Search results for: evolutionary genetic algorithm

Authors: Sadia Basar, Naila Habib, Awais Adnan

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The paper presents the Technique for Image Segmentation Using K-Means Clustering Classification. The presented algorithms were specific, however, missed the neighboring information and required high-speed computerized machines to run the segmentation algorithms. Clustering is the process of partitioning a group of data points into a small number of clusters. The proposed method is content-aware and feature extraction method which is able to run on low-end computerized machines, simple algorithm, required low-quality streaming, efficient and used for security purpose. It has the capability to highlight the boundary and the object. At first, the user enters the data in the representation of the input. Then in the next step, the digital image is converted into groups clusters. Clusters are divided into many regions. The same categories with same features of clusters are assembled within a group and different clusters are placed in other groups. Finally, the clusters are combined with respect to similar features and then represented in the form of segments. The clustered image depicts the clear representation of the digital image in order to highlight the regions and boundaries of the image. At last, the final image is presented in the form of segments. All colors of the image are separated in clusters.

Keywords: clustering, image segmentation, K-means function, local and global minimum, region

Procedia PDF Downloads 364

Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

Procedia PDF Downloads 69

Authors: Sungchul Ha, Hyunwoo Kim

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In mobile ad hoc networks, all nodes in a network only have limited resources and calculation ability. Therefore communication topology which have long lifetime is good for all nodes in mobile ad hoc networks. There are a variety of researches on security problems in wireless ad hoc networks. The existing many researches try to make efficient security schemes to reduce network power consumption and enhance network lifetime. Because a new node can join the network at any time, the wireless ad hoc networks are exposed to various threats and can be destroyed by attacks. Resource consumption is absolutely necessary to secure networks, but more resource consumption can be a critical problem to network lifetime. This paper focuses on efficient monitoring node distribution to enhance network lifetime in wireless ad hoc networks. Since the wireless ad hoc networks cannot use centralized infrastructure and security systems of wired networks, a new special IDS scheme is necessary. The scheme should not only cover all nodes in a network but also enhance the network lifetime. In this paper, we propose an efficient IDS node distribution scheme using minimum spanning tree (MST) method. The simulation results show that the proposed algorithm has superior performance in comparison with existing algorithms.

Keywords: MANETs, IDS, power control, minimum spanning tree

Procedia PDF Downloads 353

Authors: Muhammad Maisam Abbas, Salman Tariq, Usama Riaz, Muhammad Tanveer, Humaira Abdul Ghafoor

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Autism Spectrum Disorder (ASD) refers to a developmental disorder that impairs an individual's communication and interaction ability. Individuals feel difficult to read facial expressions while communicating or interacting. Facial Expression Recognition (FER) is a unique method of classifying basic human expressions, i.e., happiness, fear, surprise, sadness, disgust, neutral, and anger through static and dynamic sources. This paper conducts a comprehensive comparison and proposed optimal method for a continued research project—a system that can assist people who have Autism Spectrum Disorder (ASD) in recognizing facial expressions. Comparison has been conducted on three supervised learning algorithms EigenFace, FisherFace, and LBPH. The JAFFE, CK+, and TFEID (I&II) datasets have been used to train and test the algorithms. The results were then evaluated based on variance, standard deviation, and accuracy. The experiments showed that FisherFace has the highest accuracy for all datasets and is considered the best algorithm to be implemented in our system.

Keywords: autism spectrum disorder, ASD, EigenFace, facial expression recognition, FisherFace, local binary pattern histogram, LBPH

Procedia PDF Downloads 161

Authors: S. Ayeko, J. Milton, C. Hughes, K. Anderson, R. G. Middleton

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Background: Periprosthetic femoral fractures (PFF) in association with hip hemiarthroplasty or total hip arthroplasty is a common and serious complication. In the Vancouver Classification system algorithm, B1 fractures should be treated with Open Reduction and Internal Fixation (ORIF) and preferentially revised in combination with ORIF if B2 or B3. This study aims to assess patient outcomes after plate osteosynthesis alone for Vancouver B1 and B2 fractures. The main outcome is the 1-year re-revision rate, and secondary outcomes are 30-day and 1-year mortality. Method: This is a retrospective single-centre case-series review from January 2016 to June 2021. Vancouver B1 and B2, non-malignancy fractures in adults over 18 years of age treated with polyaxial Non-Contact Bridging plate osteosynthesis, have been included. Outcomes were gathered from electronic notes and radiographs. Results: There were 50 B1 and 64 B2 fractures. 26 B2 fractures were managed with ORIF and revision, 39 ORIF alone. Of the revision group, one died within 30 days (3.8%), one at one year (3.8%), and two were revised within one year (7.7). Of the B2 ORIF group, three died within 30-day mortality (7.96%), eight at one year (21.1%), and 0 were revised in 1 year. Conclusion: This study has demonstrated that satisfactory outcomes can be achieved with ORIF, excluding revision in the management of B2 fractures.

Keywords: arthroplasty, bridging plate, periprosthetic fracture, revision surgery

Procedia PDF Downloads 93

Authors: Hossein Rassi, Alaheh Gholami Roud-Majany, Zahra Razavi, Massoud Hoshmand

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Cervical cancer is multi step disease that is thought to result from an interaction between genetic background and environmental factors. Human papillomavirus (HPV) infection is the leading risk factor for cervical intraepithelial neoplasia (CIN)and cervical cancer. In other hand, some of hTERT and miRNA polymorphism may plays an important role in carcinogenesis. This study attempts to clarify the relation of hTERT genotypes and miR-146a genotypes in cervical cancer. Forty two archival samples with cervical lesion retired from Khatam hospital and 40 sample from healthy persons used as control group. A simple and rapid method was used to detect the simultaneous amplification of the HPV consensus L1 region and HPV-16,-18, -11, -31, 33 and -35 along with the b-globin gene as an internal control. We use Multiplex PCR for detection of hTERT and miR-146a rs2910164 genotypes in our lab. Finally, data analysis was performed using the 7 version of the Epi Info(TM) 2012 software and test chi-square(x2) for trend. Cervix lesions were collected from 42 patients with Squamous metaplasia, cervical intraepithelial neoplasia, and cervical carcinoma. Successful DNA extraction was assessed by PCR amplification of b-actin gene (99bp). According to the results, hTERT ( rs 2736098) GG genotype and miR-146a rs2910164 CC genotype was significantly associated with increased risk of cervical cancer in the study population. In this study, we detected 13 HPV 18 from 42 cervical cancer. The connection between several SNP polymorphism and human virus papilloma in rare researches were seen. The reason of these differences in researches' findings can result in different kinds of races and geographic situations and also differences in life grooves in every region. The present study provided preliminary evidence that a p53 GG genotype and miR-146a rs2910164 CC genotype may effect cervical cancer risk in the study population, interacting synergistically with HPV 18 genotype. Our results demonstrate that the testing of hTERT rs 2736098 genotypes and miR-146a rs2910164 genotypes in combination with HPV18 can serve as major risk factors in the early identification of cervical cancers. Furthermore, the results indicate the possibility of primary prevention of cervical cancer by vaccination against HPV18 in Iran.

Keywords: polymorphism of hTERT gene, miR-146a rs2910164 polymorphism, cervical cancer, virus

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

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Authors: Hatem Mrad, Mohamed Bouazara, Fouad Erchiqui

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Fatigue, is considered as one of the main cause of mechanical properties degradation of mechanical parts. Probability and reliability methods are appropriate for fatigue analysis using uncertainties that exist in fatigue material or process parameters. Current work deals with the study of the effect of the number and counting Rainflow cycle on fatigue lifetime (cumulative damage) of an upper arm of the vehicle suspension system. The major part of the fatigue damage induced in suspension arm is caused by two main classes of parameters. The first is related to the materials properties and the second is the road excitation or the applied force of the passenger’s number. Therefore, Young's modulus and road excitation are selected as input parameters to conduct repetitive simulations by Monte Carlo (MC) algorithm. Latin hypercube sampling method is used to generate these parameters. Response surface method is established according to fatigue lifetime of each combination of input parameters according to strain-life method. A PYTHON script was developed to automatize finite element simulations of the upper arm according to a design of experiments.

Keywords: fatigue, monte carlo, rainflow cycle, response surface, suspension system

Procedia PDF Downloads 248

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 179

Authors: Xiaoming Jiang, Jinqiao Shi, Qingfeng Tan, Wentao Zhang, Xuebin Wang, Muqian Chen

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Nowadays, big companies such as Google, Microsoft, which have adequate proxy servers, have perfectly implemented their web crawlers for a certain website in parallel. But due to lack of expensive proxy servers, it is still a puzzle for researchers to crawl large amounts of information from a single website in parallel. In this case, it is a good choice for researchers to use free public proxy servers which are crawled from the Internet. In order to improve efficiency of web crawler, the following two issues should be considered primarily: (1) Tasks may fail owing to the instability of free proxy servers; (2) A proxy server will be blocked if it visits a single website frequently. In this paper, we propose Proxisch, an optimization approach of large-scale unstable proxy servers scheduling, which allow anyone with extremely low cost to run a web crawler efficiently. Proxisch is designed to work efficiently by making maximum use of reliable proxy servers. To solve second problem, it establishes a frequency control mechanism which can ensure the visiting frequency of any chosen proxy server below the website’s limit. The results show that our approach performs better than the other scheduling algorithms.

Keywords: proxy server, priority queue, optimization algorithm, distributed web crawling

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Authors: Yuling Cui, Danhao Deng, Chaowei Wang, Weidong Wang

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In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods.

Keywords: UAV trajectory design, power allocation, energy efficient, downlink throughput, deep reinforcement learning, DDPG

Procedia PDF Downloads 138

Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

Procedia PDF Downloads 186

Authors: Paffrath Meinhard, Zhou Yayun, Guo Yiqing, Ertl Harald

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Winding geometry design is an important part of power transformer electrical design. Conventionally, the winding geometry is designed manually, which is a time-consuming job because it involves many iteration steps in order to meet all cost, manufacturing and electrical requirements. Here a method is presented which automatically generates the winding geometry for given user parameters and allows the user to interactively set and change parameters. To achieve this goal, the winding problem is transferred to a mixed integer nonlinear optimization problem. The relevant geometrical design parameters are defined as optimization variables. The cost and other requirements are modeled as constraints. For the solution, a stochastic ant colony optimization algorithm is applied. It is well-known, that an optimizer can get stuck in a local minimum. For the winding problem, we present efficient strategies to come out of local minima, furthermore a reduced variable search range helps to accelerate the solution process. Numerical examples show that the optimization result is delivered within seconds such that the user can interactively change the variable search area and constraints to improve the design.

Keywords: ant colony optimization, mixed integer nonlinear programming, power transformer, winding design

Procedia PDF Downloads 371

Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Lien Gysens, Bert Vanmechelen, Maarten Haspeslagh, Piet Maes, Ann Martens

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Bovine papillomavirus (BPV) types 1 and 2 play a central role in the etiology of the most common neoplasm in horses, the equine sarcoid. The unknown mechanism behind the unique variety in a clinical presentation on the one hand and the host-dependent clinical outcome of BPV-1 infection, on the other hand, indicate the involvement of additional factors. Earlier studies have reported the potential functional significance of intratypic sequence variants, along with the existence of sarcoid-sourced BPV variants. Therefore, intratypic sequence variation seems to be an important emerging viral factor. This study aimed to give a broad insight in sarcoid-sourced BPV variation and explore its potential association with disease presentation. In order to do this, a nanopore sequencing approach was successfully optimized for screening a wide spectrum of clinical samples. Specimens of each tumour were initially screened for BPV-1/-2 by quantitative real-time PCR. A custom-designed primer set was used on BPV-positive samples to amplify the complete viral genome in two multiplex PCR reactions, resulting in a set of overlapping amplicons. For phylogenetic analysis, separate alignments were made of all available complete genome sequences for BPV-1/-2. The resulting alignments were used to infer Bayesian phylogenetic trees. We found substantial genetic variation among sarcoid-derived BPV-1, although this variation could not be linked to disease severity. Several of the BPV-1 genomes had multiple major deletions. Remarkably, the majority of the cluster within the region coding for late viral genes. Together with the extensiveness (up to 603 nucleotides) of the described deletions, this suggests an altered function of L1/L2 in disease pathogenesis. By generating a significant amount of complete-length BPV genomes, we succeeded in introducing next-generation sequencing into veterinary research focusing on the equine sarcoid, thus facilitating the first report of both nanopore-based sequencing of complete sarcoid-sourced BPV-1/-2 and the simultaneous nanopore sequencing of multiple complete genomes originating from a single clinical sample.

Keywords: Bovine papillomavirus, equine sarcoid, horse, nanopore sequencing, phylogenetic analysis

Procedia PDF Downloads 169

Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: brain-machine interface, EEGLAB, emotiv EEG neuroheadset, OpenViBE, simulink

Procedia PDF Downloads 487

Authors: Shinta Holdsworth, Jan Axmacher, Darren J. Mann

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Beetles represent the most diverse insect taxon, and they contribute significantly to a wide range of vital ecological functions. Examples include decomposition by bark beetles, nitrogen recycling and dung processing by dung beetles or pest control by predatory ground beetles. Nonetheless, research into the distribution patterns, species richness and functional diversity of beetles particularly from tropical regions remains extremely limited. In our research, we aim to investigate the distribution and diversity patterns of beetles and the roles they play in small tropical island ecosystems in the Kepulauan Seribu Marine National Park and on Java. Our research furthermore provides insights into the effects anthropogenic activities have on the assemblage composition and diversity of beetles on the small islands. We recorded a substantial number of highly abundant small island species, including a substantial number of unique small island species across the study area, highlighting these islands’ potential importance for the regional conservation of genetic resources. The highly varied patterns observed in relation to the use of different trapping types - pitfall traps and flight interception traps (FITs) - underscores the need for complementary trapping strategies that combine multiple methods for beetle community surveys in tropical islands. The significant impacts of human activities have on the small island beetle faunas were also highlighted in our research. More island beetle species encountered in settlement than forest areas shows clear trend of positive links between anthropogenic activities and the overall beetle species richness. However, undisturbed forests harboured a high number of unique species, also in comparison to disturbed forests. Finally, our study suggests that, with regards to different feeding guilds, the diversity of herbivorous beetles on islands is strongly affected by the different levels of forest cover encountered.

Keywords: beetle diversity, forest disturbance, island biogeography, island settlement

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Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

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Authors: Maryam Kalkatechi

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The paper presents the construction unit that was proposed as a result of researching and finding solutions for challenges of the traditional masonry unit. The concept of ‘unit as arrangements of cells’ was investigated in four categories of structure, handling and assembly, thermal characteristics and weather ability which resulted in construction unit as an independent system which shapes a part of the envelope. Comparing to the traditional wall systems in which the system is in layers, the part system is a monolithic piece by itself. Even though the overall wythe-10 inches- is less than the combined layers-14 inches- in a traditional wall system, it is still seen as a spatial component. The component as a furnishing of envelope is discussed from material application point of view. The algorithm definition of the arrangement cells crafts the relationship between cells and functionality with material. This craft is realized as the envelope furnishing. Three alternative materials in relation to furnishing the envelope are discussed for printing the construction unit; transparent plastic, opaque plastic and glass. The qualities vary in the four categories, however this paper focuses on the visual qualities of materials applied. In a diagram the qualities of the materials are compared in relation to each other.

Keywords: furnishing envelope, 3D printed construction unit, opaque plastic, transparent plastic, glass

Procedia PDF Downloads 170

Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary Design Optimisation, Rule Based Architecture, Aircraft Design, Decision Support System

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Salina Yahya Saddick

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Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

Procedia PDF Downloads 368

Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

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Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

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Authors: Mohammad Pourmohammadi Fallah, Maziar Salahi

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In the literature, a mixed-integer linear programming model for the integrated production planning and warehouse layout problem is proposed. To solve the model, the authors proposed a Lagrangian relax-and-fix heuristic that takes a significant amount of time to stop with gaps above 5$\%$ for large-scale instances. Here, we present two heuristic algorithms to solve the problem. In the first one, we use a greedy approach by allocating warehouse locations with less reservation costs and also less transportation costs from the production area to locations and from locations to the output point to items with higher demands. Then a smaller model is solved. In the second heuristic, first, we sort items in descending order according to the fraction of the sum of the demands for that item in the time horizon plus the maximum demand for that item in the time horizon and the sum of all its demands in the time horizon. Then we categorize the sorted items into groups of 3, 4, or 5 and solve a small-scale optimization problem for each group, hoping to improve the solution of the first heuristic. Our preliminary numerical results show the effectiveness of the proposed heuristics.

Keywords: capacitated lot-sizing, warehouse layout, mixed-integer linear programming, heuristics algorithm

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Authors: Tugba Altin

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In a time characterized by escalating climate change impacts, communities globally face extreme events with deep-reaching tangible and intangible consequences. At the intersection of these phenomena lies the profound impact on the cultural and emotional connections that individuals forge with their environments. This study casts a spotlight on the Lytton Creek Fire of 2021, showcasing it as an exemplar of both the visible destruction brought by such events and the more covert yet deeply impactful disturbances to place attachment (PA). Defined as the emotional and cognitive bond individuals form with their surroundings, PA is critical in comprehending how such catastrophic events reshape cultural identity and the bond with the land. Against the stark backdrop of the Lytton Creek Fire's devastation, the research seeks to unpack the multilayered dynamics of PA amidst the tangible wreckage and the intangible repercussions such as emotional distress and disrupted cultural landscapes. Delving deeper, it examines how affected populations renegotiate their affiliations with these drastically altered environments, grappling with both the tangible loss of their homes and the intangible challenges to solace, identity, and community cohesion. This exploration is instrumental in the broader climate change narrative, as it offers crucial insights into how these personal-place relationships can influence and shape climate adaptation and recovery strategies. Departing from traditional data collection methodologies, this study adopts an interpretive phenomenological approach enriched by hermeneutic insights and places the experiences of the Lytton community and its co-researchers at its core. Instead of conventional interviews, innovative methods like walking audio sessions and photo elicitation are employed. These techniques allow participants to immerse themselves back into the environment, reviving and voicing their memories and emotions in real-time. Walking audio captures reflections on spatial narratives after the trauma, whereas photo voices encapsulate the intangible emotions, presenting a visual representation of place-based experiences. Key findings emphasize the indispensability of addressing both the tangible and intangible traumas in community recovery efforts post-disaster. The profound changes to the cultural landscape and the subsequent shifts in PA underscore the need for holistic, culturally attuned, and emotionally insightful adaptation strategies. These strategies, rooted in the lived experiences and testimonies of the affected individuals, promise more resonant and effective recovery efforts. The research further contributes to climate change discourse, highlighting the intertwined pathways of tangible reconstruction and the essentiality of emotional and cultural rejuvenation. Furthermore, the use of participatory methodologies in this inquiry challenges traditional research paradigms, pointing to potential evolutionary shifts in qualitative research norms. Ultimately, this study underscores the need for a more integrative approach in addressing the aftermath of environmental disasters, ensuring that both physical and emotional rebuilding are given equal emphasis.

Keywords: place attachment, community recovery, disaster reponse, sensory responses, intangible traumas, visual methodologies

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Dawit Gebreegzabher Hagos, Yazezew Kebede Kiro, Mahmud Abdulkader, Henk H. D. F. Schallig, Dawit Wolday

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Rapid and accurate visceral leishmaniasis (VL) diagnosis is needed to initiate prompt treatment to reduce morbidity and mortality. Here, we evaluated the performance of loop-mediated isothermal amplification (LAMP) assay for the diagnosis of VL from blood in an endemic area in Ethiopia. LAMP was positive in 117/122 confirmed VL cases and negative in 149/152 controls, resulting in a sensitivity of 95.9% (95% CI: 90.69–98.66) and a specificity of 98.0% (95% CI: 94.34–99.59), respectively. The sensitivity of the LAMP assay was 95.0% (95% CI: 88.61–98.34) in HIV-negatives and 100% (95% CI: 85.18–100.0) in HIV-positives. Compared with microscopy, LAMP detected 82/87 (94.3%, 95% CI: 87.10–98.11) of the microscopy1 cases and was negative in 11/27 (40.7%, 95% CI: 22.39–61.20) of the microscopy2 cases. Compared with the rK39 serology, LAMP detected 113/120 (94.2%, 95% CI: 88.35–97.62) of the rK391 cases and was negative in 149/154 (96.8%, 95% CI: 92.59–98.94) of the rK392 cases. However, when compared with microscopy only, rK39 detected 83/87 (95.4%, 95% CI: 88.64–98.73) of the microscopy1 cases and negative in only 12/27 (44.4%, 95% CI: 25.48–64.67) of the microscopy– cases. There was an excellent agreement between rK39 and LAMP (Kappa 5 0.91, 95% CI: 0.86–0.96). Furthermore, an algorithm using rK39 followed by LAMP would yield a sensitivity of 99.2% (95%CI: 95.52–99.89) and a specificity of 98.0% (95% CI: 94.34–99.59). The findings demonstrate that the LAMP assay is an accurate and rapid molecular assay for VL diagnosis, including in HIV-1 co-infected patients, in an endemic setting.

Keywords: visceral leishmaniasis, HIV, diagnosis, LAMP, Ethiopia

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Authors: Gulnaz Khan, Meha F. Aftab, Munazza Murtaza, Rizwana S. Waraich

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Advanced glycation end products (AGEs) precursor and its abnormal accumulation cause damage to various tissues and organs. AGEs have pathogenic implication in several diseases including diabetes. Existing AGEs inhibitors are not in clinical use, and there is a need for development of novel inhibitors. The present investigation aimed at identifying the novel AGEs inhibitors and assessing their mechanism of action for treating insulin resistance in mice model of diabetes. Novel derivatives of benzylidene of indan-1,3-dione were synthesized. The compounds were selected to study their action mechanism in improving insulin resistance, in vitro, in human hepatocytes and murine adipocytes and then, in vivo, in mice genetic model of diabetes (db/db). Mice were treated with novel derivatives of benzylidene of indane 1,3-dione. AGEs mediated ROS production was measured by dihydroethidium fluorescence assay. AGEs level in the serum of treated mice was observed by ELISA. Gene expression of receptor for AGEs (RAGE), PPAR-gamma, TNF-alpha and GLUT-4 was evaluated by RT-PCR. Glucose uptake was measured by fluorescent method. Microscopy was used to analyze glycogen synthesis in muscle. Among several derivatives of benzylidene of indan-1,3-dione, IDD-24, demonstrated highest inhibition of AGESs. IDD-24 significantly reduced AGEs formation and expression of receptor for advanced glycation end products (RAGE) in fat, liver of db/db mice. Suppression of AGEs mediated ROS production was also observed in hepatocytes and fat cell, after treatment with IDD-24. Glycogen synthesis was increased in muscle tissue of mice treated with IDD-24. In adipocytes, IDD-24 prevented AGEs induced reduced glucose uptake. Mice treated with IDD-24 exhibited increased glucose tolerance, serum adiponectin levels and decreased insulin resistance. The result of present study suggested that IDD-24 can be a possible treatment target to address glycotoxins induced insulin resistance.

Keywords: advance glycation end product, hyperglycemia, indan-1, 3-dione, insulin resistance

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Authors: Sidi Mohamed Mesli, Mohamed Habchi, Mohamed Kotbi, Rafik Benallal, Abdelali Derouiche

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Fluoride glasses with a nominal composition of BaMnMF7 (M = FeV assuming isomorphous replacement) have been structurally modelled through the simultaneous simulation of their neutron diffraction patterns by a reverse Monte Carlo (RMC) model and by a Rietveld for disordered materials (RDM) method. Model is consistent with an expected network of interconnected [MF6] polyhedra. The RMC results are accompanied by artificial satellite peaks. To remedy this problem, we use an extension of the RMC algorithm, which introduces an energy penalty term in acceptance criteria. This method is called the Hybrid Reverse Monte Carlo (HRMC) method. The idea of this paper is to apply the (HRMC) method to the title glasses, in order to make a study of the phenomenon nature of order and disorder by displaying and discussing the partial pair distribution functions (PDFs) g(r). We suggest that this method can be used to describe average correlations between components of fluoride glass or similar system.

Keywords: fluoride glasses, RMC simulation, neutron scattering, hybrid RMC simulation, Lennard-Jones potential, partial pair distribution functions

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Authors: Prakash Thapa, Gye Choon Park, Sung Gi Kwon, Jin Lee

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The generation of electric power from a proton exchange membrane (PEM) fuel cell is influenced by temperature, pressure, humidity, flow rate of reactant gaseous and partial flooding of membrane electrode assembly (MEA). Among these factors, temperature and cathode flooding are the most affecting parameters on the performance of fuel cell. This paper describes the detail design and effect of these parameters on PEM fuel cell. Performance of all parameters was monitored, analyzed and controlled by using 5KWatt PEM fuel cell. In the real-time data communication for remote monitoring and control of PEM fuel cell, a normalized least mean square algorithm in cognitive radio environment is used. By the use of this method, probability of energy signal detection will be maximum which solved the frequency shortage problem. So the monitoring system hanging out and slow speed problem will be solved. Also from the control unit, all parameters are controlled as per the system requirement. As a result, PEM fuel cell generates maximum electricity with better performance.

Keywords: proton exchange membrane (PEM) fuel cell, pressure, temperature and humidity sensor (PTH), efficiency curve, cognitive radio network (CRN)

Procedia PDF Downloads 448