Search results for: control area network (CAN)
21493 Implemented Cascade with Feed Forward by Enthalpy Balance Superheated Steam Temperature Control for a Boiler with Distributed Control System
Authors: Kanpop Saion, Sakreya Chitwong
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Control of superheated steam temperature in the steam generation is essential for the efficiency safety and increment age of the boiler. Conventional cascade PID temperature control in the super heater is known to be efficient to compensate disturbance. However, the complex of thermal power plant due to nonlinearity, load disturbance and time delay of steam of superheater system is bigger than other control systems. The cascade loop with feed forward steam temperature control with energy balance compensator using thermodynamic model has been used for the compensation the complex structure of superheater. In order to improve the performance of steam temperature control. The experiment is implemented for 100% load steady and load changing state. The cascade with feed forward with energy balance steam temperature control has stabilized the system as well.Keywords: cascade with feed forward, boiler, superheated steam temperature control, enthalpy balance
Procedia PDF Downloads 30721492 A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses
Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh
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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications
Procedia PDF Downloads 31821491 Light-Weight Network for Real-Time Pose Estimation
Authors: Jianghao Hu, Hongyu Wang
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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone
Procedia PDF Downloads 15421490 Development of Value Based Planning Methodology Incorporating Risk Assessment for Power Distribution Network
Authors: Asnawi Mohd Busrah, Au Mau Teng, Tan Chin Hooi, Lau Chee Chong
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This paper describes value based planning (VBP) methodology incorporating risk assessment as an enhanced and more practical approach to evaluate distribution network projects in Peninsular Malaysia. Assessment indicators associated with economics, performance and risks are formulated to evaluate distribution projects to quantify their benefits against investment. The developed methodology is implemented in a web-based software customized to capture investment and network data, compute assessment indicators and rank the proposed projects according to their benefits. Value based planning approach addresses economic factors in the power distribution planning assessment, so as to minimize cost solution to the power utility while at the same time provide maximum benefits to customers.Keywords: value based planning, distribution network, value of loss load (VoLL), energy not served (ENS)
Procedia PDF Downloads 48121489 ANOVA-Based Feature Selection and Machine Learning System for IoT Anomaly Detection
Authors: Muhammad Ali
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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection
Procedia PDF Downloads 12621488 Application of Low-order Modeling Techniques and Neural-Network Based Models for System Identification
Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo
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The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.Keywords: the bluff body wakes, low-order modeling, neural network, system identification
Procedia PDF Downloads 18421487 Non-Linear Control Based on State Estimation for the Convoy of Autonomous Vehicles
Authors: M-M. Mohamed Ahmed, Nacer K. M’Sirdi, Aziz Naamane
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In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.Keywords: autonomous vehicles, convoy, non-linear control, non-linear observer, sliding mode
Procedia PDF Downloads 14121486 Lateral Control of Electric Vehicle Based on Fuzzy Logic Control
Authors: Hartani Kada, Merah Abdelkader
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Aiming at the high nonlinearities and unmatched uncertainties of the intelligent electric vehicles’ dynamic system, this paper presents a lateral motion control algorithm for intelligent electric vehicles with four in-wheel motors. A fuzzy logic procedure is presented and formulated to realize lateral control in lane change. The vehicle dynamics model and a desired target tracking model were established in this paper. A fuzzy logic controller was designed for integrated active front steering (AFS) and direct yaw moment control (DYC) in order to improve vehicle handling performance and stability, and a fuzzy controller for the automatic steering problem. The simulation results demonstrate the strong robustness and excellent tracking performance of the control algorithm that is proposed.Keywords: fuzzy logic, lateral control, AFS, DYC, electric car technology, longitudinal control, lateral motion
Procedia PDF Downloads 61221485 Functional Instruction Set Simulator (ISS) of a Neural Network (NN) IP with Native BF-16 Generator
Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula
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A Functional Model to mimic the functional correctness of a Neural Network Compute Accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of gcc compilers to BF-16 datatype, which we addressed with a native BF-16 generator integrated to our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex Neural Network Accelerator design by proposing a Functional Model-based scoreboard or Software model using SystemC. The proposed Functional Model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT bringing up micro-steps of execution.Keywords: ISA (instruction set architecture), NN (neural network), TLM (transaction-level modeling), GEMM (general matrix multiplication)
Procedia PDF Downloads 8721484 Structural Health Monitoring of Offshore Structures Using Wireless Sensor Networking under Operational and Environmental Variability
Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader
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The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.Keywords: condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network
Procedia PDF Downloads 27721483 Suitable Models and Methods for the Steady-State Analysis of Multi-Energy Networks
Authors: Juan José Mesas, Luis Sainz
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The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study.Keywords: coupling elements, energy carriers, multi-energy networks, steady-state analysis
Procedia PDF Downloads 8121482 Execution Time Optimization of Workflow Network with Activity Lead-Time
Authors: Xiaoping Qiu, Binci You, Yue Hu
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The executive time of the workflow network has an important effect on the efficiency of the business process. In this paper, the activity executive time is divided into the service time and the waiting time, then the lead time can be extracted from the waiting time. The executive time formulas of the three basic structures in the workflow network are deduced based on the activity lead time. Taken the process of e-commerce logistics as an example, insert appropriate lead time for key activities by using Petri net, and the executive time optimization model is built to minimize the waiting time with the time-cost constraints. Then the solution program-using VC++6.0 is compiled to get the optimal solution, which reduces the waiting time of key activities in the workflow, and verifies the role of lead time in the timeliness of e-commerce logistics.Keywords: electronic business, execution time, lead time, optimization model, petri net, time workflow network
Procedia PDF Downloads 17621481 Distributed Coordination of Connected and Automated Vehicles at Multiple Interconnected Intersections
Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu
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In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.Keywords: connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control
Procedia PDF Downloads 35721480 A Deep Learning Based Method for Faster 3D Structural Topology Optimization
Authors: Arya Prakash Padhi, Anupam Chakrabarti, Rajib Chowdhury
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Topology or layout optimization often gives better performing economic structures and is very helpful in the conceptual design phase. But traditionally it is being done in finite element-based optimization schemes which, although gives a good result, is very time-consuming especially in 3D structures. Among other alternatives machine learning, especially deep learning-based methods, have a very good potential in resolving this computational issue. Here convolutional neural network (3D-CNN) based variational auto encoder (VAE) is trained using a dataset generated from commercially available topology optimization code ABAQUS Tosca using solid isotropic material with penalization (SIMP) method for compliance minimization. The encoded data in latent space is then fed to a 3D generative adversarial network (3D-GAN) to generate the outcome in 64x64x64 size. Here the network consists of 3D volumetric CNN with rectified linear unit (ReLU) activation in between and sigmoid activation in the end. The proposed network is seen to provide almost optimal results with significantly reduced computational time, as there is no iteration involved.Keywords: 3D generative adversarial network, deep learning, structural topology optimization, variational auto encoder
Procedia PDF Downloads 17521479 Growth Analysis in Wheat as Influenced by Water Stress and Variety in Sokoto, Sudan Savannah, Nigeria
Authors: M. B. Sokoto, I. U. Abubakar
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The study was carried out on effect of water stress and variety on growth of wheat (Triticum aestivum L.), during 2009/10 and 2010/11 dry seasons. The treatments consisted of factorial combination of water stress at three critical growth stage which was imposed by withholding water at (Tillering, Flowering, Grain filling) and Control (No stress) and two varieties (Star 11 TR 77173/SLM and Kauze/Weaver) laid out in a split-plot design with three replications. Water stress was assigned to the main-plot while variety was assigned to the sub-plots. Result revealed significant (P<0.05) effect of water stress, water stress at tillering significantly (P<0.05) reduced plant height, LAI, CGR, and NAR. Variety had a significant effect on plant height, LAI, CGR and NAR. In conclusion water stress at tillering was observed to be most critical growth stage in wheat, and water stress at this period should be avoided because it results to decrease in growth components in wheat. Wheat should be sown in November or at least first week of December in this area and other area with similar climate. Star II TR 77173/LM is recommended variety for the area.Keywords: wheat, growth, water stress, variety, Sudan savannah
Procedia PDF Downloads 33621478 Mobile Robot Manipulator Kinematics Motion Control Analysis with MATLAB/Simulink
Authors: Wayan Widhiada, Cok Indra Partha, Gusti Ngurah Nitya Santhiarsa
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The purpose of this paper is to investigate the sophistication of the use of Proportional Integral and Derivative Control to control the kinematic motion of the mobile robot manipulator. Simulation and experimental methods will be used to investigate the sophistication of PID control to control the mobile robot arm in the collection and placement of several kinds of objects quickly, accurately and correctly. Mathematical modeling will be done by utilizing the integration of Solidworks and MATLAB / Simmechanics software. This method works by converting the physical model file into the xml file. This method is easy, fast and accurate done in modeling and design robotics. The automatic control design of this robot manipulator will be validated in simulations and experimental in control labs as evidence that the mobile robot manipulator gripper control design can achieve the best performance such as the error signal is lower than 5%, small overshoot and get steady signal response as quickly.Keywords: control analysis, kinematics motion, mobile robot manipulator, performance
Procedia PDF Downloads 41021477 Methods for Restricting Unwanted Access on the Networks Using Firewall
Authors: Bhagwant Singh, Sikander Singh Cheema
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This paper examines firewall mechanisms routinely implemented for network security in depth. A firewall can't protect you against all the hazards of unauthorized networks. Consequently, many kinds of infrastructure are employed to establish a secure network. Firewall strategies have already been the subject of significant analysis. This study's primary purpose is to avoid unnecessary connections by combining the capability of the firewall with the use of additional firewall mechanisms, which include packet filtering and NAT, VPNs, and backdoor solutions. There are insufficient studies on firewall potential and combined approaches, but there aren't many. The research team's goal is to build a safe network by integrating firewall strength and firewall methods. The study's findings indicate that the recommended concept can form a reliable network. This study examines the characteristics of network security and the primary danger, synthesizes existing domestic and foreign firewall technologies, and discusses the theories, benefits, and disadvantages of different firewalls. Through synthesis and comparison of various techniques, as well as an in-depth examination of the primary factors that affect firewall effectiveness, this study investigated firewall technology's current application in computer network security, then introduced a new technique named "tight coupling firewall." Eventually, the article discusses the current state of firewall technology as well as the direction in which it is developing.Keywords: firewall strategies, firewall potential, packet filtering, NAT, VPN, proxy services, firewall techniques
Procedia PDF Downloads 10321476 Building a Parametric Link between Mapping and Planning: A Sunlight-Adaptive Urban Green System Plan Formation Process
Authors: Chenhao Zhu
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Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper
Procedia PDF Downloads 14221475 Quadrotor in Horizontal Motion Control and Maneuverability
Authors: Ali Oveysi Sarabi
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In this paper, controller design for the attitude and altitude dynamics of an outdoor quadrotor, which is constructed with low cost actuators and drivers, is aimed. Before designing the controller, the quadrotor is modeled mathematically in Matlab-Simulink environment. To control attitude dynamics, linear quadratic regulator (LQR) based controllers are designed, simulated and applied to the system. Two different proportional-integral-derivative action (PID) controllers are designed to control yaw and altitude dynamics. During the implementation of the designed controllers, different test setups are used. Designed controllers are implemented and tuned on the real system using xPC Target. Tests show that these basic control structures are successful to control the attitude and altitude dynamics.Keywords: helicopter balance, flight dynamics, autonomous landing, control robotics
Procedia PDF Downloads 51321474 A Medical Resource Forecasting Model for Emergency Room Patients with Acute Hepatitis
Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang
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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.Keywords: acute hepatitis, medical resource cost, artificial neural network, support vector regression
Procedia PDF Downloads 42321473 The Relations between Seismic Results and Groundwater near the Gokpinar Damp Area, Denizli, Turkey
Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen
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The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate one-dimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.Keywords: seismic data, Gokpinar Damp, urban planning, Denizli
Procedia PDF Downloads 28821472 A Simple Autonomous Hovering and Operating Control of Multicopter Using Only Web Camera
Authors: Kazuya Sato, Toru Kasahara, Junji Kuroda
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In this paper, an autonomous hovering control method of multicopter using only Web camera is proposed. Recently, various control method of an autonomous flight for multicopter are proposed. But, in the previously proposed methods, a motion capture system (i.e., OptiTrack) and laser range finder are often used to measure the position and posture of multicopter. To achieve an autonomous flight control of multicopter with simple equipment, we propose an autonomous flight control method using AR marker and Web camera. AR marker can measure the position of multicopter with Cartesian coordinate in three dimensional, then its position connects with aileron, elevator, and accelerator throttle operation. A simple PID control method is applied to the each operation and adjust the controller gains. Experimental result are given to show the effectiveness of our proposed method. Moreover, another simple operation method for autonomous flight control multicopter is also proposed.Keywords: autonomous hovering control, multicopter, Web camera, operation
Procedia PDF Downloads 56321471 Dynamic Transmission Modes of Network Public Opinion on Subevents Clusters of an Emergent Event
Authors: Yuan Xu, Xun Liang, Meina Zhang
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The rise and attenuation of the public opinion broadcast of an emergent accident, in the social network, has a close relationship with the dynamic development of its subevents cluster. In this article, we take Tianjin Port explosion's subevents as an example to research the dynamic propagation discipline of Internet public opinion in a sudden accident, and analyze the overall structure of dynamic propagation to propose four different routes for subevents clusters propagation. We also generate network diagrams for the dynamic public opinion propagation, analyze each propagation type specifically. Based on this, suggestions on the supervision and guidance of Internet public opinion broadcast can be made.Keywords: network dynamic transmission modes, emergent subevents clusters, Tianjin Port explosion, public opinion supervision
Procedia PDF Downloads 29721470 A POX Controller Module to Prepare a List of Flow Header Information Extracted from SDN Traffic
Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin
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Software Defined Networking (SDN) is a paradigm designed to facilitate the way of controlling the network dynamically and with more agility. Network traffic is a set of flows, each of which contains a set of packets. In SDN, a matching process is performed on every packet coming to the network in the SDN switch. Only the headers of the new packets will be forwarded to the SDN controller. In terminology, the flow header fields are called tuples. Basically, these tuples are 5-tuple: the source and destination IP addresses, source and destination ports, and protocol number. This flow information is used to provide an overview of the network traffic. Our module is meant to extract this 5-tuple with the packets and flows numbers and show them as a list. Therefore, this list can be used as a first step in the way of detecting the DDoS attack. Thus, this module can be considered as the beginning stage of any flow-based DDoS detection method.Keywords: matching, OpenFlow tables, POX controller, SDN, table-miss
Procedia PDF Downloads 19921469 Neural Network Based Control Algorithm for Inhabitable Spaces Applying Emotional Domotics
Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez
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In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.Keywords: data analysis, emotional domotics, performance improvement, neural network
Procedia PDF Downloads 14321468 Big Data in Telecom Industry: Effective Predictive Techniques on Call Detail Records
Authors: Sara ElElimy, Samir Moustafa
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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).Keywords: big data analytics, machine learning, CDRs, 5G
Procedia PDF Downloads 14021467 Novel Recommender Systems Using Hybrid CF and Social Network Information
Authors: Kyoung-Jae Kim
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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition
Procedia PDF Downloads 29421466 Evolution Mechanism of the Formation of Rock Heap under Seismic Action and Analysis on Engineering Geological Structure
Authors: Jian-Xiu Wan, Yao Yin
Abstract:
In complex terrain and poor geological conditions areas, Railway, highway and other transportation constructions are still strongly developing. However, various geological disasters happened such as landslide, rock heap and so on. According to the results of geological investigation, the form of skirt (trapezoidal), semicircle and triangle rock heaps are mainly due to complex internal force and external force, in a certain extent, which is related to the terrain, the nature of the rock mass, the supply area and the surface shape of rock heap. Combined with the above factors, discrete element numerical simulation of rock mass is established under different terrain conditions based on 3DEC, and accelerated formation process of rock heap under seismic action is simulated. The fragmentation structure supply area is calculated, in which the most dangerous area is located. At the same time, the formation mechanism and development process are studied in different terrain conditions, and the structure of rock heap is judged by section, which can provide a strong theoretical and technical support for the prevention and control of geological disasters.Keywords: 3DEC, fragmentation structure, rock heap, slope, seismic action
Procedia PDF Downloads 29821465 Improvement of an Arm and Shoulder Exoskeleton Using Gyro Sensor
Authors: D. Maneetham
Abstract:
The developed exoskeleton device has to control joints between shoulder and arm. Exoskeleton device can help patients with hemiplegia upper so that the patient can help themselves in their daily life. Exoskeleton device includes a robot arm wear that looks like the movement is similar to the normal arm. Exoskeleton arm is powered by the motor through the cable with a control system that developed to control the movement of the joint of a robot arm. The arm will include the shoulder, the elbow, and the wrist. The control system is used Arduino Mega 2560 controller and the operation of the DC motor through the relay module. The control system can be divided into two modes such as the manual control with the joystick mode and automatically control with the movement of the head by Gyro sensor. The controller is also designed to move between the shoulder and the arm movement from their original location. Results have shown that the controller gave the best performance and all movements can be controlled.Keywords: exoskeleton arm, hemiplegia upper, shoulder and arm, stroke
Procedia PDF Downloads 35321464 Combination of Plantar Pressure and Star Excursion Balance Test for Evaluation of Dynamic Posture Control on High-Heeled Shoes
Authors: Yan Zhang, Jan Awrejcewicz, Lin Fu
Abstract:
High-heeled shoes force the foot into plantar flexion position resulting in foot arch rising and disturbance of the articular congruence between the talus and tibiofibular mortice, all of which may increase the challenge of balance maintenance. Plantar pressure distribution of the stance limb during the star excursion balance test (SEBT) contributes to the understanding of potential sources of reaching excursions in SEBT. The purpose of this study is to evaluate the dynamic posture control while wearing high-heeled shoes using SEBT in a combination of plantar pressure measurement. Twenty healthy young females were recruited. Shoes of three heel heights were used: flat (0.8 cm), low (4.0 cm), high (6.6 cm). The testing grid of SEBT consists of three lines extending out at 120° from each other, which were defined as anterior, posteromedial, and posterolateral directions. Participants were instructed to stand on their dominant limb with the heel in the middle of the testing grid and hands on hips and to reach the non-stance limb as far as possible towards each direction. The distal portion of the reaching limb lightly touched the ground without shifting weight. Then returned the reaching limb to the beginning position. The excursion distances were normalized to leg length. The insole plantar measurement system was used to record peak pressure, contact area, and pressure-time integral of the stance limb. Results showed that normalized excursion distance decreased significantly as heel height increased. The changes of plantar pressure in SEBT as heel height increased were more obvious in the medial forefoot (MF), medial midfoot (MM), rearfoot areas. At MF, the peak pressure and pressure-time integral of low and high shoes increased significantly compared with that of flat shoes, while the contact area decreased significantly as heel height increased. At MM, peak pressure, contact area, and pressure-time integral of high and low shoes were significantly lower than that of flat shoes. To reduce posture instability, the stance limb plantar loading shifted to medial forefoot. Knowledge of this study identified dynamic posture control deficits while wearing high-heeled shoes and the critical role of the medial forefoot in dynamic balance maintenance.Keywords: dynamic posture control, high-heeled shoes, plantar pressure, star excursion balance test.
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