Search results for: miRNA:mRNA interaction network

Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

Abstract:

The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

Procedia PDF Downloads 274

Authors: Henok Mezemr Besfat, Haftom Gebreslassie Gebregwergs

Abstract:

wireless network is one of the most important mediums of transmission of information from one device to another devices. Wireless communication has a broad range of applications, including mobile communications through cell phones and satellites, Internet of Things (IoT) connecting several devices, wireless sensor networks for traffic management and environmental monitoring, satellite communication for weather forecasting and TV without requiring any cable or wire or other electronic conductors, by using electromagnetic waves like IR, RF, satellite, etc. This paper summarizes different wireless network technologies, applications of different wireless technologies and different types of wireless networks. Generally, wireless technology will further enhance operations and experiences across sectors with continued innovation. This paper suggests different strategies that can improve wireless networks and technologies.

Keywords: wireless senser, wireless technology, wireless network, internet of things

Procedia PDF Downloads 37

Authors: Oluwaponmile David Alao

Abstract:

Misdiagnosis has been the major problem in health sector. Heart attack has been one of diseases that have high level of misdiagnosis recorded on the part of physicians. In this paper, an intelligent system has been developed for diagnosis of heart attack in the health sector. Dataset of heart attack obtained from UCI repository has been used. This dataset is made up of thirteen attributes which are very vital in diagnosis of heart disease. The system is developed on the multilayer perceptron trained with back propagation neural network then simulated with feed forward neural network and a recognition rate of 87% was obtained which is a good result for diagnosis of heart attack in medical field.

Keywords: heart attack, artificial neural network, diagnosis, intelligent system

Procedia PDF Downloads 646

Authors: Sina Mahdavi, Mahdi Asghari Ozma

Abstract:

Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human Varicella-zoster virus (VZV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on VZV retrovirus infection in MS disease progression. For this study, the keywords "Multiple sclerosis", " Human Varicella-zoster virus ", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched and 14 articles were chosen, studied, and analyzed. Analysis of the amino acid sequences of HNRNPA1 with VZV proteins has shown a 62% amino acid sequence similarity between VZV gE and the PrLD/M9 epitope region (TNPO1 binding domain) of mutant HNRNPA1. A heterogeneous nuclear ribonucleoprotein (hnRNP), which is produced by HNRNPA1, is involved in the processing and transfer of mRNA and pre-mRNA. Mutant HNRNPA1 mimics gE of VZV as an antigen that leads to autoantibody production. Mutant HnRNPA1 translocates to the cytoplasm, after aggregation is presented by MHC class I, followed by CD8 + cells. Of these, antibodies and immune cells against the gE epitopes of VZV remain due to the memory immune response, causing neurodegeneration and the development of MS in genetically predisposed individuals. VZV expression during the course of MS is present in genetically predisposed individuals with HNRNPA1 mutation, suggesting a link between VZV and MS, and that this virus may play a role in the development of MS by inducing an inflammatory state. Therefore, measures to modulate VZV expression may be effective in reducing inflammatory processes in demyelinated areas of MS patients in genetically predisposed individuals.

Keywords: multiple sclerosis, varicella-zoster virus, central nervous system, autoimmunity

Procedia PDF Downloads 69

Authors: İkbal Eski

Abstract:

This investigation is researched on design of robust neural network predictors for analyzing vibration effects on moving parts of a drilling machine. Moreover, the research is divided two parts; first part is experimental investigation, second part is simulation analysis with neural networks. Therefore, a real time the drilling machine is used to vibrations during working conditions. The measured real vibration parameters are analyzed with proposed neural network. As results: Simulation approaches show that Radial Basis Neural Network has good performance to adapt real time parameters of the drilling machine.

Keywords: artificial neural network, vibration analyses, drilling machine, robust

Procedia PDF Downloads 383

Authors: Safak Baykal

Abstract:

The purpose of this study is analyzing the relationship between self leadership and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: bonding, homophilous social capital (BoSC) which implies better, strong, dense or closed network ties, and bridging, heterophilous social capital (BrSC) which implies weak ties, bridging the structural holes. The other concept of the study is Trust (Tr), namely interpersonal trust, willingness to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.73 and social capital values (BoSC/BrSC) is highly correlated with Tr values of the people.

Keywords: bonding social capital, bridging social capital, trust, social network analysis (SNA)

Procedia PDF Downloads 518

Authors: Ruth Manzanares, Victor Honores, Hugo Zapata, Javier Cansaya, Deivid Yavar, Junior Meza

Abstract:

LogiSum is a robot focused on education like a solution to the ecological crisis. This robot allows reducing the pollution on the beaches by stimulating environmental awareness of not contaminating through the collection of waste. Through the use of the methodology of design thinking, it is intended to reinforce values in adults and with a greater focus on children, so as not to contaminate the beaches. The goal is to encourage the use of the container of the robot LogiSum to put the garbage, with visual interaction and simulation of dialogue with the function of the robot. The results obtained of the testings of the interaction of children with the robot showed an encouraging behavior. With the robot, children left the waste in the right places and not bury it in the sand or in the floor.

Keywords: interaction human-robot, pollution reduction, social robot, robot container, beach pollution

Procedia PDF Downloads 253

Authors: Chengliang Xie, Jinhyun Ryu, Hyun Joon Kim, Gyeong Jae Cho, Wan Sung Choi, Sang Soo Kang, Kye Man Cho, Dong Hoon Lee

Abstract:

Obesity has become a global health problem and a source of major metabolic diseases like type-2 diabetes, hypertension, heart disease, nonalcoholic fatty liver and cancer. Synthetic anti-obesity drugs are effective but very costly and with undesirable side effects, so natural products such as soybean are needed as an alternative for obesity treatment. Lactobacillus Plantarum P1201is a probiotic bacterial strain reported to produce conjugated linoleic acid (CLA) and increase the ratio of aglycone-isoflavone of soybean, both of which have anti-obesity effect. In this study, the anti-obesity effect of the fermented soybean extract with P1201 (FSE) will be evaluated compared with that of the soybean extract (SE) by 3T3-L1 cells as an in vitro model of adipogenesis. 3T3-L1 cells were treated with SE and FSE during the nine days of the differentiation, lipid accumulation was evaluated by oil-red staining and triglyceride content and the mRNA expression level of adipogenic or lipogenic genes were analyzed by RT-PCR and qPCR. The results showed that formation of lipid droplets in differentiated 3T3-L1 cells was inhibited and triglyceride content was reduced by 23.1% after treated with 1000 μg/mL of FSE compared with control. For SE-treated groups, no delipidating effect was observed. The effect of FSE on adipogenesis inhibition can be attributed to the down-regulation of mRNA expressionof CCAAT/enhancer binding protein (C/EBP-α), lipoprotein lipase (LPL), adiponectin, adipocyte fatty acid-binding protein (aP2), fatty acid synthesis (FAS) and CoA carboxylase (ACC). Our results demonstrated that the anti-obesity effect of soybean can be improved by fermentation with P1201, and P1201can be used as a potential probiotic bacterial strain to produce natural anti-obesity food.

Keywords: fermentation, Lactobacillus plantarum P1201, obesity, soybean

Procedia PDF Downloads 326

Authors: Ali̇ Bayram, Semih Dalkilic, Remzi Yigiter

Abstract:

N-methyl-D-aspartate (NMDA) receptor is a subtype of glutamate receptor and plays a pivotal role in learning, memory, neuronal plasticity, neurotoxicity and synaptic mechanisms. Animal experiments were suggested that glutamate-induced excitotoxic injuriy and NMDA receptor blockage lead to amnesia and other neurodegenerative diseases including Alzheimer’s disease (AD), Huntington’s disease, amyotrophic lateral sclerosis. Aim of this study is to investigate association between NMDA receptor coding gene GRIN2B expression level and Alzheimer disease. The study was approved by the local ethics committees, and it was conducted according to the principles of the Declaration of Helsinki and guidelines for the Good Clinical Practice. Peripheral blood was collected 50 patients who diagnosed AD and 49 healthy control individuals. Total RNA was isolated with RNeasy midi kit (Qiagen) according to manufacturer’s instructions. After checked RNA quality and quantity with spectrophotometer, GRIN2B expression levels were detected by quantitative real time PCR (QRT-PCR). Statistical analyses were performed, variance between two groups were compared with Mann Whitney U test in GraphpadInstat algorithm with 95 % confidence interval and p < 0.05. After statistical analyses, we have determined that GRIN2B expression levels were down regulated in AD patients group with respect to control group. But expression level of this gene in each group was showed high variability. İn this study, we have determined that NMDA receptor coding gene GRIN2B expression level was down regulated in AD patients when compared with healthy control individuals. According to our results, we have speculated that GRIN2B expression level was associated with AD. But it is necessary to validate these results with bigger sample size.

Keywords: Alzheimer’s disease, N-methyl-d-aspartate receptor, NR2B, GRIN2B, mRNA expression, RT-PCR

Procedia PDF Downloads 382

Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

Abstract:

The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

Procedia PDF Downloads 35

Authors: Seyede Sanaz Seyedebrahimi, Shima Rahimi, Shohreh Fakhari, Ali Jalili

Abstract:

Background: CXCR4, as a chemokine receptor, plays well-known roles in various types of cancers. Several studies have been conducted to overcome CXCR4 axis acts in multiple myeloma (MM) pathogenesis and progression. Dexamethasone, a standard treatment for multiple myeloma, has been shown to increase CXCR4 levels in multiple myeloma cell lines. Herein, we focused on the effects of metformin and dexamethasone on CXCR4 at the cellular level and the migration rate of cell lines after exposure to a combination compared to single-agent models. Materials and Method: Multiple myeloma cell lines (U266 and RPMI8226) were cultured with different metformin and dexamethasone concentrations in single-agent and combination models. The simultaneous combination doses were calculated by CompuSyn software. Cell surface and mRNA expression of CXCR4 were determined using flow cytometry and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay, respectively. The Transwell cell migration assay evaluated the migration ability. Results: In concurred with previous studies, our results showed a dexamethasone up-regulation effect on CXCR4 in a dose-dependent manner. Although, the metformin single-agent model could reduce CXCR4 expression of U266 and RPMI8226 in cell surface and mRNA expression level. Moreover, the administration of metformin and dexamethasone simultaneously exerted a higher suppression effect on CXCR4 expression than the metformin single-agent model. The migration rate through the combination model's matrigel membrane was remarkably lower than the metformin and dexamethasone single-agent model. Discussion: According to our findings, the combination of metformin and dexamethasone effectively inhibited dexamethasone-induced CXCR4 expression in multiple myeloma cell lines. As a result, metformin may be counted as an alternative medicine combined with other chemotherapies to combat multiple myeloma. However, more research is required.

Keywords: CXCR4, dexamethasone, metformin, migration, multiple myeloma

Procedia PDF Downloads 143

Authors: Andri Ottesen, Sam Toglaw, Mirna Safa

Abstract:

Entrepreneurial companies on their developing path from an idea to a corporation go through a similar six-step process. Each of these six development steps is supported by a distinctive financing path. This paper explores the Kuwait model for Entrepreneurial Finance and Development through in-depth interviews with ten successful Kuwaiti entrepreneurs. This paper offers insight into the development and financing of entrepreneurial companies in this oil-rich, predominantly Islamic country that are in many ways different from the steps. Western entrepreneurial companies go through. This model could be used to understand the commonalities and the difference between entrepreneurial development and financing and could be used to bridge the gap.

Keywords: entrepreneurial-financing, entrepreneurial-developing, Kuwait, Vancouver school

Procedia PDF Downloads 205

Authors: Mary Anne Roa

Abstract:

Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

Procedia PDF Downloads 384

Authors: Alexander Hempfing

Abstract:

The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.

Keywords: economic integration, industrial organization, input-output economics, network economics, production networks

Procedia PDF Downloads 264

Authors: M. R. Martinez-Torres, S. L. Toral, M. Olmedilla

Abstract:

Typically, virtual communities exhibit the well-known phenomenon of participation inequality, which means that only a small percentage of users is responsible of the majority of contributions. However, the sustainability of the community requires that the group of active users must be continuously nurtured with new users that gain expertise through a participation process. This paper analyzes the time evolution of Open Source Software (OSS) communities, considering users that join/abandon the community over time and several topological properties of the network when modeled as a social network. More specifically, the paper analyzes the role of those users rejoining the community and their influence in the global characteristics of the network.

Keywords: open source communities, social network Analysis, time series, virtual communities

Procedia PDF Downloads 517

Authors: Sh. Hamada

Abstract:

The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both ¹²C and ¹⁶O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+¹²C and α+¹⁶O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (N_r). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.

Keywords: density distribution, double folding, elastic scattering, nuclear rainbow, optical model

Procedia PDF Downloads 228

Authors: Melissa C. LaDuke

Abstract:

The purpose of this literature review was to identify the use of online communities of practice (CoPs) within e-learning environments as a method to build social interaction and student-centered educational experiences. A literature review was conducted to survey and collect scholarly thoughts concerning CoPs from a variety of sources. Data collected included best practices, ties to educational theories, and examples of online CoPs. Social interaction has been identified as a critical piece of the learning infrastructure, specifically for adult learners. CoPs are an effective way to help students connect to each other and the material of interest. The use of CoPs falls in line with many educational theories, including situated learning theory, social constructivism, connectivism, adult learning theory, and motivation. New literacies such as social media and gamification can help increase social interaction in online environments and provide methods to host CoPs. Steps to build and sustain a CoP were discussed in addition to CoP considerations and best practices.

Keywords: community of practice, knowledge sharing, social interaction, online course design, new literacies

Procedia PDF Downloads 85

Authors: Younghyun Jeon, Seungjoo Maeng

Abstract:

In the Ad-hoc network, the great interests regarding MIMO scheme leads to their combination, which is also utilized into its applicable network. We manage the field of the problem into Reverse-link MIMO Ad-hoc Network (RMAN) and propose the methodology to maximize the data rate with its power consumption using Node-Cooperative beamforming technique. Based on the result of mathematical optimization formulation, we design the algorithm to construct optimal orthogonal weight vector according to channel feedback and control its transmission power according to QoS-pricing value level. In simulation results, we show the validity of the proposed mathematical optimization result and algorithm which mean that the sum-rate of each link is converged into some point.

Keywords: ad-hoc network, MIMO, cooperative beamforming, transmit power

Procedia PDF Downloads 389

Authors: Alok Shiomurti Tripathi, Ajay Kumar Timiri, Papiya Mitra Mazumder, Anil Chandewar

Abstract:

The present study evaluates the possible drug interaction between glimepiride (GLIM) and sildenafil citrate (SIL) in streptozotocin (STZ) induced in diabetic nephropathic (DN) animals and also postulates the possible mechanism of interaction by molecular modeling studies. Diabetic nephropathy was induced by single dose of STZ (60 mg/kg, ip) and confirms it by assessing the blood and urine biochemical parameters on 28th day of its induction. Selected DN animals were used for the drug interaction between GLIM (0.5mg/kg, p.o.) and SIL (2.5 mg/kg, p.o.) after 29th and 70th day of protocol. Drug interaction were assessed by evaluating the plasma drug concentration using HPLC-UV and also determine the change in the biochemical parameter in blood and urine. Mechanism of the interaction was postulated by molecular modeling study using Maestro module of Schrodinger software. DN was confirmed as there was significant alteration in the blood and urine biochemical parameter in STZ treated groups. The concentration of SIL increased significantly (p<0.001) in rat plasma when co administered with GLIM after 70th day of protocol. Molecular modelling study revealed few important interactions with rat serum albumin and CYP2C9.GLIM has strong hydrophobic interaction with binding site residues of rat serum albumin compared to SIL. Whereas, for CYP2C9, GLIM has strong hydrogen bond with polar contacts and hydrophobic interactions than SIL. Present study concludes that bioavailability of SIL increases when co-administered chronically with GLIM in the management of DN animals and mechanism has been supported by molecular modeling studies.

Keywords: diabetic nephropathy, glimepiride, sildenafil citrate, pharmacokinetics, homology modeling, schrodinger

Procedia PDF Downloads 367

Authors: Sultan Noman Qasem

Abstract:

This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

Procedia PDF Downloads 547

Authors: Widyani Fatwa Dewi, Subroto Athor

Abstract:

In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

Procedia PDF Downloads 158

Authors: Yili Wang, Jarmo Kinos, Tuire Palonen, Tarja-Riitta Hurme

Abstract:

This longitudinal study aims to examine how five- and six-year-old children’s peer relationships are formed and fostered during one preschool year in a southwestern Finnish preschool. All 16 kindergarteners participated in the study (at dyad level N=240; i.e., 16 x 15 relationships among the children). The children were divided into four daily groups, based on the table order during the daily routines, and four intervention groups, based on the teachers’ pedagogical plan. During the intervention, one iPad was given to each group in order to stimulate interaction among peers and, thus, enable the children to form new peer relationships. In the data gathering, sociometric nomination techniques were used to investigate the nature (i.e., stability and mutuality) of the peer relationships. The data was collected five times during the year to see what kind of peer relationship changes occurred at the dyad level and the group level, i.e., in establishing and losing friendship ties among the children. Social network analyses were used to analyze the data. The results indicate that the children’s preference for gender segregation was strong compared to age preference and intervention. In all, the number of reciprocal friendship ties and the mutual absence of friendship ties increased towards the end of the year, whereas the number of unilateral friendship ties decreased. This indicates that children’s nominations narrow down; thus, the group structure becomes more crystalized. Instead of extending their friendship networks, children seek stable and mutual relationships with their peers in their middle childhood years. The intervention only had a slightly negative influence on children’s peer relationships.

Keywords: intervention study, peer relationship, preschool education, social network analysis, sociometric ratings

Procedia PDF Downloads 259

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 68

Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

Abstract:

Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

Procedia PDF Downloads 394

Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

Abstract:

In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

Procedia PDF Downloads 405

Authors: Abdelhacine Gouasmia, Abdelhamid Belkhiri, Allaeddine Athmani

Abstract:

The objective of this paper is to evaluate the effects of soil-structure interaction (SSI) on the modal characteristics and on the dynamic response of current structures. The objective is on the overall behaviour of a real structure of five storeys reinforced concrete (R/C) building typically encountered in Algeria. Sensitivity studies are undertaken in order to study the effects of frequency content of the input motion, frequency of the soil-structure system, rigidity and depth of the soil layer on the dynamic response of such structures. This investigation indicated that the rigidity of the soil layer is the predominant factor in soil-structure interaction and its increases would definitely reduce the deformation in the R/C structure. On the other hand, increasing the period of the underlying soil will cause an increase in the lateral displacements at story levels and create irregularity in the distribution of story shears. Possible resonance between the frequency content of the input motion and soil could also play an important role in increasing the structural response.

Keywords: direct method, finite element method, foundation, R/C Frame, soil-structure interaction

Procedia PDF Downloads 631

Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

Procedia PDF Downloads 512

Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

Abstract:

we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

Procedia PDF Downloads 138

Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

Abstract:

Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

Procedia PDF Downloads 148

Authors: Luciano Garelli, Marco Schauer, Jorge D’Elia, Mario A. Storti, Sabine C. Langer

Abstract:

This paper discuss a coupling strategy of two different software packages to provide fluid structure interaction (FSI) analysis. The basic idea is to combine the advantages of the two codes to create a powerful FSI solver for two and three dimensional analysis. The fluid part is computed by a program called PETSc-FEM, a software developed at Centro de Investigación de Métodos Computacionales (CIMEC). The structural part of the coupled process is computed by the research code elementary Parallel Solver (elPaSo) of the Technische Universität Braunschweig, Institut für Konstruktionstechnik (IK).

Keywords: computational fluid dynamics (CFD), fluid structure interaction (FSI), finite element method (FEM), software

Procedia PDF Downloads 546