. LAB were isolated from traditionally fermented kocho samples and characterized following standard methods. Accordingly, a total of 150 LAB were isolated, of which 7 (4.67%) isolates showed 50.52-74.05% and 33.33-62.40% survival rates at pH 2 for 3 and 6 h, respectively. The 7 acid-tolerant isolates were also tolerated 0.3% bile salt for 24 h with 88.96 to 98.10% survival. The acid and bile salt-tolerant LAB isolates also inhibited some reference foodborne pathogenic bacteria to varying degrees. All 7 acid- and bile salt-tolerant isolates were susceptible to ampicillin, tetracycline and erythromycin. However, the potent isolates showed remarkable resistance to kanamycin. Likewise, four of the 7 isolates were resistant to streptomycin, but three of the 7 isolates were sensitive to streptomycin. The identification of the seven selected probiotic LAB isolates and their genetic relatedness was performed based on whole-genome sequence comparisons. Consequently, these isolates belonged to Lactobacillus species, including 6 Lb. plantarum, 1 Lb. brevis. Among the 7 potential probiotic LAB strains, BAGEL predicted 2 bacteriocin for class II in the genome of 7 strains. The 7 Lactobacillus strains were found to be potentially useful for producing functional products and could be suitable probiotic candidates for food processing industries

Keywords: ferneted foods, kocho, probiotics, lactic acid bacteria

Procedia PDF Downloads 37