Search results for: conventional neural network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8654

Search results for: conventional neural network

7304 Design and Simulation of MEMS-Based Capacitive Pressure Sensors

Authors: Kirankumar B. Balavalad, Bhagyashree Mudhol, B. G. Sheeparamatti

Abstract:

MEMS sensor have gained popularity in automotive, biomedical, and industrial applications. In this paper, the design and simulation of conventional, slotted, and perforated MEMS capacitive pressure sensor is proposed. Polysilicon material is used as diaphragm material that deflects due to applied pressure. Better sensitivity is the main advantage of conventional pressure sensor as compared with other two sensors and perforated pressure sensor achieves large operating pressure range. The proposed MEMS sensor demonstrated with diaphragm length 50um, gap depth 3um is being modelled. The simulation is carried out for different types of MEMS capacitive pressure sensor using COMSOL Multiphysics and Coventor ware.

Keywords: MEMS, conventional pressure sensor, slotted and perforated diaphragm, COMSOL multiphysics, coventor ware

Procedia PDF Downloads 508
7303 Understanding the Conflict Between Ecological Environment and Human Activities in the Process of Urbanization

Authors: Yazhou Zhou, Yong Huang, Guoqin Ge

Abstract:

In the process of human social development, the coupling and coordinated development among the ecological environment(E), production(P), and living functions(L) is of great significance for sustainable development. This study uses an improved coupling coordination degree model (CCDM) to discover the coordination conflict between E and human settlement environment. The main work of this study is as follows: (1) It is found that in the process of urbanization development of Ya 'an city from 2014 to 2018, the degree of coupling (DOC) value between E, P, and L is high, but the coupling coordination degree (CCD) of the three is low, especially the DOC value of E and the other two has the biggest decline. (2) A more objective weight value is obtained, which can avoid the analysis error caused by subjective judgment weight value.

Keywords: ecological environment, coupling coordination degree, neural network, sustainable development

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7302 Success Factors for Innovations in SME Networks

Authors: J. Gochermann

Abstract:

Due to complex markets and products, and increasing need to innovate, cooperation between small and medium size enterprises arose during the last decades, which are not prior driven by process optimization or sales enhancement. Especially small and medium sized enterprises (SME) collaborate increasingly in innovation and knowledge networks to enhance their knowledge and innovation potential, and to find strategic partners for product and market development. These networks are characterized by dual objectives, the superordinate goal of the total network, and the specific objectives of the network members, which can cause target conflicts. Moreover, most SMEs do not have structured innovation processes and they are not accustomed to collaborate in complex innovation projects in an open network structure. On the other hand, SMEs have suitable characteristics for promising networking. They are flexible and spontaneous, they have flat hierarchies, and the acting people are not anonymous. These characteristics indeed distinguish them from bigger concerns. Investigation of German SME networks have been done to identify success factors for SME innovation networks. The fundamental network principles, donation-return and confidence, could be confirmed and identified as basic success factors. Further factors are voluntariness, adequate number of network members, quality of communication, neutrality and competence of the network management, as well as reliability and obligingness of the network services. Innovation and knowledge networks with an appreciable number of members from science and technology institutions need also active sense-making to bring different disciplines into successful collaboration. It has also been investigated, whether and how the involvement in an innovation network impacts the innovation structure and culture inside the member companies. The degree of reaction grows with time and intensity of commitment.

Keywords: innovation and knowledge networks, SME, success factors, innovation structure and culture

Procedia PDF Downloads 283
7301 Upon One Smoothing Problem in Project Management

Authors: Dimitri Golenko-Ginzburg

Abstract:

A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

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7300 A Car Parking Monitoring System Using a Line-Topology Wireless Sensor Network

Authors: Dae Il Kim, Jungho Moon, Tae Yun Chung

Abstract:

This paper presents a car parking monitoring system using a wireless sensor network. The presented sensor network has a line-shaped topology and adopts a TDMA-based protocol for allowing multi-hop communications. Sensor nodes are deployed in the ground of an outdoor parking lot in such a way that a sensor node monitors a parking space. Each sensor node detects the availability of the associated parking space and transmits the detection result to a sink node via intermediate sensor nodes existing between the source sensor node and the sink node. We evaluate the feasibility of the presented sensor network and the TDMA-based communication protocol through experiments using 11 sensor nodes deployed in a real parking lot. The result shows that the presented car parking monitoring system is robust to changes in the communication environments and efficient for monitoring parking spaces of outdoor parking lots.

Keywords: multi-hop communication, parking monitoring system, TDMA, wireless sensor network

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7299 Research Activity in Computational Science Using High Performance Computing: Co-Authorship Network Analysis

Authors: Sul-Ah Ahn, Youngim Jung

Abstract:

The research activities of the computational scientists using high-performance computing are analyzed using bibliometric approaches. This study aims at providing computational scientists using high-performance computing and relevant policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of computational scientists using high-performance computing as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2006-2015. We extracted the author rank in the computational science field using high-performance computing by the number of papers published during ten years from 2006. Finally, we drew the co-authorship network for 50 top-authors and their coauthors and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Keywords: co-authorship network analysis, computational science, high performance computing, research activity

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7298 Neural Network-based Risk Detection for Dyslexia and Dysgraphia in Sinhala Language Speaking Children

Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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7297 DAG Design and Tradeoff for Full Live Virtual Machine Migration over XIA Network

Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

Abstract:

Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

Procedia PDF Downloads 855
7296 Application of Neuro-Fuzzy Technique for Optimizing the PVC Membrane Sensor

Authors: Majid Rezayi, Sh. Shahaboddin, HNM E. Mahmud, A. Yadollah, A. Saeid, A. Yatimah

Abstract:

In this study, the adaptive neuro-fuzzy inference system (ANFIS) was applied to obtain the membrane composition model affecting the potential response of our reported polymeric PVC sensor for determining the titanium (III) ions. The performance statistics of the artificial neural network (ANN) and linear regression models for potential slope prediction of membrane composition of titanium (III) ion selective electrode were compared with ANFIS technique. The results show that the ANFIS model can be used as a practical tool for obtaining the Nerntian slope of the proposed sensor in this study.

Keywords: adaptive neuro fuzzy inference, PVC sensor, titanium (III) ions, Nerntian slope

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7295 Analysis of the Impacts and Challenges of Conventional Solid Waste Management in Urban Centers of Developing Countries

Authors: Haruna Abdu Usman, J. Mohammed Umar, U. M. Bashir

Abstract:

Solid waste management continued to be the biggest threat to the sustainability of urban centers of developing countries. Most streets corners of these urban centers are characterized by heaps of uncollected wastes at drains, public spaces and road sides destroying the aesthetic qualities and environmental ecosystems of these cities. Also, harboring disease vectors and rodents putting the health of the populace at risk, thus posing a serious challenge to the municipalities who are in most cases responsible for the solid waste management in these cities. The typical or commonest method adapted by these agencies in dealing with the solid waste management is the conventional approach; focusing mainly on waste collection ,treatment(composting and incineration)and disposal giving little consideration to the 3RS, of waste reduce, re-used and recycled. The resultant consequence being huge budget spending in solid waste management as high as 80% but little collection rate as low as 50%. This paper attempt to analyze the impacts and effects of the conventional solid waste management practices on the stakeholders in solid waste management; the municipal authorities, the communities, formal and informal waste managers, the NGOs and CBOs and suggests appropriate measures that would lessen the effects.

Keywords: conventional waste management, solid waste, waste stakeholders, developing countries

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7294 Urban Design via Estimation Model for Traffic Index of Cities Based on an Artificial Intelligence

Authors: Seyed Sobhan Alvani, Mohammad Gohari

Abstract:

By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.

Keywords: traffic index, population growth rate, cities wideness, artificial neural network

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7293 BFDD-S: Big Data Framework to Detect and Mitigate DDoS Attack in SDN Network

Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

Abstract:

Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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7292 The Influence of Neural Synchrony on Auditory Middle Latency and Late Latency Responses and Its Correlation with Audiological Profile in Individuals with Auditory Neuropathy

Authors: P. Renjitha, P. Hari Prakash

Abstract:

Auditory neuropathy spectrum disorder (ANSD) is an auditory disorder with normal cochlear outer hair cell function and disrupted auditory nerve function. It results in unique clinical characteristic with absent auditory brainstem response (ABR), absent acoustic reflex and the presence of otoacoustic emissions (OAE) and cochlear microphonics. The lesion site could be at cochlear inner hair cells, the synapse between the inner hair cells and type I auditory nerve fibers, and/or the auditory nerve itself. But the literatures on synchrony at higher auditory system are sporadic and are less understood. It might be interesting to see if there is a recovery of neural synchrony at higher auditory centers. Also, does the level at which the auditory system recovers with adequate synchrony to the extent of observable evoke response potentials (ERPs) can predict speech perception? In the current study, eight ANSD participants and healthy controls underwent detailed audiological assessment including ABR, auditory middle latency response (AMLR), and auditory late latency response (ALLR). AMLR was recorded for clicks and ALLR was evoked using 500Hz and 2 kHz tone bursts. Analysis revealed that the participant could be categorized into three groups. Group I (2/8) where ALLR was present only for 2kHz tone burst. Group II (4/8), where AMLR was absent and ALLR was seen for both the stimuli. Group III (2/8) consisted individuals with identifiable AMLR and ALLR for all the stimuli. The highest speech identification sore observed in ANSD group was 30% and hence considered having poor speech perception. Overall test result indicates that the site of neural synchrony recovery could be varying across individuals with ANSD. Some individuals show recovery of neural synchrony at the thalamocortical level while others show the same only at the cortical level. Within ALLR itself there could be variation across stimuli again could be related to neural synchrony. Nevertheless, none of these patterns could possible explain the speech perception ability of the individuals. Hence, it could be concluded that neural synchrony as measured by evoked potentials could not be a good clinical predictor speech perception.

Keywords: auditory late latency response, auditory middle latency response, auditory neuropathy spectrum disorder, correlation with speech identification score

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7291 Capacitated Multiple Allocation P-Hub Median Problem on a Cluster Based Network under Congestion

Authors: Çağrı Özgün Kibiroğlu, Zeynep Turgut

Abstract:

This paper considers a hub location problem where the network service area partitioned into predetermined zones (represented by node clusters is given) and potential hub nodes capacity levels are determined a priori as a selection criteria of hub to investigate congestion effect on network. The objective is to design hub network by determining all required hub locations in the node clusters and also allocate non-hub nodes to hubs such that the total cost including transportation cost, opening cost of hubs and penalty cost for exceed of capacity level at hubs is minimized. A mixed integer linear programming model is developed introducing additional constraints to the traditional model of capacitated multiple allocation hub location problem and empirically tested.

Keywords: hub location problem, p-hub median problem, clustering, congestion

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7290 Evaluation of Biological Seed Coating Technology On-Field Performance of Wheat in Regenerative Agriculture and Conventional Systems

Authors: S. Brain, P. J. Storer, H. Strydom, Z. M. Solaiman

Abstract:

Increasing farmer awareness of soil health, the impact of agricultural management practices, and the requirement for high-quality agricultural produce are major factors driving the rapid adoption of biological seed treatments - currently valued globally at USD 1.5 billion. Biological seed coatings with multistrain plant beneficial microbial technology have the capability to affect plant establishment, growth, and development positively. These beneficial plant microbes can potentially increase soil health, plant yield, and nutrition – acting as bio fertilisers, rhizoremediators, phytostimulators, and stress modulators, and can ultimately reduce the overall use of agrichemicals. A field trial was conducted on MACE wheat in the central wheat belt of Western Australia to evaluate a proprietary seed coating technology (Langleys Bio-EnergeticTM Microbe blend (BMB)) on a conventional program (+/- BMB microbes) and a Regenerative Biomineral fertiliser program (+/- BMB microbes). The Conventional (+BMB) and Biomineral (+BMB) treated plants had no fungicide treatments and had no disease issues. Control (No fertiliser, No microbes), Conventional (No Microbes), and Biomineral (No Microbes) were treated with fungicides (seed dressing and foliar). From the research findings, compared to control and no microbe treatments, both the Conventional (+ BMB) and Biomineral (+ BMB) showed significant increases in Soil Carbon (SOC), Seed germination, nutrient use efficiency (NUE) of nitrogen, phosphate and mineral nutrients, grain mineral nutrient uptake, protein %, hectolitre weight, and fewer screenings, yield, and gross margins.

Keywords: biological seed coating, biomineral fertiliser, plant nutrition, regenerative and conventional agriculture

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7289 Online Pose Estimation and Tracking Approach with Siamese Region Proposal Network

Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

Abstract:

Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: computer vision, pose estimation, pose tracking, Siamese network

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7288 Laser Keratoplasty in Human Eye Considering the Fluid Aqueous Humor and Vitreous Humor Fluid Flow

Authors: Dara Singh, Keikhosrow Firouzbakhsh, Mohammad Taghi Ahmadian

Abstract:

In this paper, conventional laser Keratoplasty surgeries in the human eye are studied. For this purpose, a validated 3D finite volume model of the human eye is introduced. In this model the fluid flow has also been considered. The discretized domain of the human eye incorporates a bio-heat transfer equation coupled with a Boussinesq equation. Both continuous and pulsed lasers have been modeled and the results are compared. Moreover, two different conventional surgical positions that are upright and recumbent are compared for these laser therapies. The simulation results show that in these conventional surgeries, the temperature rises above the critical values at the laser insertion areas. However, due to the short duration and the localized nature, the potential damages are restricted to very small regions and can be ignored. The conclusion is that the present day lasers are acceptably safe to the human eye.

Keywords: eye, heat-transfer, keratoplasty laser, surgery

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7287 Design and Implementation of Campus Wireless Networking for Sharing Resources in Federal Polytechnic Bauchi, Bauchi State, Nigeria

Authors: Hassan Abubakar

Abstract:

This paper will serve as a guide to good design and implementation of wireless networking for campus institutions in Nigeria. It can be implemented throughout the primary, secondary and tertiary institutions. This paper describe the some technical functions, standard configurations and layouts of the 802.11 wireless LAN(Local Area Network) that can be implemented across the campus network. The paper also touches upon the wireless infrastructure standards involved with enhanced services, such as voice over wireless and wireless guest hotspot. The paper also touch the benefits derived from implementing campus wireless network and share some lights on how to arrive at the success in increasing the performance of wireless and using the campus wireless to share resources like software applications, printer and documents.

Keywords: networking, standards, wireless local area network (WLAN), radio frequency (RF), campus

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7286 A Survey on Intelligent Techniques Based Modelling of Size Enlargement Process for Fine Materials

Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

Abstract:

Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

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7285 Node Optimization in Wireless Sensor Network: An Energy Approach

Authors: Y. B. Kirankumar, J. D. Mallapur

Abstract:

Wireless Sensor Network (WSN) is an emerging technology, which has great invention for various low cost applications both for mass public as well as for defence. The wireless sensor communication technology allows random participation of sensor nodes with particular applications to take part in the network, which results in most of the uncovered simulation area, where fewer nodes are located at far distances. The drawback of such network would be that the additional energy is spent by the nodes located in a pattern of dense location, using more number of nodes for a smaller distance of communication adversely in a region with less number of nodes and additional energy is again spent by the source node in order to transmit a packet to neighbours, thereby transmitting the packet to reach the destination. The proposed work is intended to develop Energy Efficient Node Placement Algorithm (EENPA) in order to place the sensor node efficiently in simulated area, where all the nodes are equally located on a radial path to cover maximum area at equidistance. The total energy consumed by each node compared to random placement of nodes is less by having equal burden on fewer nodes of far location, having distributed the nodes in whole of the simulation area. Calculating the network lifetime also proves to be efficient as compared to random placement of nodes, hence increasing the network lifetime, too. Simulation is been carried out in a qualnet simulator, results are obtained on par with random placement of nodes with EENP algorithm.

Keywords: energy, WSN, wireless sensor network, energy approach

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7284 Policy Monitoring and Water Stakeholders Network Analysis in Shemiranat

Authors: Fariba Ebrahimi, Mehdi Ghorbani

Abstract:

Achieving to integrated Water management fundamentally needs to effective relation, coordination, collaboration and synergy among various actors who have common but different responsibilities. In this sense, the foundation of comprehensive and integrated management is not compatible with centralization and top-down strategies. The aim of this paper is analysis institutional network of water relevant stakeholders and water policy monitoring in Shemiranat. In this study collaboration networks between informal and formal institutions co-management process have been investigated. Stakeholder network analysis as a quantitative method has been implicated in this research. The results of this study indicate that institutional cohesion is medium; sustainability of institutional network is about 40 percent (medium). Additionally the core-periphery index has measured in this study according to reciprocity index. Institutional capacities for integrated natural resource management in regional level are measured in this study. Furthermore, the necessity of centrality reduction and promote stakeholders relations and cohesion are emphasized to establish a collaborative natural resource governance.

Keywords: policy monitoring, water management, social network, stakeholder, shemiranat

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7283 Exploring Research Trends and Topics in Intervention on Metabolic Syndrome Using Network Analysis

Authors: Lee Soo-Kyoung, Kim Young-Su

Abstract:

This study established a network related to metabolic syndrome intervention by conducting a social network analysis of titles, keywords, and abstracts, and it identified emerging topics of research. It visualized an interconnection between critical keywords and investigated their frequency of appearance to construe the trends in metabolic syndrome intervention measures used in studies conducted over 38 years (1979–2017). It examined a collection of keywords from 8,285 studies using text rank analyzer, NetMiner 4.0. The analysis revealed 5 groups of newly emerging keywords in the research. By examining the relationship between keywords with reference to their betweenness centrality, the following clusters were identified. Thus if new researchers refer to existing trends to establish the subject of their study and the direction of the development of future research on metabolic syndrome intervention can be predicted.

Keywords: intervention, metabolic syndrome, network analysis, research, the trend

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7282 Optimal Scheduling of Trains in Complex National Scale Railway Networks

Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

Abstract:

Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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7281 Fake News Detection for Korean News Using Machine Learning Techniques

Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

Abstract:

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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7280 Participation, Network, Women’s Competency, and Government Policy Affecting on Community Development

Authors: Nopsarun Vannasirikul

Abstract:

The purposes of this research paper were to study the current situations of community development, women’s potentials, women’s participation, network, and government policy as well as to study the factors influencing women’s potentials, women’s participation, network, and government policy that have on the community development. The population included the women age of 18 years old who were living in the communities of Bangkok areas. This study was a mix research method of quantitative and qualitative method. A simple random sampling method was utilized to obtain 400 sample groups from 50 districts of Bangkok and to perform data collection by using questionnaire. Also, a purposive sampling method was utilized to obtain 12 informants for an in-depth interview to gain an in-sight information for quantitative method.

Keywords: community development, participation, network, women’s right, management

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7279 Offset Dependent Uniform Delay Mathematical Optimization Model for Signalized Traffic Network Using Differential Evolution Algorithm

Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

Abstract:

A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

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7278 A Review of In-Vehicle Network for Cloud Connected Vehicle

Authors: Hanbhin Ryu, Ilkwon Yun

Abstract:

Automotive industry targets to provide an improvement in safety and convenience through realizing fully autonomous vehicle. For partially realizing fully automated driving, Current vehicles already feature varieties of advanced driver assistance system (ADAS) for safety and infotainment systems for the driver’s convenience. This paper presents Cloud Connected Vehicle (CCV) which connected vehicles with cloud data center via the access network to control the vehicle for achieving next autonomous driving form and describes its features. This paper also describes the shortcoming of the existing In-Vehicle Network (IVN) to be a next generation IVN of CCV and organize the 802.3 Ethernet, the next generation of IVN, related research issue to verify the feasibility of using Ethernet. At last, this paper refers to additional considerations to adopting Ethernet-based IVN for CCV.

Keywords: autonomous vehicle, cloud connected vehicle, ethernet, in-vehicle network

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7277 Rumour Containment Using Monitor Placement and Truth Propagation

Authors: Amrah Maryam

Abstract:

The emergence of online social networks (OSNs) has transformed the way we pursue and share information. On the one hand, OSNs provide great ease for the spreading of positive information while, on the other hand, they may also become a channel for the spreading of malicious rumors and misinformation throughout the social network. Thus, to assure the trustworthiness of OSNs to its users, it is of vital importance to detect the misinformation propagation in the network by placing network monitors. In this paper, we aim to place monitors near the suspected nodes with the intent to limit the diffusion of misinformation in the social network, and then we also detect the most significant nodes in the network for propagating true information in order to minimize the effect of already diffused misinformation. Thus, we initiate two heuristic monitor placement using articulation points and truth propagation using eigenvector centrality. Furthermore, to provide real-time workings of the system, we integrate both the monitor placement and truth propagation entities as well. To signify the effectiveness of the approaches, we have carried out the experiment and evaluation of Stanford datasets of online social networks.

Keywords: online social networks, monitor placement, independent cascade model, spread of misinformation

Procedia PDF Downloads 161
7276 Performance Analysis of Hierarchical Agglomerative Clustering in a Wireless Sensor Network Using Quantitative Data

Authors: Tapan Jain, Davender Singh Saini

Abstract:

Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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7275 Security Threats on Wireless Sensor Network Protocols

Authors: H. Gorine, M. Ramadan Elmezughi

Abstract:

In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area.

Keywords: wireless sensor networks, network security, light weight encryption, threats

Procedia PDF Downloads 526