Search results for: Architecture artifacts
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 942

Search results for: Architecture artifacts

552 SPA-VNDN: Enhanced Smart Parking Application by Vehicular Named Data Networking

Authors: Bassma Aldahlan, Zongming Fei

Abstract:

Recently, there is a great interest in smart parking application. Theses applications are enhanced by a vehicular ad-hoc network, which helps drivers find and reserve satiable packing spaces for a period of time ahead of time. Named Data Networking (NDN) is a future Internet architecture that benefits vehicular ad-hoc networks because of its clean-slate design and pure communication model. In this paper, we proposed an NDN-based frame-work for smart parking that involved a fog computing architecture. The proposed application had two main directions: First, we allowed drivers to query the number of parking spaces in a particular parking lot. Second, we introduced a technique that enabled drivers to make intelligent reservations before their arrival time. We also introduced a “push-based” model supporting the NDN-based framework for smart parking applications. To evaluate the proposed solution’s performance, we analyzed the function for finding parking lots with available parking spaces and the function for reserving a parking space. Our system showed high performance results in terms of response time and push overhead. The proposed reservation application performed better than the baseline approach.

Keywords: Cloud Computing, Vehicular Named Data Networking, Smart Parking Applications, Fog Computing.

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551 A Safety Analysis Method for Multi-Agent Systems

Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

Abstract:

Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: Multi-agent system, safety analysis, safety model.

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550 An FPGA Implementation of Intelligent Visual Based Fall Detection

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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549 Development of Reliable Web-Based Laboratories for Developing Countries

Authors: Teyana S. Sapula, Damian D. Haule

Abstract:

In online context, the design and implementation of effective remote laboratories environment is highly challenging on account of hardware and software needs. This paper presents the remote laboratory software framework modified from ilab shared architecture (ISA). The ISA is a framework which enables students to remotely acccess and control experimental hardware using internet infrastructure. The need for remote laboratories came after experiencing problems imposed by traditional laboratories. Among them are: the high cost of laboratory equipment, scarcity of space, scarcity of technical personnel along with the restricted university budget creates a significant bottleneck on building required laboratory experiments. The solution to these problems is to build web-accessible laboratories. Remote laboratories allow students and educators to interact with real laboratory equipment located anywhere in the world at anytime. Recently, many universities and other educational institutions especially in third world countries rely on simulations because they do not afford the experimental equipment they require to their students. Remote laboratories enable users to get real data from real-time hand-on experiments. To implement many remote laboratories, the system architecture should be flexible, understandable and easy to implement, so that different laboratories with different hardware can be deployed easily. The modifications were made to enable developers to add more equipment in ISA framework and to attract the new developers to develop many online laboratories.

Keywords: Batched, ISA, labserver, servicebroker.

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548 RUPSec: An Extension on RUP for Developing Secure Systems - Requirements Discipline

Authors: Mohammad Reza Ayatollahzadeh Shirazi, Pooya Jaferian, Golnaz Elahi, Hamid Baghi, Babak Sadeghian

Abstract:

The world is moving rapidly toward the deployment of information and communication systems. Nowadays, computing systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in development process of computing systems, specially in developing systems such as banking, military and e-business systems. For developing every system, a process model which includes a process, methods and tools is chosen. The Rational Unified Process (RUP) is one of the most popular and complete process models which is used by developers in recent years. This process model should be extended to be used in developing secure software systems. In this paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles, and Artifacts to RUP in order to capture, document and model threats and security requirements of system. These extensions introduce a group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are captured and modeled. These models are used in design, implementation and test activitie

Keywords:

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547 Microservices-Based Provisioning and Control of Network Services for Heterogeneous Networks

Authors: Shameemraj M. Nadaf, Sipra Behera, Hemant K. Rath, Garima Mishra, Raja Mukhopadhyay, Sumanta Patro

Abstract:

Microservices architecture has been widely embraced for rapid, frequent, and reliable delivery of complex applications. It enables organizations to evolve their technology stack in various domains. Today, the networking domain is flooded with plethora of devices and software solutions which address different functionalities ranging from elementary operations, viz., switching, routing, firewall etc., to complex analytics and insights based intelligent services. In this paper, we attempt to bring in the microservices based approach for agile and adaptive delivery of network services for any underlying networking technology. We discuss the life cycle management of each individual microservice and a distributed control approach with emphasis for dynamic provisioning, management, and orchestration in an automated fashion which can provide seamless operations in large scale networks. We have conducted validations of the system in lab testbed comprising of Traditional/Legacy and Software Defined Wireless Local Area networks.

Keywords: Microservices architecture, software defined wireless networks, traditional wireless networks, automation, orchestration, intelligent networks, network analytics, seamless management, single pane control, fine-grain control.

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546 A Multi-layer Artificial Neural Network Architecture Design for Load Forecasting in Power Systems

Authors: Axay J Mehta, Hema A Mehta, T.C.Manjunath, C. Ardil

Abstract:

In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.

Keywords: Power system, Load forecasting, Neural Network, Neuron, Stabilization, Network structure, Load.

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545 Electro-Thermal Imaging of Breast Phantom: An Experimental Study

Authors: H. Feza Carlak, N. G. Gencer

Abstract:

To increase the temperature contrast in thermal images, the characteristics of the electrical conductivity and thermal imaging modalities can be combined. In this experimental study, it is objected to observe whether the temperature contrast created by the tumor tissue can be improved just due to the current application within medical safety limits. Various thermal breast phantoms are developed to simulate the female breast tissue. In vitro experiments are implemented using a thermal infrared camera in a controlled manner. Since experiments are implemented in vitro, there is no metabolic heat generation and blood perfusion. Only the effects and results of the electrical stimulation are investigated. Experimental study is implemented with two-dimensional models. Temperature contrasts due to the tumor tissues are obtained. Cancerous tissue is determined using the difference and ratio of healthy and tumor images. 1 cm diameter single tumor tissue causes almost 40 °mC temperature contrast on the thermal-breast phantom. Electrode artifacts are reduced by taking the difference and ratio of background (healthy) and tumor images. Ratio of healthy and tumor images show that temperature contrast is increased by the current application.

Keywords: Medical diagnostic imaging, breast phantom, active thermography, breast cancer detection.

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544 Inversion of Electrical Resistivity Data: A Review

Authors: Shrey Sharma, Gunjan Kumar Verma

Abstract:

High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: Resistivity, inversion, optimization.

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543 Group Key Management Protocols: A Novel Taxonomy

Authors: Yacine Challal, Hamida Seba

Abstract:

Group key management is an important functional building block for any secure multicast architecture. Thereby, it has been extensively studied in the literature. In this paper we present relevant group key management protocols. Then, we compare them against some pertinent performance criteria.

Keywords: Multicast, Security, Group Key Management.

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542 A Watermarking Scheme for MP3 Audio Files

Authors: Dimitrios Koukopoulos, Yiannis Stamatiou

Abstract:

In this work, we present for the first time in our perception an efficient digital watermarking scheme for mpeg audio layer 3 files that operates directly in the compressed data domain, while manipulating the time and subband/channel domain. In addition, it does not need the original signal to detect the watermark. Our scheme was implemented taking special care for the efficient usage of the two limited resources of computer systems: time and space. It offers to the industrial user the capability of watermark embedding and detection in time immediately comparable to the real music time of the original audio file that depends on the mpeg compression, while the end user/audience does not face any artifacts or delays hearing the watermarked audio file. Furthermore, it overcomes the disadvantage of algorithms operating in the PCMData domain to be vulnerable to compression/recompression attacks, as it places the watermark in the scale factors domain and not in the digitized sound audio data. The strength of our scheme, that allows it to be used with success in both authentication and copyright protection, relies on the fact that it gives to the users the enhanced capability their ownership of the audio file not to be accomplished simply by detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark.

Keywords: Audio watermarking, mpeg audio layer 3, hardinstance generation, NP-completeness.

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541 An Efficient Watermarking Method for MP3 Audio Files

Authors: Dimitrios Koukopoulos, Yiannis Stamatiou

Abstract:

In this work, we present for the first time in our perception an efficient digital watermarking scheme for mpeg audio layer 3 files that operates directly in the compressed data domain, while manipulating the time and subband/channel domain. In addition, it does not need the original signal to detect the watermark. Our scheme was implemented taking special care for the efficient usage of the two limited resources of computer systems: time and space. It offers to the industrial user the capability of watermark embedding and detection in time immediately comparable to the real music time of the original audio file that depends on the mpeg compression, while the end user/audience does not face any artifacts or delays hearing the watermarked audio file. Furthermore, it overcomes the disadvantage of algorithms operating in the PCMData domain to be vulnerable to compression/recompression attacks, as it places the watermark in the scale factors domain and not in the digitized sound audio data. The strength of our scheme, that allows it to be used with success in both authentication and copyright protection, relies on the fact that it gives to the users the enhanced capability their ownership of the audio file not to be accomplished simply by detecting the bit pattern that comprises the watermark itself, but by showing that the legal owner knows a hard to compute property of the watermark.

Keywords: Audio watermarking, mpeg audio layer 3, hard instance generation, NP-completeness.

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540 A Semantic Registry to Support Brazilian Aeronautical Web Services Operations

Authors: Luís Antonio de Almeida Rodriguez, José Maria Parente de Oliveira, Ednelson Oliveira

Abstract:

In the last two decades, the world’s aviation authorities have made several attempts to create consensus about a global and accepted approach for applying semantics to web services registry descriptions. This problem has led communities to face a fat and disorganized infrastructure to describe aeronautical web services. It is usual for developers to implement ad-hoc connections among consumers and providers and manually create non-standardized service compositions, which need some particular approach to compose and semantically discover a desired web service. Current practices are not precise and tend to focus on lightweight specifications of some parts of the OWL-S and embed them into syntactic descriptions (SOAP artifacts and OWL language). It is necessary to have the ability to manage the use of both technologies. This paper presents an implementation of the ontology OWL-S that describes a Brazilian Aeronautical Web Service Registry, which makes it able to publish, advertise, make multi-criteria semantic discovery aligned with the ideas of the System Wide Information Management (SWIM) Program, and invoke web services within the Air Traffic Management context. The proposal’s best finding is a generic approach to describe semantic web services. The paper also presents a set of functional requirements to guide the ontology development and to compare them to the results to validate the implementation of the OWL-S Ontology.

Keywords: Aeronautical Web Services, OWL-S, Semantic Web Services Discovery, Ontologies.

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539 A Taxonomy of Group Key Management Protocols: Issues and Solutions

Authors: Yacine Challal, Abdelmadjid Bouabdallah, Hamida Seba

Abstract:

Group key management is an important functional building block for any secure multicast architecture. Thereby, it has been extensively studied in the literature. In this paper we present relevant group key management protocols. Then, we compare them against some pertinent performance criteria.

Keywords: Multicast, Security, Group Key Management.

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538 A Modular On-line Profit Sharing Approach in Multiagent Domains

Authors: Pucheng Zhou, Bingrong Hong

Abstract:

How to coordinate the behaviors of the agents through learning is a challenging problem within multi-agent domains. Because of its complexity, recent work has focused on how coordinated strategies can be learned. Here we are interested in using reinforcement learning techniques to learn the coordinated actions of a group of agents, without requiring explicit communication among them. However, traditional reinforcement learning methods are based on the assumption that the environment can be modeled as Markov Decision Process, which usually cannot be satisfied when multiple agents coexist in the same environment. Moreover, to effectively coordinate each agent-s behavior so as to achieve the goal, it-s necessary to augment the state of each agent with the information about other existing agents. Whereas, as the number of agents in a multiagent environment increases, the state space of each agent grows exponentially, which will cause the combinational explosion problem. Profit sharing is one of the reinforcement learning methods that allow agents to learn effective behaviors from their experiences even within non-Markovian environments. In this paper, to remedy the drawback of the original profit sharing approach that needs much memory to store each state-action pair during the learning process, we firstly address a kind of on-line rational profit sharing algorithm. Then, we integrate the advantages of modular learning architecture with on-line rational profit sharing algorithm, and propose a new modular reinforcement learning model. The effectiveness of the technique is demonstrated using the pursuit problem.

Keywords: Multi-agent learning; reinforcement learning; rationalprofit sharing; modular architecture.

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537 Graph Cuts Segmentation Approach Using a Patch-Based Similarity Measure Applied for Interactive CT Lung Image Segmentation

Authors: Aicha Majda, Abdelhamid El Hassani

Abstract:

Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: Graph cuts, lung CT scan, lung parenchyma segmentation, patch based similarity metric.

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536 The Traditional Malay Textile (TMT)Knowledge Model: Transformation towards Automated Mapping

Authors: Syerina Azlin Md Nasir, Nor Laila Md Noor, Suriyati Razali

Abstract:

The growing interest on national heritage preservation has led to intensive efforts on digital documentation of cultural heritage knowledge. Encapsulated within this effort is the focus on ontology development that will help facilitate the organization and retrieval of the knowledge. Ontologies surrounding cultural heritage domain are related to archives, museum and library information such as archaeology, artifacts, paintings, etc. The growth in number and size of ontologies indicates the well acceptance of its semantic enrichment in many emerging applications. Nowadays, there are many heritage information systems available for access. Among others is community-based e-museum designed to support the digital cultural heritage preservation. This work extends previous effort of developing the Traditional Malay Textile (TMT) Knowledge Model where the model is designed with the intention of auxiliary mapping with CIDOC CRM. Due to its internal constraints, the model needs to be transformed in advance. This paper addresses the issue by reviewing the previous harmonization works with CIDOC CRM as exemplars in refining the facets in the model particularly involving TMT-Artifact class. The result is an extensible model which could lead to a common view for automated mapping with CIDOC CRM. Hence, it promotes integration and exchange of textile information especially batik-related between communities in e-museum applications.

Keywords: automated mapping, cultural heritage, knowledgemodel, textile practice

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535 GC and GCxGC-MS Composition of Volatile Compounds from Carum carvi by Using Techniques Assisted by Microwaves

Authors: F. Benkaci-Ali, R. Mékaoui, G. Scholl, G. Eppe

Abstract:

The new methods as accelerated steam distillation assisted by microwave (ASDAM) is a combination of microwave heating and steam distillation, performed at atmospheric pressure at very short extraction time. Isolation and concentration of volatile compounds are performed by a single stage. (ASDAM) has been compared with (ASDAM) with cryogrinding of seeds (CG) and a conventional technique, hydrodistillation assisted by microwave (HDAM), hydro-distillation (HD) for the extraction of essential oil from aromatic herb as caraway and cumin seeds. The essential oils extracted by (ASDAM) for 1 min were quantitatively (yield) and qualitatively (aromatic profile) no similar to those obtained by ASDAM-CG (1 min) and HD (for 3 h). The accelerated microwave extraction with cryogrinding inhibits numerous enzymatic reactions as hydrolysis of oils. Microwave radiations constitute the adequate mean for the extraction operations from the yields and high content in major component majority point view, and allow to minimise considerably the energy consumption, but especially heating time too, which is one of essential parameters of artifacts formation. The ASDAM and ASDAM-CG are green techniques and yields an essential oil with higher amounts of more valuable oxygenated compounds comparable to the biosynthesis compounds, and allows substantial savings of costs, in terms of time, energy and plant material.

Keywords: Microwave, steam distillation, caraway, cumin, cryogrinding, GC-MS, GCxGC-MS.

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534 A Domain Specific Modeling Language Semantic Model for Artefact Orientation

Authors: Bunakiye R. Japheth, Ogude U. Cyril

Abstract:

Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: Control process, metrics of engineering, structured abstraction, semantic model.

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533 Bridged Quantum Cellular Automata based on Si/SiO2 Superlattices

Authors: I.V. Matyushkin

Abstract:

The new architecture for quantum cellular automata is offered. A QCA cell includes two layers nc-Si, divided by a dielectric. Among themselves cells are connected by the bridge from a conductive material. The comparison is made between this and QCA, offered earlier by C. Lent's group.

Keywords: quantum cellular automata (QCA), nc-Si, Si/SiO2 superlattices, parallel computing

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532 Dynamic Threshold Adjustment Approach For Neural Networks

Authors: Hamza A. Ali, Waleed A. J. Rasheed

Abstract:

The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.

Keywords: Classification, Recognition, Neural Networks, Pattern Recognition, Generalization.

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531 A Design of Elliptic Curve Cryptography Processor Based on SM2 over GF(p)

Authors: Shiji Hu, Lei Li, Wanting Zhou, Daohong Yang

Abstract:

The data encryption is the foundation of today’s communication. On this basis, to improve the speed of data encryption and decryption is always an important goal for high-speed applications. This paper proposed an elliptic curve crypto processor architecture based on SM2 prime field. Regarding hardware implementation, we optimized the algorithms in different stages of the structure. For modulo operation on finite field, we proposed an optimized improvement of the Karatsuba-Ofman multiplication algorithm and shortened the critical path through the pipeline structure in the algorithm implementation. Based on SM2 recommended prime field, a fast modular reduction algorithm is used to reduce 512-bit data obtained from the multiplication unit. The radix-4 extended Euclidean algorithm was used to realize the conversion between the affine coordinate system and the Jacobi projective coordinate system. In the parallel scheduling point operations on elliptic curves, we proposed a three-level parallel structure of point addition and point double based on the Jacobian projective coordinate system. Combined with the scalar multiplication algorithm, we added mutual pre-operation to the point addition and double point operation to improve the efficiency of the scalar point multiplication. The proposed ECC hardware architecture was verified and implemented on Xilinx Virtex-7 and ZYNQ-7 platforms, and each 256-bit scalar multiplication operation took 0.275ms. The performance for handling scalar multiplication is 32 times that of CPU (dual-core ARM Cortex-A9).

Keywords: Elliptic curve cryptosystems, SM2, modular multiplication, point multiplication.

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530 A Ground Structure Method to Minimize the Total Installed Cost of Steel Frame Structures

Authors: Filippo Ranalli, Forest Flager, Martin Fischer

Abstract:

This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: Cost-based structural optimization, cost-based topology and sizing optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures.

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529 Complex Wavelet Transform Based Image Denoising and Zooming Under the LMMSE Framework

Authors: T. P. Athira, Gibin Chacko George

Abstract:

This paper proposes a dual tree complex wavelet transform (DT-CWT) based directional interpolation scheme for noisy images. The problems of denoising and interpolation are modelled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT-CWT is used to decompose an input low-resolution noisy image into low and high frequency subbands. The high-frequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in tandem, the proposed DT-CWT based noisy image interpolation method can reduce many noise-caused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.

Keywords: Dual-tree complex wavelet transform (DT-CWT), denoising, interpolation, optimal estimation, super resolution.

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528 Biologically Inspired Artificial Neural Cortex Architecture and its Formalism

Authors: Alexei M. Mikhailov

Abstract:

The paper attempts to elucidate the columnar structure of the cortex by answering the following questions. (1) Why the cortical neurons with similar interests tend to be vertically arrayed forming what is known as cortical columns? (2) How to describe the cortex as a whole in concise mathematical terms? (3) How to design efficient digital models of the cortex?

Keywords: Cortex, pattern recognition, artificial neural cortex, computational biology, brain and neural engineering.

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527 Multi-Agent Systems Applied in the Modeling and Simulation of Biological Problems: A Case Study in Protein Folding

Authors: Pedro Pablo González Pérez, Hiram I. Beltrán, Arturo Rojo-Domínguez, Máximo EduardoSánchez Gutiérrez

Abstract:

Multi-agent system approach has proven to be an effective and appropriate abstraction level to construct whole models of a diversity of biological problems, integrating aspects which can be found both in "micro" and "macro" approaches when modeling this type of phenomena. Taking into account these considerations, this paper presents the important computational characteristics to be gathered into a novel bioinformatics framework built upon a multiagent architecture. The version of the tool presented herein allows studying and exploring complex problems belonging principally to structural biology, such as protein folding. The bioinformatics framework is used as a virtual laboratory to explore a minimalist model of protein folding as a test case. In order to show the laboratory concept of the platform as well as its flexibility and adaptability, we studied the folding of two particular sequences, one of 45-mer and another of 64-mer, both described by an HP model (only hydrophobic and polar residues) and coarse grained 2D-square lattice. According to the discussion section of this piece of work, these two sequences were chosen as breaking points towards the platform, in order to determine the tools to be created or improved in such a way to overcome the needs of a particular computation and analysis of a given tough sequence. The backwards philosophy herein is that the continuous studying of sequences provides itself important points to be added into the platform, to any time improve its efficiency, as is demonstrated herein.

Keywords: multi-agent systems, blackboard-based agent architecture, bioinformatics framework, virtual laboratory, protein folding.

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526 Analyzing the Shearing-Layer Concept Applied to Urban Green System

Authors: S. Pushkar, O. Verbitsky

Abstract:

Currently, green rating systems are mainly utilized for correctly sizing mechanical and electrical systems, which have short lifetime expectancies. In these systems, passive solar and bio-climatic architecture, which have long lifetime expectancies, are neglected. Urban rating systems consider buildings and services in addition to neighborhoods and public transportation as integral parts of the built environment. The main goal of this study was to develop a more consistent point allocation system for urban building standards by using six different lifetime shearing layers: Site, Structure, Skin, Services, Space, and Stuff, each reflecting distinct environmental damages. This shearing-layer concept was applied to internationally well-known rating systems: Leadership in Energy and Environmental Design (LEED) for Neighborhood Development, BRE Environmental Assessment Method (BREEAM) for Communities and Comprehensive Assessment System for Building Environmental Efficiency (CASBEE) for Urban Development. The results showed that LEED for Neighborhood Development and BREEAM for Communities focused on long-lifetime-expectancy building designs, whereas CASBEE for Urban Development gave equal importance to the Building and Service Layers. Moreover, although this rating system was applied using a building-scale assessment, “Urban Area + Buildings” focuses on a short-lifetime-expectancy system design, neglecting to improve the architectural design by considering bioclimatic and passive solar aspects.

Keywords: Green rating system, passive solar architecture, shearing-layer concept, urban community.

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525 Optimized Brain Computer Interface System for Unspoken Speech Recognition: Role of Wernicke Area

Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

Abstract:

In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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524 Cellular Automata Based Robust Watermarking Architecture towards the VLSI Realization

Authors: V. H. Mankar, T. S. Das, S. K. Sarkar

Abstract:

In this paper, we have proposed a novel blind watermarking architecture towards its hardware implementation in VLSI. In order to facilitate this hardware realization, cellular automata (CA) concept is introduced. The CA has been already accepted as an attractive structure for VLSI implementation because of its modularity, parallelism, high performance and reliability. The hardware realizable multiresolution spread spectrum watermarking techniques are very few in numbers in spite of their best ever resiliency against signal impairments. This is because of the computational cost and complexity associated with their different filter banks and lifting techniques. The concept of cellular automata theory in order to form a new transform domain technique i.e. Cellular Automata Transform (CAT) have been incorporated. Since CA provides spreading sequences having very low cross-correlation properties, the CA based pseudorandom sequence generator is considered in the present work. Considering the watermarking technique as a digital communication process, an error control coding (ECC) must be incorporated in the data hiding schemes. Besides the hardware implementation of entire CA based data hiding technique, the individual blocks of the algorithm using CA provide the best result than that of some other methods irrespective of the hardware and software technique. The Cellular Automata Transform, CA based PN sequence generator, and CA ECC are the requisite blocks that are developed not only to meet the reliable hardware requirements but also for the basic spread spectrum watermarking features. The proposed algorithm shows statistical invisibility and resiliency against various common signal-processing operations. This algorithmic design utilizes the existing allocated bandwidth in the data transmission channel in a more efficient manner.

Keywords: Cellular automata, watermarking, error control coding, PN sequence, VLSI.

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523 Creating Customer Value through SOA and Outsourcing: A NEBIC Approach

Authors: Benazeer Md. Shahzada, Verelst Jan, Van Grembergen Wim, Mannaert Herwig

Abstract:

This article is an extension and a practical application approach of Wheeler-s NEBIC theory (Net Enabled Business Innovation Cycle). NEBIC theory is a new approach in IS research and can be used for dynamic environment related to new technology. Firms can follow the market changes rapidly with support of the IT resources. Flexible firms adapt their market strategies, and respond more quickly to customers changing behaviors. When every leading firm in an industry has access to the same IT resources, the way that these IT resources are managed will determine the competitive advantages or disadvantages of firm. From Dynamic Capabilities Perspective and from newly introduced NEBIC theory by Wheeler, we know that only IT resources cannot deliver customer value but good configuration of those resources can guarantee customer value by choosing the right emerging technology, grasping the right economic opportunities through business innovation and growth. We found evidences in literature that SOA (Service Oriented Architecture) is a promising emerging technology which can deliver the desired economic opportunity through modularity, flexibility and loose-coupling. SOA can also help firms to connect in network which can open a new window of opportunity to collaborate in innovation and right kind of outsourcing. There are many articles and research reports indicates that failure rate in outsourcing is very high but at the same time research indicates that successful outsourcing projects adds tangible and intangible benefits to the service consumer. Business executives and policy makers in the west should not afraid of outsourcing but they should choose the right strategy through the use of emerging technology to significantly reduce the failure rate in outsourcing.

Keywords: Absorptive capacity, Dynamic Capability, Netenabled business innovation cycle, Service oriented architecture.

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