Search results for: system modeling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20044

Search results for: system modeling

17074 Building an Interactive Web-Based GIS System for Planning of Geological Survey Works

Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

Abstract:

The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a web-based system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: engineering geology, flex, geological survey planning, geoscience, GIS, site investigation, WebGIS

Procedia PDF Downloads 301
17073 Modeling and Characterization of Organic LED

Authors: Bouanati Sidi Mohammed, N. E. Chabane Sari, Mostefa Kara Selma

Abstract:

It is well-known that Organic light emitting diodes (OLEDs) are attracting great interest in the display technology industry due to their many advantages, such as low price of manufacturing, large-area of electroluminescent display, various colors of emission included white light. Recently, there has been much progress in understanding the device physics of OLEDs and their basic operating principles. In OLEDs, Light emitting is the result of the recombination of electron and hole in light emitting layer, which are injected from cathode and anode. For improve luminescence efficiency, it is needed that hole and electron pairs exist affluently and equally and recombine swiftly in the emitting layer. The aim of this paper is to modeling polymer LED and OLED made with small molecules for studying the electrical and optical characteristics. The first simulation structures used in this paper is a mono layer device; typically consisting of the poly (2-methoxy-5(2’-ethyl) hexoxy-phenylenevinylene) (MEH-PPV) polymer sandwiched between an anode usually an indium tin oxide (ITO) substrate, and a cathode, such as Al. In the second structure we replace MEH-PPV by tris (8-hydroxyquinolinato) aluminum (Alq3). We choose MEH-PPV because of it's solubility in common organic solvents, in conjunction with a low operating voltage for light emission and relatively high conversion efficiency and Alq3 because it is one of the most important host materials used in OLEDs. In this simulation, the Poole-Frenkel- like mobility model and the Langevin bimolecular recombination model have been used as the transport and recombination mechanism. These models are enabled in ATLAS -SILVACO software. The influence of doping and thickness on I(V) characteristics and luminescence, are reported.

Keywords: organic light emitting diode, polymer lignt emitting diode, organic materials, hexoxy-phenylenevinylene

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17072 Computer Anxiety and the Use of Computerized System by University Librarians in Delta State University Library, Nigeria

Authors: L. Arumuru

Abstract:

The paper investigates computer anxiety and the use of computerized library system by university librarians in Delta State University library, Abraka, Nigeria. Some of the root causes of computer anxiety among university librarians such as lack of exposure to computers at early age, inadequate computer skills, inadequate computer training, fear at the sight of a computer, lack of understanding of how computers work, etc. were pin-pointed in the study. Also, the different services rendered in the university libraries with the aid of computers such as reference services, circulation services, acquisition services, cataloguing and classification services, etc. were identified. The study employed the descriptive survey research design through the expo-facto method, with a population of 56 librarians, while the simple percentage and frequency counts were used to analyze the data generated from the administered copies of the questionnaire. Based on the aforementioned root causes of computer anxiety and the resultant effect on computerized library system, recommendations were proffered in the study.

Keywords: computer anxiety, computerized library system, library services, university librarians

Procedia PDF Downloads 376
17071 Analysis of Collision Avoidance System

Authors: N. Gayathri Devi, K. Batri

Abstract:

The advent of technology has increased the traffic hazards and the road accidents take place. Collision detection system in automobile aims at reducing or mitigating the severity of an accident. This project aims at avoiding Vehicle head on collision by means of collision detection algorithm. This collision detection algorithm predicts the collision and the avoidance or minimization have to be done within few seconds on confirmation. Under critical situation collision minimization is made possible by turning the vehicle to the desired turn radius so that collision impact can be reduced. In order to avoid the collision completely, the turning of the vehicle should be achieved at reduced speed in order to maintain the stability.

Keywords: collision avoidance system, time to collision, time to turn, turn radius

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17070 A Sentence-to-Sentence Relation Network for Recognizing Textual Entailment

Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

Abstract:

Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

Procedia PDF Downloads 336
17069 PEA Design of the Direct Control for Training Motor Drives

Authors: Abdulatif Abdulsalam Mohamed Shaban

Abstract:

This paper states that the art of Procedure Entry Array (PEA) plan with a focus on control system applications. This paper begins with an impression of PEA technology development, followed by an arrangement of design technologies, and the use of programmable description languages and system-level design tools. They allow a practical approach based on a unique model for complete engineering electronics systems. There are three main design rules are implemented in the system. These are algorithm based fine-tuning, modularity, and the control act and the architectural constraints. An overview of contributions and limits of PEAs is also given, followed by a short survey of PEA-based gifted controllers for recent engineering systems. Finally, two complete and timely case studies are presented to illustrate the benefits of a PEA implementation when using the proposed system modelling and devise attitude. These consist of the direct control for training motor drives and the control of a diesel-driven stand-alone generator with the help of logical design.

Keywords: control (DC), engineering electronics systems, training motor drives, procedure entry array

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17068 CDM-Based Controller Design for High-Frequency Induction Heating System with LLC Tank

Authors: M. Helaimi, R. Taleb, D. Benyoucef, B. Belmadani

Abstract:

This paper presents the design of a polynomial controller with coefficient diagram method (CDM). This controller is used to control the output power of high frequency resonant inverter with LLC tank. One of the most important problems associated with the proposed inverter is achieving ZVS operating during the induction heating process. To overcome this problem, asymmetrical voltage cancellation (AVC) control technique is proposed. The phased look loop (PLL) is used to track the natural frequency of the system. The small signal model of the system with the proposed control is obtained using extending describing function method (EDM). The validity of the proposed control is verified by simulation results.

Keywords: induction heating, AVC control, CDM, PLL, resonant inverter

Procedia PDF Downloads 655
17067 Design of EV Steering Unit Using AI Based on Estimate and Control Model

Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

Abstract:

Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

Procedia PDF Downloads 13
17066 Heat: A Healthy Eating Programme

Authors: Osagbai Joshua Eriki, Ngozi Agunwamba, Alice Hill, Lorna Almond, Maniya Duffy, Devashini Naidoo, David Ho, Raman Deo

Abstract:

Aims: To evaluate the baseline eating pattern in a psychiatric hospital through quantifying purchases of food and drink items at the hospital shop and to implement a traffic light healthy eating labeling system. Method: A electronic till with reporting capabilities was purchased. A two-week period of baseline data collection was conducted. Thereafter, a system for labeling items based on the nutritional value of the food items at the hospital shop was implemented. Green labeling represented the items with the lowest calories and red the most. Further data was collated on the number and types of items purchased by patients according to the category, and the initial effectiveness of the system was evaluated. Result: Despite the implementation of the traffic light system, the red category had the highest number of items purchased by patients, highlighting the importance of promoting healthy eating choices. However, the study also showed that the system was effective in promoting healthy options, as the number of items purchased from the green category increased during the study period. Conclusion: The implementation of a traffic light labeling system for items sold at the hospital shop offers a promising approach to promoting healthy eating habits and choices. This is likely to contribute to a toolkit of measures when considering the multifactorial challenges that obesity and weight issues pose for long-stay psychiatric inpatients

Keywords: mental health, nutrition, food, healthy

Procedia PDF Downloads 92
17065 Analysing the Cost of Immigrants to the National Health System in Eastern Macedonia and Thrace

Authors: T. Theodosiou, P. Polychronidou, A. G. Karasavvoglou

Abstract:

The latest years the number of immigrants at Greece has increased dramatically. Their impact on the National Health System (NHS) has not been yet thoroughly investigated. This paper analyses the cost of immigrants to the NHS hospitals of the region of Eastern Macedonia and Thrace. The data are collected from 2005 to 2011 from five different hospitals and are analysed using linear mixed effects models in order to investigate the effects of nationality and year on the cost of hospitalization and treatment. The results show that generally the Greek nationality patients have a higher mean cost of hospitalization compared to the immigrants and that there is an increasing trend for the cost except for the year 2010.

Keywords: cost, Eastern Macedonia and Thrace, immigrants, national health system

Procedia PDF Downloads 240
17064 Annotation Ontology for Semantic Web Development

Authors: Hadeel Al Obaidy, Amani Al Heela

Abstract:

The main purpose of this paper is to examine the concept of semantic web and the role that ontology and semantic annotation plays in the development of semantic web services. The paper focuses on semantic web infrastructure illustrating how ontology and annotation work to provide the learning capabilities for building content semantically. To improve productivity and quality of software, the paper applies approaches, notations and techniques offered by software engineering. It proposes a conceptual model to develop semantic web services for the infrastructure of web information retrieval system of digital libraries. The developed system uses ontology and annotation to build a knowledge based system to define and link the meaning of a web content to retrieve information for users’ queries. The results are more relevant through keywords and ontology rule expansion that will be more accurate to satisfy the requested information. The level of results accuracy would be enhanced since the query semantically analyzed work with the conceptual architecture of the proposed system.

Keywords: semantic web services, software engineering, semantic library, knowledge representation, ontology

Procedia PDF Downloads 166
17063 Assessment of Collapse Potential of Degrading SDOF Systems

Authors: Muzaffer Borekci, Murat Serdar Kirçil

Abstract:

Predicting the collapse potential of a structure during earthquakes is an important issue in earthquake engineering. Many researchers proposed different methods to assess the collapse potential of structures under the effect of strong ground motions. However most of them did not consider degradation and softening effect in hysteretic behavior. In this study, collapse potential of SDOF systems caused by dynamic instability with stiffness and strength degradation has been investigated. An equation was proposed for the estimation of collapse period of SDOF system which is a limit value of period for dynamic instability. If period of the considered SDOF system is shorter than the collapse period then the relevant system exhibits dynamic instability and collapse occurs.

Keywords: collapse, degradation, dynamic instability, seismic response

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17062 Homeless Population Modeling and Trend Prediction Through Identifying Key Factors and Machine Learning

Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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17061 A Single-Use Endoscopy System for Identification of Abnormalities in the Distal Oesophagus of Individuals with Chronic Reflux

Authors: Nafiseh Mirabdolhosseini, Jerry Zhou, Vincent Ho

Abstract:

The dramatic global rise in acid reflux has also led to oesophageal adenocarcinoma (OAC) becoming the fastest-growing cancer in developed countries. While gastroscopy with biopsy is used to diagnose OAC patients, this labour-intensive and expensive process is not suitable for population screening. This study aims to design, develop, and implement a minimally invasive system to capture optical data of the distal oesophagus for rapid screening of potential abnormalities. To develop the system and understand user requirements, a user-centric approach was employed by utilising co-design strategies. Target users’ segments were identified, and 38 patients and 14 health providers were interviewed. Next, the technical requirements were developed based on consultations with the industry. A minimally invasive optical system was designed and developed considering patient comfort. This system consists of the sensing catheter, controller unit, and analysis program. Its procedure only takes 10 minutes to perform and does not require cleaning afterward since it has a single-use catheter. A prototype system was evaluated for safety and efficacy for both laboratory and clinical performance. This prototype performed successfully when submerged in simulated gastric fluid without showing evidence of erosion after 24 hours. The system effectively recorded a video of the mid-distal oesophagus of a healthy volunteer (34-year-old male). The recorded images were used to develop an automated program to identify abnormalities in the distal oesophagus. Further data from a larger clinical study will be used to train the automated program. This system allows for quick visual assessment of the lower oesophagus in primary care settings and can serve as a screening tool for oesophageal adenocarcinoma. In addition, this system is able to be coupled with 24hr ambulatory pH monitoring to better correlate oesophageal physiological changes with reflux symptoms. It also can provide additional information on lower oesophageal sphincter functions such as opening times and bolus retention.

Keywords: endoscopy, MedTech, oesophageal adenocarcinoma, optical system, screening tool

Procedia PDF Downloads 74
17060 Intrusion Detection System Based on Peer to Peer

Authors: Alireza Pour Ebrahimi, Vahid Abasi

Abstract:

Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

Procedia PDF Downloads 533
17059 Optimal Reactive Power Dispatch under Various Contingency Conditions Using Whale Optimization Algorithm

Authors: Khaled Ben Oualid Medani, Samir Sayah

Abstract:

The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

Procedia PDF Downloads 107
17058 Soil-Structure Interaction in Stiffness and Strength Degrading Systems

Authors: Enrique Bazan-Zurita, Sittipong Jarernprasert, Jacobo Bielak

Abstract:

We study the effects of soil-structure interaction (SSI) on the inelastic seismic response of a single-degree-of-freedom system whose hysteretic behaviour exhibits stiffness and/or strength degrading characteristics. Two sets of accelerograms are used as seismic input: the first comprising 87 record from stiff to medium stiff sites in California, and the second comprising 66 records from the soft lakebed of Mexico City. This study focuses in three seismic response parameters: ductility demand, inter-story drift, and total lateral displacement. The results allow quantitative estimates of changes in such parameters in an SSI system in comparison with those corresponding to the associated fixed-base system. We found that degrading features affect significantly both the response of fixed-base structures and the impact of soil-structure interaction. We propose a procedure to incorporate the results of this and similar studies in seismic design regulations for SSI system with anticipated nonlinear degrading behaviour.

Keywords: inelastic, seismic, building, foundation, interaction

Procedia PDF Downloads 277
17057 Glaucoma Detection in Retinal Tomography Using the Vision Transformer

Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

Abstract:

Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

Procedia PDF Downloads 182
17056 Overview of Different Approaches Used in Optimal Operation Control of Hybrid Renewable Energy Systems

Authors: K. Kusakana

Abstract:

A hybrid energy system is a combination of renewable energy sources with back up, as well as a storage system used to respond to given load energy requirements. Given that the electrical output of each renewable source is fluctuating with changes in weather conditions, and since the load demand also varies with time; one of the main attributes of hybrid systems is to be able to respond to the load demand at any time by optimally controlling each energy source, storage and back-up system. The induced optimization problem is to compute the optimal operation control of the system with the aim of minimizing operation costs while efficiently and reliably responding to the load energy requirement. Current optimization research and development on hybrid systems are mainly focusing on the sizing aspect. Thus, the aim of this paper is to report on the state-of-the-art of optimal operation control of hybrid renewable energy systems. This paper also discusses different challenges encountered, as well as future developments that can help in improving the optimal operation control of hybrid renewable energy systems.

Keywords: renewable energies, hybrid systems, optimization, operation control

Procedia PDF Downloads 369
17055 Evaluation of Collect Tree Protocol for Structural Health Monitoring System Using Wireless Sensor Networks

Authors: Amira Zrelli, Tahar Ezzedine

Abstract:

Routing protocol may enhance the lifetime of sensor network, it has a highly importance, especially in wireless sensor network (WSN). Therefore, routing protocol has a big effect in these networks, thus the choice of routing protocol must be studied before setting up our network. In this work, we implement the routing protocol collect tree protocol (CTP) which is one of the hierarchic protocols used in structural health monitoring (SHM). Therefore, to evaluate the performance of this protocol, we choice to work with Contiki system and Cooja simulator. By throughput and RSSI evaluation of each node, we will deduce about the utility of CTP in structural monitoring system.

Keywords: CTP, WSN, SHM, routing protocol

Procedia PDF Downloads 282
17054 A Multi Agent Based Protection Scheme for Smart Distribution Network in Presence of Distributed Energy Resources

Authors: M. R. Ebrahimi, B. Mahdaviani

Abstract:

Conventional electric distribution systems are radial in nature, supplied at one end through a main source. These networks generally have a simple protection system usually implemented using fuses, re-closers, and over-current relays. Recently, great attention has been paid to applying Distributed energy resources (DERs) throughout electric distribution systems. Presence of such generation in a network leads to losing coordination of protection devices. Therefore, it is desired to develop an algorithm which is capable of protecting distribution systems that include DER. On the other hand smart grid brings opportunities to the power system. Fast advancement in communication and measurement techniques accelerates the development of multi agent system (MAS). So in this paper, a new approach for the protection of distribution networks in the presence of DERs is presented base on MAS. The proposed scheme has been implemented on a sample 27-bus distribution network.

Keywords: distributed energy resource, distribution network, protection, smart grid, multi agent system

Procedia PDF Downloads 598
17053 The Formulation of Inference Fuzzy System as a Valuation Subsidiary Based Particle Swarm Optimization for Solves the Issue of Decision Making in Middle Size Soccer Robot League

Authors: Zahra Abdolkarimi, Naser Zouri

Abstract:

The actual purpose of RoboCup is creating independent team of robots in 2050 based of FiFa roles to bring the victory in compare of world star team. There is unbelievable growing of Robots created a collection of complex and motivate subject in robotic and intellectual ornate, also it made a mechatronics style base of theoretical and technical way in Robocop. Decision making of robots depends to environment reaction, self-player and rival player with using inductive Fuzzy system valuation subsidiary to solve issue of robots in land game. The measure of selection in compare with other methods depends to amount of victories percentage in the same team that plays accidentally.

Keywords: particle swarm optimization, chaos theory, inference fuzzy system, simulation environment rational fuzzy system, mamdani and assilian, deffuzify

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17052 Interpolation Issue in PVNPG-14M Application for Technical Control of Artillery Fire

Authors: Martin Blaha, Ladislav Potužák, Daniel Holesz

Abstract:

This paper focused on application support for technical control of artillery units – PVNPG-14M, especially on interpolation issue. Artillery units of the Army of the Czech Republic, reflecting the current global security neighborhood, can be used outside the Czech Republic. The paper presents principles, evolution and calculation in the process of complete preparation. The paper presents expertise using of application of current artillery communication and information system and suggests the perspective future system. The paper also presents problems in process of complete preparing of fire especially problems in permanently information (firing table) and calculated values. The paper presents problems of current artillery communication and information system and suggests requirements of the future system.

Keywords: Fire for Effect, Application, Fire Control, Interpolation method, Software development.

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17051 Design, Synthesis and Pharmacological Investigation of Novel 2-Phenazinamine Derivatives as a Mutant BCR-ABL (T315I) Inhibitor

Authors: Gajanan M. Sonwane

Abstract:

Nowadays, the entire pharmaceutical industry is facing the challenge of increasing efficiency and innovation. The major hurdles are the growing cost of research and development and a concurrent stagnating number of new chemical entities (NCEs). Hence, the challenge is to select the most druggable targets and to search the equivalent drug-like compounds, which also possess specific pharmacokinetic and toxicological properties that allow them to be developed as drugs. The present research work includes the studies of developing new anticancer heterocycles by using molecular modeling techniques. The heterocycles synthesized through such methodology are much effective as various physicochemical parameters have been already studied and the structure has been optimized for its best fit in the receptor. Hence, on the basis of the literature survey and considering the need to develop newer anticancer agents, new phenazinamine derivatives were designed by subjecting the nucleus to molecular modeling, viz., GQSAR analysis and docking studies. Simultaneously, these designed derivatives were subjected to in silico prediction of biological activity through PASS studies and then in silico toxicity risk assessment studies. In PASS studies, it was found that all the derivatives exhibited a good spectrum of biological activities confirming its anticancer potential. The toxicity risk assessment studies revealed that all the derivatives obey Lipinski’s rule. Amongst these series, compounds 4c, 5b and 6c were found to possess logP and drug-likeness values comparable with the standard Imatinib (used for anticancer activity studies) and also with the standard drug methotrexate (used for antimitotic activity studies). One of the most notable mutations is the threonine to isoleucine mutation at codon 315 (T315I), which is known to be resistant to all currently available TKI. Enzyme assay planned for confirmation of target selective activity.

Keywords: drug design, tyrosine kinases, anticancer, Phenazinamine

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17050 Spin-Dependent Transport Signatures of Bound States: From Finger to Top Gates

Authors: Yun-Hsuan Yu, Chi-Shung Tang, Nzar Rauf Abdullah, Vidar Gudmundsson

Abstract:

Spin-orbit gap feature in energy dispersion of one-dimensional devices is revealed via strong spin-orbit interaction (SOI) effects under Zeeman field. We describe the utilization of a finger-gate or a top-gate to control the spin-dependent transport characteristics in the SOI-Zeeman influenced split-gate devices by means of a generalized spin-mixed propagation matrix method. For the finger-gate system, we find a bound state in continuum for incident electrons within the ultra-low energy regime. For the top-gate system, we observe more bound-state features in conductance associated with the formation of spin-associated hole-like or electron-like quasi-bound states around band thresholds, as well as hole bound states around the reverse point of the energy dispersion. We demonstrate that the spin-dependent transport behavior of a top-gate system is similar to that of a finger-gate system only if the top-gate length is less than the effective Fermi wavelength.

Keywords: spin-orbit, zeeman, top-gate, finger-gate, bound state

Procedia PDF Downloads 253
17049 Wave Interaction with Defects in Pressurized Composite Structures

Authors: R. K. Apalowo, D. Chronopoulos, V. Thierry

Abstract:

A wave finite element (WFE) and finite element (FE) based computational method is presented by which the dispersion properties as well as the wave interaction coefficients for one-dimensional structural system can be predicted. The structural system is discretized as a system comprising a number of waveguides connected by a coupling joint. Uniform nodes are ensured at the interfaces of the coupling element with each waveguide. Then, equilibrium and continuity conditions are enforced at the interfaces. Wave propagation properties of each waveguide are calculated using the WFE method and the coupling element is modelled using the FE method. The scattering of waves through the coupling element, on which damage is modelled, is determined by coupling the FE and WFE models. Furthermore, the central aim is to evaluate the effect of pressurization on the wave dispersion and scattering characteristics of the prestressed structural system compared to that which is not prestressed. Numerical case studies are exhibited for two waveguides coupled through a coupling joint.

Keywords: Finite Element, Prestressed Structures, Wave Finite Element, Wave Propagation Properties, Wave Scattering Coefficients.

Procedia PDF Downloads 283
17048 Recurrent Neural Networks for Complex Survival Models

Authors: Pius Marthin, Nihal Ata Tutkun

Abstract:

Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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17047 Performance of Modified Wedge Anchorage System for Pre-Stressed FRP Bars

Authors: Othman S. Alsheraida, Sherif El-Gamal

Abstract:

Fiber Reinforced Polymers (FRP) is a composite material with exceptional properties that are capable of replacing conventional steel reinforcement in reinforced and pre-stressed concrete structures. However, the main obstacle for their wide use in the pre-stressed concrete application is the anchorage system. Due to the weakness of FRP in the transverse direction, the pre-stressing capacity of FRP bars is limited. This paper investigates the modification of the conventional wedge anchorage system to be used for stressing of FRP bars in pre-stressed applications. Epoxy adhesive material with glass FRP (GFRP) bars and conventional steel wedge were used in this paper. The GFRP bars are encased with epoxy at the anchor zone and the wedge system was used in the pull-out test. The results showed a loading capacity of 47.6 kN which is 69% of the bar ultimate capacity. Additionally, nylon wedge was made with the same dimensions of the steel wedge and tested for GFRP bars without epoxy layer. The nylon wedge showed a loading capacity of 19.7 kN which is only 28.5% of the ultimate bar capacity.

Keywords: anchorage, concrete, epoxy, frp, pre-stressed

Procedia PDF Downloads 285
17046 Parametric Analysis of Lumped Devices Modeling Using Finite-Difference Time-Domain

Authors: Felipe M. de Freitas, Icaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

Abstract:

The SPICE-based simulators are quite robust and widely used for simulation of electronic circuits, their algorithms support linear and non-linear lumped components and they can manipulate an expressive amount of encapsulated elements. Despite the great potential of these simulators based on SPICE in the analysis of quasi-static electromagnetic field interaction, that is, at low frequency, these simulators are limited when applied to microwave hybrid circuits in which there are both lumped and distributed elements. Usually the spatial discretization of the FDTD (Finite-Difference Time-Domain) method is done according to the actual size of the element under analysis. After spatial discretization, the Courant Stability Criterion calculates the maximum temporal discretization accepted for such spatial discretization and for the propagation velocity of the wave. This criterion guarantees the stability conditions for the leapfrogging of the Yee algorithm; however, it is known that for the field update, the stability of the complete FDTD procedure depends on factors other than just the stability of the Yee algorithm, because the FDTD program needs other algorithms in order to be useful in engineering problems. Examples of these algorithms are Absorbent Boundary Conditions (ABCs), excitation sources, subcellular techniques, grouped elements, and non-uniform or non-orthogonal meshes. In this work, the influence of the stability of the FDTD method in the modeling of concentrated elements such as resistive sources, resistors, capacitors, inductors and diode will be evaluated. In this paper is proposed, therefore, the electromagnetic modeling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-wide frequencies. The models of the resistive source, the resistor, the capacitor, the inductor, and the diode will be evaluated, among the mathematical models for lumped components in the LE-FDTD method (Lumped-Element Finite-Difference Time-Domain), through the parametric analysis of Yee cells size which discretizes the lumped components. In this way, it is sought to find an ideal cell size so that the analysis in FDTD environment is in greater agreement with the expected circuit behavior, maintaining the stability conditions of this method. Based on the mathematical models and the theoretical basis of the required extensions of the FDTD method, the computational implementation of the models in Matlab® environment is carried out. The boundary condition Mur is used as the absorbing boundary of the FDTD method. The validation of the model is done through the comparison between the obtained results by the FDTD method through the electric field values and the currents in the components, and the analytical results using circuit parameters.

Keywords: hybrid circuits, LE-FDTD, lumped element, parametric analysis

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17045 A Neurosymbolic Learning Method for Uplink LTE-A Channel Estimation

Authors: Lassaad Smirani

Abstract:

In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

Procedia PDF Downloads 382