Search results for: integrated network analysis
31693 A Remote Sensing Approach to Calculate Population Using Roads Network Data in Lebanon
Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba
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In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.Keywords: population, road network, statistical correlations, remote sensing
Procedia PDF Downloads 16131692 Cooperative Cross Layer Topology for Concurrent Transmission Scheduling Scheme in Broadband Wireless Networks
Authors: Gunasekaran Raja, Ramkumar Jayaraman
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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing
Procedia PDF Downloads 26531691 Demonstration of Powering up Low Power Wireless Sensor Network by RF Energy Harvesting System
Authors: Lim Teck Beng, Thiha Kyaw, Poh Boon Kiat, Lee Ngai Meng
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This work presents discussion on the possibility of merging two emerging technologies in microwave; wireless power transfer (WPT) and RF energy harvesting. The current state of art of the two technologies is discussed and the strength and weakness of the two technologies is also presented. The equivalent circuit of wireless power transfer is modeled and explained as how the range and efficiency can be further increased by controlling certain parameters in the receiver. The different techniques of harvesting the RF energy from the ambient are also extensive study. Last but not least, we demonstrate that a low power wireless sensor network (WSN) can be power up by RF energy harvesting. The WSN is designed to transmit every 3 minutes of information containing the temperature of the environment and also the voltage of the node. One thing worth mention is both the sensors that are used for measurement are also powering up by the RF energy harvesting system.Keywords: energy harvesting, wireless power transfer, wireless sensor network and magnetic coupled resonator
Procedia PDF Downloads 51931690 Modern Trends in Pest Management Agroindustry
Authors: Amarjit S Tanda
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Integrated Pest Management Technology (IPMT) offers a crop protection model with sustainable agriculture production with minimum damage to the environment and human health. A concept of agro-ecological crop protection seems unsuitable under dynamic environmental systems. To remedy this, we are proposing Genetically Engineered Crop Protection System (GECPS), as an alternate concept in IPMT that suggests how GE cultivars can be optimally put to the service of crop protection. Genetically engineered cultivars which are developed by gene editing biotechnology may provide a preventive defense against the insect pests and plant diseases, a suitable alternative crop system for blending in IPMT program, in the future agro-industry.Keywords: integrated, pest, management, technology
Procedia PDF Downloads 7331689 Convolutional Neural Networks versus Radiomic Analysis for Classification of Breast Mammogram
Authors: Mehwish Asghar
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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence
Procedia PDF Downloads 22531688 Application of the Sufficiency Economy Philosophy to Integrated Instructional Model of In-Service Teachers of Schools under the Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn, Nakhonnayok Educational Service Area Office
Authors: Kathaleeya Chanda
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The schools under the Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn in Nakhonnayok Educational Service Area Office are the small schools, situated in a remote and undeveloped area.Thus, the school-age youth didn’t have or have fewer opportunities to study at the higher education level which can lead to many social and economic problems. This study aims to solve these educational issues of the schools, under The Project Initiated by H.R.H Princess in Maha Chakri Sirindhorn, Nakhonnayok Educational Service Area Office, by the development of teachers, so that teachers could develop teaching and learning system with the ultimate goal to increase students’ academic achievement, increase the educational opportunities for the youth in the area, and help them learn happily. 154 in-service teachers from 22 schools and 4 different districts in Nakhonnayok participated in this teacher training. Most teachers were satisfied with the training content and the trainer. Thereafter, the teachers were given the test to assess the skills and knowledge after training. Most of the teachers earned a score higher than 75%. Accordingly, it can be concluded that after attending the training, teachers have a clear understanding of the contents. After the training session, the teachers have to write a lesson plan that is integrated or adapted to the Sufficiency Economy Philosophy. The teachers can either adopt intradisciplinary or interdisciplinary integration according to their actual teaching conditions in the school. Two weeks after training session, the researchers went to the schools to discuss with the teachers and follow up the assigned integrated lesson plan. It was revealed that the progress of integrated lesson plan could be divided into 3 groups: 1) the teachers who have completed the integrated lesson plan, but are concerned about the accuracy and consistency, 2) teachers who almost complete the lesson plan or made a great progress but are still concerned, confused in some aspects and not fill in the details of the plan, and 3), the teachers who made few progress, are uncertain and confused in many aspects, and may had overloaded tasks from their school. However, a follow-up procedure led to the commitment of teachers to complete the lesson plan. Regarding student learning assessment, from an experiment teaching, most of the students earned a score higher than 50 %. The rate is higher than the one from actual teaching. In addition, the teacher have assessed that the student is happy, enjoys learning, and providing a good cooperates in teaching activities. The students’ interview about the new lesson plan shows that they are happy with it, willing to learn, and able to apply such knowledge in daily life. Integrated lesson plan can increases the educational opportunities for youth in the area.Keywords: sufficiency, economy, philosophy, integrated education syllabus
Procedia PDF Downloads 18631687 Interbrain Synchronization and Multilayer Hyper brain Networks when Playing Guitar in Quartet
Authors: Viktor Müller, Ulman Lindenberger
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Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling
Procedia PDF Downloads 7231686 Review of Energy Efficiency Routing in Ad Hoc Wireless Networks
Authors: P. R. Dushantha Chaminda, Peng Kai
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In this review paper, we enclose the thought of wireless ad hoc networks and particularly mobile ad hoc network (MANET), their field of study, intention, concern, benefit and disadvantages, modifications, with relation of AODV routing protocol. Mobile computing is developing speedily with progression in wireless communications and wireless networking protocols. Making communication easy, we function most wireless network devices and sensor networks, movable, battery-powered, thus control on a highly constrained energy budget. However, progress in battery technology presents that only little improvements in battery volume can be expected in the near future. Moreover, recharging or substitution batteries is costly or unworkable, it is preferable to support energy waste level of devices low.Keywords: wireless ad hoc network, energy efficient routing protocols, AODV, EOAODV, AODVEA, AODVM, AOMDV, FF-AOMDV, AOMR-LM
Procedia PDF Downloads 21431685 Design and Study of a Low Power High Speed Full Adder Using GDI Multiplexer
Authors: Biswarup Mukherjee, Aniruddha Ghosal
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In this paper, we propose a new technique for implementing a low power full adder using a set of GDI multiplexers. Full adder circuits are used comprehensively in Application Specific Integrated Circuits (ASICs). Thus it is desirable to have low power operation for the sub components. The explored method of implementation achieves a low power design for the full adder. Simulated results using state-of-art Tanner tool indicates the superior performance of the proposed technique over conventional CMOS full adder. Detailed comparison of simulated results for the conventional and present method of implementation is presented.Keywords: low power full adder, 2-T GDI MUX, ASIC (application specific integrated circuit), 12-T FA, CMOS (complementary metal oxide semiconductor)
Procedia PDF Downloads 34831684 Development and Validation of First Derivative Method and Artificial Neural Network for Simultaneous Spectrophotometric Determination of Two Closely Related Antioxidant Nutraceuticals in Their Binary Mixture”
Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy
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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared togetherKeywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network
Procedia PDF Downloads 44631683 A Comparison of Methods for Neural Network Aggregation
Authors: John Pomerat, Aviv Segev
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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning
Procedia PDF Downloads 16231682 An Introductory Study on Optimization Algorithm for Movable Sensor Network-Based Odor Source Localization
Authors: Yossiri Ariyakul, Piyakiat Insom, Poonyawat Sangiamkulthavorn, Takamichi Nakamoto
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In this paper, the method of optimization algorithm for sensor network comprised of movable sensor nodes which can be used for odor source localization was proposed. A sensor node is composed of an odor sensor, an anemometer, and a wireless communication module. The odor intensity measured from the sensor nodes are sent to the processor to perform the localization based on optimization algorithm by which the odor source localization map is obtained as a result. The map can represent the exact position of the odor source or show the direction toward it remotely. The proposed method was experimentally validated by creating the odor source localization map using three, four, and five sensor nodes in which the accuracy to predict the position of the odor source can be observed.Keywords: odor sensor, odor source localization, optimization, sensor network
Procedia PDF Downloads 29931681 GIS Based Project Management Information System for Infrastructure Projects
Authors: Riki Panchal, Debasis Sarkar
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This paper describes the work done for the GIS-based project management for different infrastructure projects. It is a review paper which gives the idea of the trends in the construction project management and various models adopted for the betterment of the project planning and execution. Traditional scheduling and progress control techniques such as bar charts and the critical path method fail to provide information pertaining to the spatial aspects of a construction project. An integrated system was developed to represent construction progress not only in terms of a CPM schedule but also in terms of a graphical representation of the construction that is synchronized with the work schedule. Hence, it is suggested to work on the common platform from where all the data can be shared and analyzed.Keywords: GIS, project management, integrated model, infrastructure project
Procedia PDF Downloads 51931680 Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area
Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim
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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.Keywords: data estimation, link data, machine learning, road network
Procedia PDF Downloads 51031679 Urban Corridor Management Strategy Based on Intelligent Transportation System
Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain
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Intelligent Transportation System (ITS) is the application of technology for developing a user–friendly transportation system for urban areas in developing countries. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. This paper attempts to present the past studies regarding several ITS available that have been successfully deployed in urban corridors of India and abroad, and to know about the current scenario and the methodology considered for planning, design, and operation of Traffic Management Systems. This paper also presents the endeavor that was made to interpret and figure out the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of 6 lanes as well as 8 lanes divided road network. Two categories of data were collected on February 2016 such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, radar gun, mobile GPS and stopwatch. From analysis, the performance interpretations incorporated were identification of peak hours and off peak hours, congestion and level of service (LOS) at mid blocks, delay followed by the plotting speed contours and recommending urban corridor management strategies. From the analysis, it is found that ITS based urban corridor management strategies will be useful to reduce congestion, fuel consumption and pollution so as to provide comfort and efficiency to the users. The paper presented urban corridor management strategies based on sensors incorporated in both vehicles and on the roads.Keywords: congestion, ITS strategies, mobility, safety
Procedia PDF Downloads 44231678 Two-stage Robust Optimization for Collaborative Distribution Network Design Under Uncertainty
Authors: Reza Alikhani
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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience
Procedia PDF Downloads 6931677 Corporate Governance in Network Marketing Organizations: The Role of Ethics and CSR
Authors: Venugopal Kummamuru
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Corporate Governance (CG) is of utmost importance for running a company ethically. It is essential for the growth and success of the corporation. It is intended to increase the accountability of an organization to the larger context of the business environment. The general principles of CG include and are related to Shareholder recognition, Stakeholder interests, and focus on Corporate Social Responsibility (CSR), Clear Board responsibilities, Ethical behavior, and Business transparency. Network Marketing Organizations (NMOs) focus on marketing through direct-sales using people who are associated with the organization but are not their employees. This paper tries to study the importance of Ethics and CSR in an NMO and suggest a basic guideline for CG in NMO(s). This paper could be used as a basis or starting point for conducting an in-depth research to understand the difference in CG practices between NMO(s) and other organizations and define a standard set of guidelines for CG practice.Keywords: corporate governance, corporate responsibility, direct selling, network marketing
Procedia PDF Downloads 31831676 The Vision Baed Parallel Robot Control
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In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic
Procedia PDF Downloads 57131675 Removal of Nitenpyram from Farmland Runoff by an Integrated Ecological Ditches with Constructed Wetland System
Authors: Dan Qu, Dezhi Sun, Benhang Li
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The removal of Nitenpyram from farmland runoff by an integrated eco-ditches and constructed wetland system was investigated in the case of different HRT. Experimental results show that the removal of COD, N and P was not influenced by the Nitenpyram. When the HRT was 2.5 d, 2 d, and 1 d, the Nitenpyram removal efficiency could reach 100%, 100% and 84%, respectively. The removal efficiency in the ecological ditches was about 38%-40% in the case of different HRT, while that in the constructed wetland was influenced by the HRT variation. The optimum HRT for Nitenpyram and pollutants removal was 2 d. The substrate zeolite with soil and hollow brick layer enabled higher Nitenpyram removal rates, probably due to the cooperative phenomenon of plant uptake and microbiological deterioration as well as the adsorption by the substrate.Keywords: ecological ditch, vertical flow constructed wetland, hydraulic retention time, Nitenpyram
Procedia PDF Downloads 40131674 Advances of Image Processing in Precision Agriculture: Using Deep Learning Convolution Neural Network for Soil Nutrient Classification
Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine
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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.Keywords: convolution, feature extraction, image analysis, validation, precision agriculture
Procedia PDF Downloads 31531673 GIS Data Governance: GIS Data Submission Process for Build-in Project, Replacement Project at Oman electricity Transmission Company
Authors: Rahma Saleh Hussein Al Balushi
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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.Keywords: asset management ISO55001, standard procedures process, governance, CMMS
Procedia PDF Downloads 12531672 Integration of EEG and Motion Tracking Sensors for Objective Measure of Attention-Deficit Hyperactivity Disorder in Pre-Schoolers
Authors: Neha Bhattacharyya, Soumendra Singh, Amrita Banerjee, Ria Ghosh, Oindrila Sinha, Nairit Das, Rajkumar Gayen, Somya Subhra Pal, Sahely Ganguly, Tanmoy Dasgupta, Tanusree Dasgupta, Pulak Mondal, Aniruddha Adhikari, Sharmila Sarkar, Debasish Bhattacharyya, Asim Kumar Mallick, Om Prakash Singh, Samir Kumar Pal
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Background: We aim to develop an integrated device comprised of single-probe EEG and CCD-based motion sensors for a more objective measure of Attention-deficit Hyperactivity Disorder (ADHD). While the integrated device (MAHD) relies on the EEG signal (spectral density of beta wave) for the assessment of attention during a given structured task (painting three segments of a circle using three different colors, namely red, green and blue), the CCD sensor depicts movement pattern of the subjects engaged in a continuous performance task (CPT). A statistical analysis of the attention and movement patterns was performed, and the accuracy of the completed tasks was analysed using indigenously developed software. The device with the embedded software, called MAHD, is intended to improve certainty with criterion E (i.e. whether symptoms are better explained by another condition). Methods: We have used the EEG signal from a single-channel dry sensor placed on the frontal lobe of the head of the subjects (3-5 years old pre-schoolers). During the painting of three segments of a circle using three distinct colors (red, green, and blue), absolute power for delta and beta EEG waves from the subjects are found to be correlated with relaxation and attention/cognitive load conditions. While the relaxation condition of the subject hints at hyperactivity, a more direct CCD-based motion sensor is used to track the physical movement of the subject engaged in a continuous performance task (CPT) i.e., separation of the various colored balls from one table to another. We have used our indigenously developed software for the statistical analysis to derive a scale for the objective assessment of ADHD. We have also compared our scale with clinical ADHD evaluation. Results: In a limited clinical trial with preliminary statistical analysis, we have found a significant correlation between the objective assessment of the ADHD subjects with that of the clinician’s conventional evaluation. Conclusion: MAHD, the integrated device, is supposed to be an auxiliary tool to improve the accuracy of ADHD diagnosis by supporting greater criterion E certainty.Keywords: ADHD, CPT, EEG signal, motion sensor, psychometric test
Procedia PDF Downloads 9931671 Autism Disease Detection Using Transfer Learning Techniques: Performance Comparison between Central Processing Unit vs. Graphics Processing Unit Functions for Neural Networks
Authors: Mst Shapna Akter, Hossain Shahriar
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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.Keywords: autism disease, neural network, CPU, GPU, transfer learning
Procedia PDF Downloads 11831670 Effect of Semantic Relational Cues in Action Memory Performance over School Ages
Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharazi
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Research into long-term memory has demonstrated that the richness of the knowledge base cues in memory tasks improves retrieval process, which in turn influences learning and memory performance. The present research investigated the idea that adding cues connected to knowledge can affect memory performance in the context of action memory in children. In action memory studies, participants are instructed to learn a series of verb–object phrases as verbal learning and experience-based learning (learning by doing and learning by observation). It is well established that executing action phrases is a more memorable way to learn than verbally repeating the phrases, a finding called enactment effect. In the present study, a total of 410 students from four grade groups—2nd, 4th, 6th, and 8th—participated in this study. During the study, participants listened to verbal action phrases (VTs), performed the phrases (SPTs: subject-performed tasks), and observed the experimenter perform the phrases (EPTs: experimenter-performed tasks). During the test phase, cued recall test was administered. Semantic relational cues (i.e., well-integrated vs. poorly integrated items) were manipulated in the present study. In that, the participants were presented two lists of action phrases with high semantic integration between verb and noun, e.g., “write with the pen” and with low semantic integration between verb and noun, e.g., “pick up the glass”. Results revealed that experience-based learning had a better results than verbal learning for both well-integrated and poorly integrated items, though manipulations of semantic relational cues can moderate the enactment effect. In addition, children of different grade groups outperformed for well- than poorly integrated items, in flavour of older children. The results were discussed in relation to the effect of knowledge-based information in facilitating retrieval process in children.Keywords: action memory, enactment effect, knowledge-based cues, school-aged children, semantic relational cues
Procedia PDF Downloads 27531669 Axial Flux Permanent Magnet Motor Design and Optimization by Using Artificial Neural Networks
Authors: Tugce Talay, Kadir Erkan
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In this study, the necessary steps for the design of axial flow permanent magnet motors are shown. The design and analysis of the engine were carried out based on ANSYS Maxwell program. The design parameters of the ANSYS Maxwell program and the artificial neural network system were established in MATLAB and the most efficient design parameters were found with the trained neural network. The results of the Maxwell program and the results of the artificial neural networks are compared and optimal working design parameters are found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design and the cogging torque was examined and design studies were carried out to reduce the cogging torque.Keywords: AFPM, ANSYS Maxwell, cogging torque, design optimisation, efficiency, NNTOOL
Procedia PDF Downloads 21931668 Identifying Concerned Citizen Communication Style During the State Parliamentary Elections in Bavaria
Authors: Volker Mittendorf, Andre Schmale
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In this case study, we want to explore the Twitter-use of candidates during the state parliamentary elections-year 2018 in Bavaria, Germany. This paper focusses on the seven parties that probably entered the parliament. Against this background, the paper classifies the use of language as populism which itself is considered as a political communication style. First, we determine the election campaigns which started in the years 2017 on Twitter, after that we categorize the posting times of the different direct candidates in order to derive ideal types from our empirical data. Second, we have done the exploration based on the dictionary of concerned citizens which contains German political language of the right and the far right. According to that, we are analyzing the corpus with methods of text mining and social network analysis, and afterwards we display the results in a network of words of concerned citizen communication style (CCCS).Keywords: populism, communication style, election, text mining, social media
Procedia PDF Downloads 14931667 The Role of Land Consolidation to Reduce Soil Degradation in the Czech Republic
Authors: Miroslav Dumbrovsky
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The paper deals with positive impacts of land consolidation on decreasing soil degradation with the main emphasis on soil and water conservation in the landscape. The importance of land degradation is very high because of its impact on crop productivity and many other adverse effects. Soil degradation through soil erosion is causing losses in crop productivity and quality of the environment, through decreasing quality of soil and water (especially water resources). Negative effects of conventional farming practices are increased water erosion, as well as crusting and compaction of the topsoil and subsoil. Soil erosion caused by water destructs the soil’s structure, reduces crop productivity due to deterioration in soil physical and chemical properties such as infiltration rate, water holding capacity, loss of nutrients needed for crop production, and loss of soil carbon. Recently, a new process of complex land consolidation in the Czech Republic has provided a unique opportunity for improving the quality of the environment and sustainability of the crop production by means a better soil and water conservation. The present process of the complex land consolidation is not only a reallocation of plots, but this system consists of a new layout of plots within a certain territory, aimed at establishing the integrated land-use economic units, based on the needs of individual landowners and land users. On the other hand, the interests of the general public and the environmental protection have to be solved, too. From the general point of view, a large part of the Czech landscape shall be reconstructed in the course of complex land consolidation projects. These projects will be based on new integrated soil-economic units, spatially arranged in a designed multifunctional system of soil and water conservation measures, such as path network and a territorial system of ecological stability, according to structural changes in agriculture. This new approach will be the basis of a rational economic utilization of the region which will comply with the present ecological and aesthetic demands at present.Keywords: soil degradation, land consolidation, soil erosion, soil conservation
Procedia PDF Downloads 35631666 A Comparison between Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process for Rationality Evaluation of Land Use Planning Locations in Vietnam
Authors: X. L. Nguyen, T. Y. Chou, F. Y. Min, F. C. Lin, T. V. Hoang, Y. M. Huang
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In Vietnam, land use planning is utilized as an efficient tool for the local government to adjust land use. However, planned locations are facing disapproval from people who live near these planned sites because of environmental problems. The selection of these locations is normally based on the subjective opinion of decision-makers and is not supported by any scientific methods. Many researchers have applied Multi-Criteria Analysis (MCA) methods in which Analytic Hierarchy Process (AHP) is the most popular techniques in combination with Fuzzy set theory for the subject of rationality assessment of land use planning locations. In this research, the Fuzzy set theory and Analytic Network Process (ANP) multi-criteria-based technique were used for the assessment process. The Fuzzy Analytic Hierarchy Process was also utilized, and the output results from two methods were compared to extract the differences. The 20 planned landfills in Hung Ha district, Thai Binh province, Vietnam was selected as a case study. The comparison results indicate that there are different between weights computed by AHP and ANP methods and the assessment outputs produced from these two methods also slight differences. After evaluation of existing planned sites, some potential locations were suggested to the local government for possibility of land use planning adjusts.Keywords: Analytic Hierarchy Process, Analytic Network Process, Fuzzy set theory, land use planning
Procedia PDF Downloads 42131665 Implementation of Real-Time Multiple Sound Source Localization and Separation
Authors: Jeng-Shin Sheu, Qi-Xun Zheng
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This paper mainly discusses a method of separating speech when using a microphone array without knowing the number and direction of sound sources. In recent years, there have been many studies on the method of separating signals by using masking, but most of the separation methods must be operated under the condition of a known number of sound sources. Such methods cannot be used for real-time applications. In our method, this paper uses Circular-Integrated-Cross-Spectrum to estimate the statistical histogram distribution of the direction of arrival (DOA) to obtain the number of sound sources and sound in the mixed-signal Source direction. In calculating the relevant parameters of the ring integrated cross-spectrum, the phase (Phase of the Cross-Power Spectrum) and phase rotation factors (Phase Rotation Factors) calculated by the cross power spectrum of each microphone pair are used. In the part of separating speech, it uses the DOA weighting and shielding separation method to calculate the sound source direction (DOA) according to each T-F unit (time-frequency point). The weight corresponding to each T-F unit can be used to strengthen the intensity of each sound source from the T-F unit and reduce the influence of the remaining sound sources, thereby achieving voice separation.Keywords: real-time, spectrum analysis, sound source localization, sound source separation
Procedia PDF Downloads 15531664 A Connected Structure of All-Optical Logic Gate “NOT-AND”
Authors: Roumaissa Derdour, Lebbal Mohamed Redha
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We present a study of the transmission of the all-optical logic gate using a structure connected with a triangular photonic crystal lattice that is improved. The proposed logic gate consists of a photonic crystal nano-resonator formed by changing the size of the air holes. In addition to the simplicity, the response time is very short, and the designed nano-resonator increases the bit rate of the logic gate. The two-dimensional finite difference time domain (2DFDTD) method is used to simulate the structure; the transmission obtained is about 98% with very negligible losses. The proposed photonic crystal AND logic gate is widely used in future integrated optical microelectronics.Keywords: logic gates, photonic crystals, optical integrated circuits, resonant cavities
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