Search results for: syngas based DRI

Authors: Mahmoud A. Hassan, Mohammed A. Khalili

Abstract:

We are proposing a simple watermarking method based on visual cryptography. The method is based on selection of specific pixels from the original image instead of random selection of pixels as per Hwang [1] paper. Verification information is generated which will be used to verify the ownership of the image without the need to embed the watermark pattern into the original digital data. Experimental results show the proposed method can recover the watermark pattern from the marked data even if some changes are made to the original digital data.

Keywords: Watermarking, visual cryptography, visualthreshold.

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Authors: Jheng-Long Wu, Pei-Chann Chang, Hsuan-Ming Chen

Abstract:

This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.

Keywords: Artificial immune system, intrusion detection, population-based incremental learning, evolution computing.

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Authors: Selim Yannier, Asif Sabanovic, Ahmet Onat, Muhammet Bastan

Abstract:

In this work, we suggested a new approach for the control of a mobile robot capable of being a building block of an intelligent agent. This approach includes obstacle avoidance and goal tracking implemented as two different sliding mode controllers. A geometry based behavior arbitration is proposed for fusing the two outputs. Proposed structure is tested on simulations and real robot. Results have confirmed the high performance of the method.

Keywords: Autonomous Mobile Robot, Behavior Based Control, Fast Local Obstacle Avoidance, Sliding Mode Control.

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Authors: Nadia M. G. AL-Saidi

Abstract:

Since 1984 many schemes have been proposed for digital signature protocol, among them those that based on discrete log and factorizations. However a new identification scheme based on iterated function (IFS) systems are proposed and proved to be more efficient. In this study the proposed identification scheme is transformed into a digital signature scheme by using a one way hash function. It is a generalization of the GQ signature schemes. The attractor of the IFS is used to obtain public key from a private one, and in the encryption and decryption of a hash function. Our aim is to provide techniques and tools which may be useful towards developing cryptographic protocols. Comparisons between the proposed scheme and fractal digital signature scheme based on RSA setting, as well as, with the conventional Guillou-Quisquater signature, and RSA signature schemes is performed to prove that, the proposed scheme is efficient and with high performance.

Keywords: Digital signature, Fractal, Iterated function systems(IFS), Guillou-Quisquater (GQ) protocol, Zero-knowledge (ZK)

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Authors: Svitov David, Alyamkin Sergey

Abstract:

The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax.

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Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

Abstract:

Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, public tendering, tender evaluation, tender evaluation committee, web-based group decision support system.

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Authors: Sudipta Majumdar, Amarendra Kumar Mishra

Abstract:

This paper proposes empirical mode decomposition (EMD) together with wavelet transform (WT) based analytic signal for power quality (PQ) events assessment. EMD decomposes the complex signals into several intrinsic mode functions (IMF). As the PQ events are non stationary, instantaneous parameters have been calculated from these IMFs using analytic signal obtained form WT. We obtained three parameters from IMFs and then used KNN classifier for classification of PQ disturbance. We compared the classification of proposed method for PQ events by obtaining the features using Hilbert transform (HT) method. The classification efficiency using WT based analytic method is 97.5% and using HT based analytic signal is 95.5%.

Keywords: Empirical mode decomposition, Hilbert transform, wavelet transform.

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Authors: Mehran Yazdi, Kazem Gheysari

Abstract:

In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.

Keywords: Biometrics, fingerprint classification, gray level cooccurrence matrix, regular texture representation.

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Authors: Nazrul M. Ahmad, Asrul H. Yaacob, Ridza Fauzi, Alireza Khorram

Abstract:

Elliptic curve-based certificateless signature is slowly gaining attention due to its ability to retain the efficiency of identity-based signature to eliminate the need of certificate management while it does not suffer from inherent private key escrow problem. Generally, cryptosystem based on elliptic curve offers equivalent security strength at smaller key sizes compared to conventional cryptosystem such as RSA which results in faster computations and efficient use of computing power, bandwidth, and storage. This paper proposes to implement certificateless signature based on bilinear pairing to structure the framework of IKE authentication. In this paper, we perform a comparative analysis of certificateless signature scheme with a well-known RSA scheme and also present the experimental results in the context of signing and verification execution times. By generalizing our observations, we discuss the different trade-offs involved in implementing IKE authentication by using certificateless signature.

Keywords: Certificateless signature, IPSec, RSA signature, IKE authentication.

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Authors: Tlili-Guiassa Yamina

Abstract:

Many natural language expressions are ambiguous, and need to draw on other sources of information to be interpreted. Interpretation of the e word تعاون to be considered as a noun or a verb depends on the presence of contextual cues. To interpret words we need to be able to discriminate between different usages. This paper proposes a hybrid of based- rules and a machine learning method for tagging Arabic words. The particularity of Arabic word that may be composed of stem, plus affixes and clitics, a small number of rules dominate the performance (affixes include inflexional markers for tense, gender and number/ clitics include some prepositions, conjunctions and others). Tagging is closely related to the notion of word class used in syntax. This method is based firstly on rules (that considered the post-position, ending of a word, and patterns), and then the anomaly are corrected by adopting a memory-based learning method (MBL). The memory_based learning is an efficient method to integrate various sources of information, and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run, and in order, to improve the importance of the various information in learning.

Keywords: Arabic language, Based-rules, exceptions, Memorybased learning, Tagging.

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Authors: Baharak Khoshkholgh-Sima, Soroush Sardari, Jalal Izadi Mobarakeh, Ramezan Ali Khavari-Nejad

Abstract:

There is an urgent need to develop novel Mycobacterium tuberculosis (Mtb) drugs that are active against drug resistant bacteria but, more importantly, kill persistent bacteria. Our study structured based on integrated analysis of metabolic pathways, small molecule screening and similarity Search in PubChem Database. Metabolic analysis approaches based on Unified weighted used for potent target selection. Our results suggest that pantothenate synthetase (panC) and and 3-methyl-2-oxobutanoate hydroxymethyl transferase (panB) as a appropriate drug targets. In our study, we used pantothenate synthetase because of existence inhibitors. We have reported the discovery of new antitubercular compounds through ligand based approaches using computational tools.

Keywords: In Silico, Ligand-based Virtual Screening, Metabolic Pathways, Mycobacterium tuberculosis

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Authors: K.V. Sridhar, Varun Gunnala, K.S.R Krishna Prasad

Abstract:

In this paper three basic approaches and different methods under each of them for extracting region of interest (ROI) from stationary images are explored. The results obtained for each of the proposed methods are shown, and it is demonstrated where each method outperforms the other. Two main problems in ROI extraction: the channel selection problem and the saliency reversal problem are discussed and how best these two are addressed by various methods is also seen. The basic approaches are 1) Saliency based approach 2) Wavelet based approach 3) Clustering based approach. The saliency approach performs well on images containing objects of high saturation and brightness. The wavelet based approach performs well on natural scene images that contain regions of distinct textures. The mean shift clustering approach partitions the image into regions according to the density distribution of pixel intensities. The experimental results of various methodologies show that each technique performs at different acceptable levels for various types of images.

Keywords: clustering, ROI, saliency, wavelets.

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Authors: Z. X. Chen, Z. Fang, X. P. Wang, G. -Q. Lo, D. -L. Kwong, Y. H. Wu

Abstract:

This paper presents a study of Ni-silicides as the bottom electrode of HfO₂-based RRAM. Various silicidation conditions were used to obtain different Ni concentrations within the Ni-silicide bottom electrode, namely Ni₂Si, NiSi, and NiSi₂. A 10nm HfO₂ switching material and 50nm TiN top electrode was then deposited and etched into 500nm by 500nm square RRAM cells. Cell performance of the Ni₂Si and NiSi cells were good, while the NiSi₂ cell could not switch reliably, indicating that the presence of Ni in the bottom electrode is important for good switching.

Keywords: HfO2-based, Ni-silicide, NiSi, resistive RAM (RRAM).

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Authors: Khalil Shihab, Nida Al-Chalabi

Abstract:

This article describes Uruk, the virtual museum of Iraq that we developed for visual exploration and retrieval of image collections. The system largely exploits the loosely-structured hierarchy of XML documents that provides a useful representation method to store semi-structured or unstructured data, which does not easily fit into existing database. The system offers users the capability to mine and manage the XML-based image collections through a web-based Graphical User Interface (GUI). Typically, at an interactive session with the system, the user can browse a visual structural summary of the XML database in order to select interesting elements. Using this intermediate result, queries combining structure and textual references can be composed and presented to the system. After query evaluation, the full set of answers is presented in a visual and structured way.

Keywords: Data-centric XML, graphical user interfaces, information retrieval, case-based reasoning, fuzzy sets

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Authors: Wei Lifan, Zhang Huaiyu, Yang Yunbin, Li Jia

Abstract:

Through the analysis of the process digital design based on digital mockup, the fact indicates that a distributed cooperative supporting environment is the foundation conditions to adopt design approach based on DMU. Data access authorization is concerned firstly because the value and sensitivity of the data for the enterprise. The access control for administrators is often rather weak other than business user. So authors established an enhanced system to avoid the administrators accessing the engineering data by potential approach and without authorization. Thus the data security is improved.

Keywords: access control, DMU, PLM, virtual prototype.

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Authors: H. Higashiyama, M. Sano, F. Nakanishi, M. Sugiyama, M. Kawanishi, S. Tsukuma

Abstract:

The heat island phenomenon and extremely hot summer climate are becoming environmental problems in Japan. Cool pavements reduce the surface temperature compared to conventional asphalt pavements in the hot summer climate and improve the thermal environment in the urban area. The authors have studied cement–based grouting materials poured into voids in porous asphalt pavements to reduce the road surface temperature. For the cement–based grouting material, cement, ceramic waste powder, and natural zeolite were used. This cement–based grouting material developed reduced the road surface temperature by 20 °C or more in the hot summer season. Considering the urban landscape, this study investigates the effect of surface temperature reduction of colored cement–based grouting materials containing pigments poured into voids in porous asphalt pavements by measuring the surface temperature of asphalt pavements outdoors. The yellow color performed the same as the original cement–based grouting material containing no pigment and was thermally better performance than the other color. However, all the tested cement–based grouting materials performed well for reducing the surface temperature and for creating the urban landscape.

Keywords: Ceramic waste powder, natural zeolite, road surface temperature, asphalt pavements, urban landscape.

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Authors: Peter A. Bibby

Abstract:

Research has suggested that implicit learning tasks may rely on episodic processing to generate above chance performance on the standard classification tasks. The current research examines the invariant features task (McGeorge and Burton, 1990) and argues that such episodic processing is indeed important. The results of the experiment suggest that both rejection and similarity strategies are used by participants in this task to simultaneously reject unfamiliar items and to accept (falsely) familiar items. Primarily these decisions are based on the presence of low or high frequency goal based features of the stimuli presented in the incidental learning phase. It is proposed that a goal based analysis of the incidental learning task provides a simple step in understanding which features of the episodic processing are most important for explaining the match between incidental, implicit learning and test performance.

Keywords: Episodic processing, incidental learning, implicitlearning, invariant learning.

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Authors: Eraricar Salleh, Ida Idayu Muhamad, Nozieanna Khairuddin

Abstract:

Antimicrobial (AM) starch-based films were developed by incorporating chitosan and lauric acid as antimicrobial agent into starch-based film. Chitosan has wide range of applications as a biomaterial, but barriers still exist to its broader use due to its physical and chemical limitations. In this work, a series of starch/chitosan (SC) blend films containing 8% of lauric acid was prepared by casting method. The structure of the film was characterized by Fourier transform infrared spectroscopy (FTIR), Xray diffraction (XRD), and scanning electron microscopy (SEM). The results indicated that there were strong interactions were present between the hydroxyl groups of starch and the amino groups of chitosan resulting in a good miscibility between starch and chitosan in the blend films. Physical properties and optical properties of the AM starch-based film were evaluated. The AM starch-based films incorporated with chitosan and lauric acid showed an improvement in water vapour transmission rate (WVTR) and addition of starch content provided more transparent films while the yellowness of the film attributed to the higher chitosan content. The improvement in water barrier properties was mainly attributed to the hydrophobicity of lauric acid and optimum chitosan or starch content. AM starch based film also showed excellent oxygen barrier. Obtaining films with good oxygen permeability would be an indication of the potential use of these antimicrobial packaging as a natural packaging and an alternative packaging to the synthetic polymer to protect food from oxidation reactions

Keywords: Antimicrobial starch-based films, chitosan, lauric acid, starch.

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Authors: Byung-Joo Oh

Abstract:

This paper describes a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers. The face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). LDA features of the face image are taken as the input of the Radial Basis Function Network (RBFN). The proposed approach has been tested on the ORL database. The experimental results show that the LDA+RBFN algorithm has achieved a recognition rate of 93.5%

Keywords: Face recognition, linear discriminant analysis, radial basis function network.

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Authors: Alok Madan, Arshad K. Hashmi

Abstract:

Performance based design (PBD) is an iterative exercise in which a preliminary trial design of the building structure is selected and if the selected trial design of the building structure does not conform to the desired performance objective, the trial design is revised. In this context, development of a fundamental approach for performance based seismic design of masonry infilled frames with minimum number of trials is an important objective. The paper presents a plastic design procedure based on the energy balance concept for PBD of multi-story multi-bay masonry infilled reinforced concrete (R/C) frames subjected to near-field earthquakes. The proposed energy based plastic design procedure was implemented for trial performance based seismic design of representative masonry infilled reinforced concrete frames with various practically relevant distributions of masonry infill panels over the frame elevation. Non-linear dynamic analyses of the trial PBD of masonry infilled R/C frames was performed under the action of near-field earthquake ground motions. The results of non-linear dynamic analyses demonstrate that the proposed energy method is effective for performance based design of masonry infilled R/C frames under near-field as well as far-field earthquakes.

Keywords: Masonry Infilled Frame, Energy Methods, Near-fault Ground Motions, Pushover Analysis, Nonlinear Dynamic Analysis, Seismic Demand.

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Authors: Christine K. Fulmer

Abstract:

Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: Constructivist theoretical approach, experiential learning, pedagogy, problem-based learning, social work education.

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Authors: Hassan M. Elragal

Abstract:

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on Takagi- Sugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the proposed fuzzy classifiers including premise (antecedent) parameters, consequent parameters and structure of fuzzy rules are optimized using PSO. Experimental results show that higher classification accuracy can be obtained with a lower number of fuzzy rules by using the proposed PSO fuzzy classifiers. The performances of M_PSO and TS_PSO fuzzy classifiers are compared to other fuzzy based classifiers

Keywords: Fuzzy classifier, Optimization of fuzzy systemparameters, Particle swarm optimization, Pattern classification.

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Authors: Sung Jun Ban, Hyeonwoo Cho, ChangWoo Lee, Sang Woo Kim

Abstract:

A packet analyzer is a tool for debugging sensor network systems and is convenient for developers. In this paper, we introduce a new packet analyzer based on an embedded system. The proposed packet analyzer is compatible with IEEE 802.15.4, which is suitable for the wireless communication standard for sensor networks, and is available for remote control by adopting a server-client scheme based on the Ethernet interface. To confirm the operations of the packet analyzer, we have developed two types of sensor nodes based on PIC4620 and ATmega128L microprocessors and tested the functions of the proposed packet analyzer by obtaining the packets from the sensor nodes.

Keywords: Sensor network, embedded system, packet analyzer.

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Authors: O. Ejale, N.B. Siddique, R. Seals

Abstract:

The purpose of this study was to present a reliable mean for human-computer interfacing based on finger gestures made in two dimensions, which could be interpreted and adequately used in controlling a remote robot's movement. The gestures were captured and interpreted using an algorithm based on trigonometric functions, in calculating the angular displacement from one point of touch to another as the user-s finger moved within a time interval; thereby allowing for pattern spotting of the captured gesture. In this paper the design and implementation of such a gesture based user interface was presented, utilizing the aforementioned algorithm. These techniques were then used to control a remote mobile robot's movement. A resistive touch screen was selected as the gesture sensor, then utilizing a programmed microcontroller to interpret them respectively.

Keywords: 2-Dimensional interface, finger gesture, mobile robot control, touch screen.

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Authors: Peng Shen Ong, Yoong Choon Chang, Chee Pun Ooi, Ettikan K. Karuppiah, Shahirina Mohd Tahir

Abstract:

Falling has been one of the major concerns and threats to the independence of the elderly in their daily lives. With the worldwide significant growth of the aging population, it is essential to have a promising solution of fall detection which is able to operate at high accuracy in real-time and supports large scale implementation using multiple cameras. Field Programmable Gate Array (FPGA) is a highly promising tool to be used as a hardware accelerator in many emerging embedded vision based system. Thus, it is the main objective of this paper to present an FPGA-based solution of visual based fall detection to meet stringent real-time requirements with high accuracy. The hardware architecture of visual based fall detection which utilizes the pixel locality to reduce memory accesses is proposed. By exploiting the parallel and pipeline architecture of FPGA, our hardware implementation of visual based fall detection using FGPA is able to achieve a performance of 60fps for a series of video analytical functions at VGA resolutions (640x480). The results of this work show that FPGA has great potentials and impacts in enabling large scale vision system in the future healthcare industry due to its flexibility and scalability.

Keywords: Fall detection, FPGA, hardware implementation.

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Authors: Alima Damak Masmoudi, Randa Boukhris Trabelsi, Dorra Sellami Masmoudi

Abstract:

Single biometric modality recognition is not able to meet the high performance supplies in most cases with its application become more and more broadly. Multimodal biometrics identification represents an emerging trend recently. This paper investigates a novel algorithm based on fusion of both fingerprint and fingervein biometrics. For both biometric recognition, we employ the Monogenic Local Binary Pattern (MonoLBP). This operator integrate the orginal LBP (Local Binary Pattern ) with both other rotation invariant measures: local phase and local surface type. Experimental results confirm that a weighted sum based proposed fusion achieves excellent identification performances opposite unimodal biometric systems. The AUC of proposed approach based on combining the two modalities has very close to unity (0.93).

Keywords: fingerprint, fingervein, LBP, MonoLBP, fusion, biometric trait.

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Authors: Abdelsalam A. Ahmed

Abstract:

Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is derived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.

Keywords: Permanent magnet synchronous motor, mode predictive control, optimization of DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP.

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Authors: Sandeep Chandana, Rene V. Mayorga

Abstract:

The paper presents a new hybridization methodology involving Neural, Fuzzy and Rough Computing. A Rough Sets based approximation technique has been proposed based on a certain Neuro – Fuzzy architecture. A New Rough Neuron composition consisting of a combination of a Lower Bound neuron and a Boundary neuron has also been described. The conventional convergence of error in back propagation has been given away for a new framework based on 'Output Excitation Factor' and an inverse input transfer function. The paper also presents a brief comparison of performances, of the existing Rough Neural Networks and ANFIS architecture against the proposed methodology. It can be observed that the rough approximation based neuro-fuzzy architecture is superior to its counterparts.

Keywords: Boundary neuron, neuro-fuzzy, output excitation factor, RANFIS, rough approximation, rough neural computing.

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Authors: Su-Yan Tang, Wei Zhang, Shan Mei, Yi-Fan Zhu

Abstract:

Network-Centric Air Defense Missile Systems (NCADMS) represents the superior development of the air defense missile systems and has been regarded as one of the major research issues in military domain at present. Due to lack of knowledge and experience on NCADMS, modeling and simulation becomes an effective approach to perform operational analysis, compared with those equation based ones. However, the complex dynamic interactions among entities and flexible architectures of NCADMS put forward new requirements and challenges to the simulation framework and models. ABS (Agent-Based Simulations) explicitly addresses modeling behaviors of heterogeneous individuals. Agents have capability to sense and understand things, make decisions, and act on the environment. They can also cooperate with others dynamically to perform the tasks assigned to them. ABS proves an effective approach to explore the new operational characteristics emerging in NCADMS. In this paper, based on the analysis of network-centric architecture and new cooperative engagement strategies for NCADMS, an agent-based simulation framework by expanding the simulation framework in the so-called System Effectiveness Analysis Simulation (SEAS) was designed. The simulation framework specifies components, relationships and interactions between them, the structure and behavior rules of an agent in NCADMS. Based on scenario simulations, information and decision superiority and operational advantages in NCADMS were analyzed; meanwhile some suggestions were provided for its future development.

Keywords: air defense missile systems, network-centric, agent-based simulation, simulation framework, information superiority, decision superiority, operational advantages

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Authors: Sheng-Shih Wang, Wei-Ting Wang

Abstract:

This paper designs an intelligent guidance system, based on wireless sensor networks, for efficient parking in parking lots. The proposed system consists of a parking space allocation subsystem, a parking space monitoring subsystem, a driving guidance subsystem, and a vehicle detection subsystem. In the system, we propose a novel and effective virtual coordinate system for sensing and displaying devices to determine the proper vacant parking space and provide the precise guidance to the driver. This study constructs a ZigBee-based wireless sensor network on Arduino platform and implements the prototype of the proposed system using Arduino-based complements. Experimental results confirm that the proposed prototype can not only work well, but also provide drivers the correct parking information.

Keywords: Arduino, Parking guidance, Wireless sensor network, ZigBee.

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