Search results for: Pattern Matching.

Authors: Rupaban Subadar

Abstract:

Performance of a dual maximal ratio combining receiver has been analyzed for M-ary coherent and non-coherent modulations over correlated Nakagami-m fading channels with nonidentical and arbitrary fading parameter. The classical probability density function (PDF) based approach is used for analysis. Expressions for outage probability and average symbol error performance for M-ary coherent and non-coherent modulations have been obtained. The obtained results are verified against the special case published results and found to be matching. The effect of the unequal fading parameters, branch correlation and unequal input average SNR on the receiver performance has been studied.

Keywords: MRC, correlated Nakagami-m fading, non-identicalfading statistics, average symbol error rate

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Authors: Md Khairullah, Hai-Xiang Lin, Remus G. Hanea, Arnold W. Heemink

Abstract:

In this paper we describe the design and implementation of a parallel algorithm for data assimilation with ensemble Kalman filter (EnKF) for oil reservoir history matching problem. The use of large number of observations from time-lapse seismic leads to a large turnaround time for the analysis step, in addition to the time consuming simulations of the realizations. For efficient parallelization it is important to consider parallel computation at the analysis step. Our experiments show that parallelization of the analysis step in addition to the forecast step has good scalability, exploiting the same set of resources with some additional efforts.

Keywords: EnKF, Data assimilation, Parallel computing, Parallel efficiency.

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Authors: Mohammed Salahat, Steve Wade, Izhar Ul-Haq

Abstract:

This paper proposes a “soft systems" approach to domain-driven design of computer-based information systems. We propose a systemic framework combining techniques from Soft Systems Methodology (SSM), the Unified Modelling Language (UML), and an implementation pattern known as “Naked Objects". We have used this framework in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within the proposed framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to generate a ubiquitous language (soft language) which can be used as the basis for developing an object-oriented domain model. The domain model is further developed using techniques based on the UML and is implemented in software following the “Naked Objects" implementation pattern. We argue that there are advantages from combining and using techniques from different methodologies in this way. The proposed systemic framework is overviewed and justified as multimethodologyusing Mingers multimethodology ideas. This multimethodology approach is being evaluated through a series of action research projects based on real-world case studies. A Peer-Tutoring case study is presented here as a sample of the framework evaluation process

Keywords: SSM, UML, Domain-Driven Design, Soft Domain-Driven Design, Naked Objects, Soft Languag e.

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Authors: Fotios N. Vlachos, Anastasios D. Garetsos, Nikolaos K. Uzunoglu, Efstathios D. Gotsis

Abstract:

A four element prototype phased array surface probe has been designed and constructed to improve clinical human prostate spectroscopic data. The probe consists of two pairs of adjacent rectangular coils with an optimum overlap to reduce the mutual inductance. The two pairs are positioned on the anterior and the posterior pelvic region and two couples of varactors at the input of each coil undertake the procedures of tuning and matching. The probe switches off and on automatically during the consecutive phases of the MR experiment with the use of an analog switch that is triggered by a microcontroller. Experimental tests that were carried out resulted in high levels of tuning accuracy. Also, the switching mechanism functions properly for various applied loads and pulse sequence characteristics, producing only 10 μs of latency.

Keywords: Automatic tuning, prostate imaging, phased array, spectroscopy.

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Authors: Oğuzhan Urhan

Abstract:

In this paper, an improved motion estimation (ME) approach based on weighted constrained one-bit transform is proposed for block-based ME employed in video encoders. Binary ME approaches utilize low bit-depth representation of the original image frames with a Boolean exclusive-OR based hardware efficient matching criterion to decrease computational burden of the ME stage. Weighted constrained one-bit transform (WC‑1BT) based approach improves the performance of conventional C-1BT based ME employing 2-bit depth constraint mask instead of a 1-bit depth mask. In this work, the range of constraint mask is further extended to increase ME performance of WC-1BT approach. Experiments reveal that the proposed method provides better ME accuracy compared existing similar ME methods in the literature.

Keywords: Fast motion estimation, low-complexity motion estimation, video coding.

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Authors: Zina Saheb, Ezz El-Masry, Jean-François Bousquet

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This paper presents an enhanced efficiency simultaneous dual band energy harvesting system for wireless body area network. A bulk biasing is used to enhance the efficiency of the adapted rectifier design to reduce V_th of MOSFET. The presented circuit harvests the radio frequency (RF) energy from two frequency bands: 1 GHz and 2.4 GHz. It is designed with TSMC 65-nm CMOS technology and high quality factor dual matching network to boost the input voltage. Full circuit analysis and modeling is demonstrated. The simulation results demonstrate a harvester with an efficiency of 23% at 1 GHz and 46% at 2.4 GHz at an input power as low as -30 dBm.

Keywords: Energy harvester, simultaneous, dual band, CMOS, differential rectifier, voltage boosting, TSMC 65nm.

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Authors: A. Elbyed

Abstract:

Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.

Keywords: Resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning.

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Authors: Kesari Verma, Aniruddha S. Thoke, Pritam Singh

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Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lighting condition. In the field of face recognition technique the single face is matched with single face from the training dataset. The author proposed a neural network based face detection algorithm from the photographs as well as if any test data appears it check from the online scanned training dataset. Experimental result shows that the algorithm detected up to 95% accuracy for any image.

Keywords: Face Detection, Face Recognition, NN Approach, PCA Algorithm.

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Authors: Udeni Jayasinghe, Anuja Dharmaratne

Abstract:

Each year many people are reported missing in most of the countries in the world owing to various reasons. Arrangements have to be made to find these people after some time. So the investigating agencies are compelled to make out these people by using manpower. But in many cases, the investigations carried out to find out an absconding for a long time may not be successful. At a time like that it may be difficult to identify these people by examining their old photographs, because their facial appearance might have changed mainly due to the natural aging process. On some occasions in forensic medicine if a dead body is found, investigations should be held to make sure that this corpse belongs to the same person disappeared some time ago. With the passage of time the face of the person might have changed and there should be a mechanism to reveal the person-s identity. In order to make this process easy, we must guess and decide as to how he will look like by now. To address this problem this paper presents a way of synthesizing a facial image with the aging effects.

Keywords: Cranio-facial growth model, eigenfaces, eigenvectors, Face Anthropometry.

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Authors: Mohammad Faisal

Abstract:

This paper investigates the relationship between state and business in the context of structural and institutional transformations in Indonesia following the collapse of the New Order regime in 1998. Since 1998, Indonesia has embarked on a shift from an authoritarian to democratic polity and from a centralised to a decentralised system of governance, transforming the country into the third largest democracy and one of the most decentralised states in the world. This paper examines whether the transformation of the Indonesian state has altered the pattern of state and business relations with focus on clientism and corruption as the key dependent variable, and probes how/to what extent this has changed as a result of the transformation and the ensuring shifts in business and state relations. Based on interviews with key government and business actors as well as prominent scholars in Indonesia, it is found that since the demise of the New Order, business associations in Indonesia have become more independent of state control and more influential in public decision-making whereas the government has become more responsive of business concerns and more committed to combat corruption and clientism. However, these changes have not necessarily rendered business people completely leave individualclientelistic relationship with the government, and simply pursue wider sectoral and business-wide collectivism as an alternative way of channelling their aspirations, which is expected to help reduce corruption and clientism in Indonesia. This paper concludes that democratisation and a more open politics may have helped reduce corruption and clientism in Indonesia through changes in government. However, it is still difficult to imply that such political transformation has fostered business collective action and a broader, more encompassing pattern of business lobbying and activism, which is expected to help reduce corruption and clientism.

Keywords: Business activism, business power, democratisation, clientism, corruption.

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Authors: N. Valliammal, S.N. Geethalakshmi

Abstract:

This paper describes an optimal approach for feature subset selection to classify the leaves based on Genetic Algorithm (GA) and Kernel Based Principle Component Analysis (KPCA). Due to high complexity in the selection of the optimal features, the classification has become a critical task to analyse the leaf image data. Initially the shape, texture and colour features are extracted from the leaf images. These extracted features are optimized through the separate functioning of GA and KPCA. This approach performs an intersection operation over the subsets obtained from the optimization process. Finally, the most common matching subset is forwarded to train the Support Vector Machine (SVM). Our experimental results successfully prove that the application of GA and KPCA for feature subset selection using SVM as a classifier is computationally effective and improves the accuracy of the classifier.

Keywords: Optimization, Feature extraction, Feature subset, Classification, GA, KPCA, SVM and Computation

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Authors: Ananth Kamath, Ankit Kant, Aravind Srivatsa, Harisha J.A

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Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv (LZ) family, Dynamic Markov Compression (DMC), Prediction by Partial Matching (PPM), and Burrows-Wheeler Transform (BWT) based algorithms. Decompression is also required to retrieve the original data by lossless means. A compression scheme for text files coupled with the principle of dynamic decompression, which decompresses only the section of the compressed text file required by the user instead of decompressing the entire text file. Dynamic decompressed files offer better disk space utilization due to higher compression ratios compared to most of the currently available text file formats.

Keywords: Compression, Dynamic Decompression, Text file format, Portable Document Format, Compression Ratio.

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Authors: Changwoo Byun, Kyounghan Lee, Seog Park

Abstract:

XML is becoming a de facto standard for online data exchange. Existing XML filtering techniques based on a publish/subscribe model are focused on the highly structured data marked up with XML tags. These techniques are efficient in filtering the documents of data-centric XML but are not effective in filtering the element contents of the document-centric XML. In this paper, we propose an extended XPath specification which includes a special matching character '%' used in the LIKE operation of SQL in order to solve the difficulty of writing some queries to adequately filter element contents using the previous XPath specification. We also present a novel technique for filtering a collection of document-centric XMLs, called Pfilter, which is able to exploit the extended XPath specification. We show several performance studies, efficiency and scalability using the multi-query processing time (MQPT).

Keywords: XML Data Stream, Document-centric XML, Filtering Technique, Value-based Predicates.

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Authors: Hirotaka Watanabe, Takaaki Kondo, Daiki Yoshida, Ariyoshi Nakayama, Taichi Sato, Shuhei Kuriyama, Hiroyuki Kamata

Abstract:

In this paper, we propose a chaotic cipher system consisting of Improved Volterra Filters and the mapping that is created from the actual voice by using Radial Basis Function Network. In order to achieve a practical system, the system supposes to use the digital communication line, such as the Internet, to maintain the parameter matching between the transmitter and receiver sides. Therefore, in order to withstand the attack from outside, it is necessary that complicate the internal state and improve the sensitivity coefficient. In this paper, we validate the robustness of proposed method from three perspectives of "Chaotic properties", "Randomness", "Coefficient sensitivity".

Keywords: Chaos cipher, 16-bit-length fixed point arithmetic, Volterra filter, Seacret communications, RBF Network

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Authors: Jun Luo, Weiguo Zhang., Dabin Qin

Abstract:

It is important to retain customer satisfaction in information technology services. When a service failure occurs, companies need to take service recovery action to recover their customer satisfaction. Although companies cannot avoid all problems and complaints, they should try to make up. Therefore, service failure and service recovery have become an important and challenging issue for companies. In this paper, the literature and the problems in the information technology services were reviewed. An integrated model of profit driven for the service failure and service recovery was established in view of the benefit of customer and enterprise. Moreover, the interaction between service failure and service recovery strategy was studied, the result of which verified the matching principles of the service recovery strategy and the type of service failure. In addition, the relationship between the cost of service recovery and customer-s cumulative value of service after recovery was analyzed with the model. The result attributes to managers in deciding on appropriate resource allocations for recovery strategies.

Keywords: service failure, service recovery, informationtechnology services

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Authors: P. Cermak

Abstract:

This paper shows possibility of extraction Social, Group and Individual Mind from Multiple Agents Rule Bases. Types those Rule bases are selected as two fuzzy systems, namely Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are describing (modeling) agent behavior. Modifying of agent behavior in the time varying environment will be provided by learning fuzzyneural networks and optimization of their parameters with using genetic algorithms in development system FUZNET. Finally, extraction Social, Group and Individual Mind from Multiple Agents Rule Bases are provided by Cognitive analysis and Matching criterion.

Keywords: Mind, Multi-agent system, Cognitive analysis, Fuzzy system, Neural network, Genetic algorithm, Rule base.

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Authors: Manal Hassan Abdel Aziz, Fatma Mohamed Magdy Badr El Dine, Nourhan Mohamed Mohamed Saeed

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Establishing association between lip print patterns and those of fingerprints as well as blood groups is of fundamental importance in the forensic identification domain. The first aim of the current study was to determine the prevalent types of ABO blood groups, lip prints and fingerprints patterns in both studied populations. Secondly, to analyze any relation found between the different print patterns and the blood groups, which would be valuable in identification purposes. The present study was conducted on 60 healthy volunteers, (30 males and 30 females) from each of the studied population. Lip prints and fingerprints were obtained and classified according to Tsuchihashi's classification and Michael Kuchen’s classification, respectively. The results show that the ulnar loop was the most frequent among both populations. Blood group A was the most frequent among Egyptians, while blood groups O and B were the predominant among Malaysians. Significant relations were observed between lip print patterns and fingerprint (in the second quadrant for Egyptian males and the first one for Malaysian). For Malaysian females, a statistically significant association was proved in the fourth quadrant. Regarding the blood groups, 89.5% of ulnar loops were significantly related to blood group A among Egyptian males. The results proved an association between the fingerprint pattern and the lip prints, as well as between the ABO blood group and the pattern of fingerprints. However, further researches with larger sample sizes need to be directed to approve the current results.

Keywords: ABO, cheiloscopy, dactylography, Egyptians, Malaysians.

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Authors: Rahmatollah Hooshmand, Mahdi Banejad

Abstract:

One of the problems in fault diagnosis of transformer based on dissolved gas, is lack of matching the result of fault diagnosis of different standards with the real world. In this paper, the result of the different standards is analyzed using fuzzy and the result is compared with the empirical test. The comparison between the suggested method and existing methods indicate the capability of the suggested method in on-line fault diagnosis of the transformers. In addition, in some cases the existing standards are not able to diagnose the fault. In theses cases, the presented method has the potential of diagnosing the fault. The information of three transformers is used to the show the capability of the suggested method in diagnosing the fault. The results validate the capability of the presented method in fault diagnosis of the transformer.

Keywords: Fault Diagnosis of Transformer, Dissolved Gas, Fuzzy Logic.

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Authors: Yannick Verbelen, Tim Dekegel, Ann Peeters, Klara Stinders, Niek Blondeel, Sam De Winne, An Braeken, Abdellah Touhafi

Abstract:

Matching an embedded electronic application with a cantilever vibration energy harvester remains a difficult endeavour due to the large number of factors influencing the output power. In the presented work, complementary balanced energy harvester parametrization is used as a methodology for simplification of harvester integration in electronic applications. This is achieved by a dual approach consisting of an adaptation of the general parametrization methodology in conjunction with a straight forward harvester benchmarking strategy. For this purpose, the design and implementation of a suitable user friendly cantilever energy harvester benchmarking platform is discussed. Its effectiveness is demonstrated by applying the methodology to a commercially available Mide V21BL vibration energy harvester, with excitation amplitude and frequency as variables.

Keywords: Energy harvesting, vibrations, piezoelectric transducers, embedded systems, harvester parametrization.

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Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms.

Keywords: Cuttlefish Algorithm, bio-inspired algorithms, optimization.

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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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Authors: Fereshteh Shacheraghi, Mohammad Reza Shakibaie, Hanieh Noveiri

Abstract:

Fourty one strains of ESBL producing P.aeruginosa which were previously isolated from burn patients in Kerman University general hospital, Iran were subjected to PCR, RFLP and sequencing in order to determine the type of extended spectrum β- lactamases (ESBL), the restriction digestion pattern and possibility of mutation among detected genes. DNA extraction was carried out by phenol chloroform method. PCR for detection of bla genes was performed using specific primer for each gene. Restriction Fragment Length Polymorphism (RFLP) for ESBL genes was carried out using EcoRI, NheI, PVUII, EcoRV, DdeI, and PstI restriction enzymes. The PCR products were subjected to direct sequencing of both the strands for identification of the ESBL genes.The blaCTX-M, blaVEB-1, blaPER-1, blaGES-1, blaOXA-1, blaOXA-4 and blaOXA-10 genes were detected in the (n=1) 2.43%, (n=41)100%, (n=28) 68.3%, (n=10) 24.4%, (n=29) 70.7%, (n=7)17.1% and (n=38) 92.7% of the ESBL producing isolates respectively. The RFLP analysis showed that each ESBL gene has identical pattern of digestion among the isolated strains. Sequencing of the ESBL genes confirmed the genuinety of PCR products and revealed no mutation in the restriction sites of the above genes. From results of the present investigation it can be concluded that blaVEB-1 and blaCTX-M were the most and the least frequently isolated ESBL genes among the P.aeruginosa strains isolated from burn patients. The RFLP and sequencing analysis revealed that same clone of the bla genes were indeed existed among the antibiotic resistant strains.

Keywords: ESBL genes, PCR, RFLP, Sequencing, P.aeruginosa

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Authors: Hye-Young Shin, Chan Kee Park

Abstract:

Background: To compare the thinning patterns of the ganglion cell-inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) as measured using Cirrus high-definition optical coherence tomography (HD-OCT) in patients with visual field (VF) defects that respect the vertical meridian. Methods: Twenty eyes of eleven patients with VF defects that respect the vertical meridian were enrolled retrospectively. The thicknesses of the macular GCIPL and pRNFL were measured using Cirrus HD-OCT. The 5% and 1% thinning area index (TAI) was calculated as the proportion of abnormally thin sectors at the 5% and 1% probability level within the area corresponding to the affected VF. The 5% and 1% TAI were compared between the GCIPL and pRNFL measurements. Results: The color-coded GCIPL deviation map showed a characteristic vertical thinning pattern of the GCIPL, which is also seen in the VF of patients with brain lesions. The 5% and 1% TAI were significantly higher in the GCIPL measurements than in the pRNFL measurements (all P < 0.01). Conclusions: Macular GCIPL analysis clearly visualized a characteristic topographic pattern of retinal ganglion cell (RGC) loss in patients with VF defects that respect the vertical meridian, unlike pRNFL measurements. Macular GCIPL measurements provide more valuable information than pRNFL measurements for detecting the loss of RGCs in patients with retrograde degeneration of the optic nerve fibers.

Keywords: Brain lesion, Macular ganglion cell-Inner plexiform layer, Spectral-domain optical coherence tomography.

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Authors: Yi Zhang, Quan Zhou, Jun Li, Yanlang Hu

Abstract:

Scheduling algorithm is a key technology in satellite switching system with input-buffer. In this paper, a new scheduling algorithm and its realization are proposed. Based on Crossbar switching fabric, the algorithm adopts serial scheduling strategy and adjusts the output port arbitrating strategy for the better equity of every port. Consequently, it increases the matching probability. The algorithm can greatly reduce the scheduling delay and cell loss rate. The analysis and simulation results by OPNET show that the proposed algorithm has the better performance than others in average delay and cell loss rate, and has the equivalent complexity. On the basis of these results, the hardware realization and simulation based on FPGA are completed, which validate the feasibility of the new scheduling algorithm.

Keywords: Scheduling algorithm, input-buffer, serial scheduling, hardware design.

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Authors: Irene Luque Ruiz, Manuel Urbano Cuadrado, Miguel Ángel Gómez-Nieto

Abstract:

In this paper we study different similarity based approaches for the development of QSAR model devoted to the prediction of activity of antiobesity drugs. Classical similarity approaches are compared regarding to dissimilarity models based on the consideration of the calculation of Euclidean distances between the nonisomorphic fragments extracted in the matching process. Combining the classical similarity and dissimilarity approaches into a new similarity measure, the Approximate Similarity was also studied, and better results were obtained. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting of inhibitory activity of drugs. Acceptable results were obtained for the models presented here.

Keywords: Graph similarity, Nonisomorphic dissimilarity, Approximate similarity, Drugs activity prediction.

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Authors: O. Abusaeeda, J. P. O Evans, D. Downes

Abstract:

We demonstrate the synthesis of intermediary views within a sequence of color encoded, materials discriminating, X-ray images that exhibit animated depth in a visual display. During the image acquisition process, the requirement for a linear X-ray detector array is replaced by synthetic image. Scale Invariant Feature Transform, SIFT, in combination with material segmented morphing is employed to produce synthetic imagery. A quantitative analysis of the feature matching performance of the SIFT is presented along with a comparative study of the synthetic imagery. We show that the total number of matches produced by SIFT reduces as the angular separation between the generating views increases. This effect is accompanied by an increase in the total number of synthetic pixel errors. The trends observed are obtained from 15 different luggage items. This programme of research is in collaboration with the UK Home Office and the US Dept. of Homeland Security.

Keywords: X-ray, kinetic depth, view synthesis, KDE

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

Abstract:

Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN.

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Authors: M. Habchi, S. M. Mesli, M. Kotbi

Abstract:

A structural study of an aqueous electrolyte whose experimental results are available. It is a solution of LiCl-6H2O type at glassy state (120K) contrasted with pure water at room temperature by means of Partial Distribution Functions (PDF) issue from neutron scattering technique. Based on these partial functions, the Reverse Monte Carlo method (RMC) computes radial and angular correlation functions which allow exploring a number of structural features of the system. The obtained curves include some artifacts. To remedy this, we propose to introduce a screened potential as an additional constraint. Obtained results show a good matching between experimental and computed functions and a significant improvement in PDFs curves with potential constraint. It suggests an efficient fit of pair distribution functions curves.

Keywords: RMC simulation; Screened potential; partial and pair distribution functions; glassy and liquid state

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