Search results for: suprasegmental features.

Authors: Sabah I. Wais, Raghad Y. Mohammed, Sedki O. Yousif

Abstract:

The influence of axial magnetic field (B=0.48 T) on the variation of ionization efficiency coefficient h and secondary electron emission coefficient g with respect to reduced electric field E/P is studied at a new range of plane-parallel electrode spacing (0< d< 20 cm) and different nitrogen working pressure between 0.5-20 Pa. The axial magnetic field is produced from an inductive copper coil of radius 5.6 cm. The experimental data of breakdown voltage is adopted to estimate the mean Paschen curves at different working features. The secondary electron emission coefficient is calculated from the mean Paschen curve and used to determine the minimum breakdown voltage. A reduction of discharge voltage of about 25% is investigated by the applied of axial magnetic field. At high interelectrode spacing, the effect of axial magnetic field becomes more significant for the obtained values of h but it was less for the values of g.

Keywords: Paschen curve, Townsend coefficient, Secondaryelectron emission, Magnetic field, Minimum breakdown voltage.

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: Electrocardiogram, dictionary learning, sparse coding, classification.

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

Abstract:

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

Keywords: Spin-orbit, Zeeman, top-gate, finger-gate, bound state.

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Authors: Sandro Mourão, Karla Okada

Abstract:

The necessity of accurate and timely field data is shared among organizations engaged in fundamentally different activities, public services or commercial operations. Basically, there are three major components in the process of the qualitative research: data collection, interpretation and organization of data, and analytic process. Representative technological advancements in terms of innovation have been made in mobile devices (mobile phone, PDA-s, tablets, laptops, etc). Resources that can be potentially applied on the data collection activity for field researches in order to improve this process. This paper presents and discuss the main features of a mobile phone based solution for field data collection, composed of basically three modules: a survey editor, a server web application and a client mobile application. The data gathering process begins with the survey creation module, which enables the production of tailored questionnaires. The field workforce receives the questionnaire(s) on their mobile phones to collect the interviews responses and sending them back to a server for immediate analysis.

Keywords: Data Gathering, Field Research, Mobile Phone, Survey.

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Authors: K. Santacruz-Gomez, E. Silva-Campa, S. Álvarez-García, V. Mata-Haro, D. Soto-Puebla, M. Pedroza-Montero

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Blood gamma irradiation is the only available method to prevent transfusion associated graft versus host disease (TAGVHD). However, when blood is irradiated, determine blood shelf time is crucial. Non irradiated blood have a self-time from 21 to 35 days when is preserved with anticoagulated solution and stored at 4°C. During their storage, red blood cells (RBC) undergo a series of biochemical, biomechanical and molecular changes involving what is known as storage lesion (SL). SL include loss of structural integrity of RBC, decrease of 2,3-diphosphatidylglyceric acid levels, and increase of both ion potassium concentration and hemoglobin (Hb). On the other hand, Atomic force Microscopy (AFM) represents a versatile tool for a nano-scale high resolution topographic analysis in biological systems. In order to evaluate SL in irradiated and nonirradiated blood, RBC topography and morphometric parameters were obtained from an AFM XE-BIO system. Cell viability was followed using flow cytometry. Our results showed that early markers as nanoscale roughness, allow us to evaluate blood quality since other perspective.

Keywords: AFM, Blood γ-irradiation, roughness, Storage lesion.

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Authors: Amirhossein Safi

Abstract:

Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: Internet of things, security, hybrid algorithm, privacy.

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Authors: Ming-Hui Cheng, Jyh-Horng Jeng

Abstract:

In this study, a classification-based video super-resolution method using artificial neural network (ANN) is proposed to enhance low-resolution (LR) to high-resolution (HR) frames. The proposed method consists of four main steps: classification, motion-trace volume collection, temporal adjustment, and ANN prediction. A classifier is designed based on the edge properties of a pixel in the LR frame to identify the spatial information. To exploit the spatio-temporal information, a motion-trace volume is collected using motion estimation, which can eliminate unfathomable object motion in the LR frames. In addition, temporal lateral process is employed for volume adjustment to reduce unnecessary temporal features. Finally, ANN is applied to each class to learn the complicated spatio-temporal relationship between LR and HR frames. Simulation results show that the proposed method successfully improves both peak signal-to-noise ratio and perceptual quality.

Keywords: Super-resolution, classification, spatio-temporal information, artificial neural network.

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Authors: José A. D. Machuca, Bernabé Escobar-Pérez, Pedro Garrido Vega, Darkys E. Lujan García

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Starting with an analysis of the financial and operational indicators that can be found in the specialised literature, this study aims to contribute to improvements in the performance measurement systems used when the unit of analysis is the manufacturing plant. For this a search was done in the highest impact Journals of Production and Operations Management and Management Accounting , with the aim of determining the financial and operational indicators used to evaluate performance when Advanced Production Practices have been implemented, more specifically when the practices implemented are Total Quality Management, JIT/Lean Manufacturing and Total Productive Maintenance. This has enabled us to obtain a classification of the two types of indicators based on how much each is used. For the financial indicators we have also prepared a proposal that can be adapted to manufacturing plants- accounting features. In the near future we will propose a model that links practices implementation with financial and operational indicators and these two last with each other. We aim to will test this model empirically with the data obtained in the High Performance Manufacturing Project.

Keywords: Advanced Production Practices, Financial Indicators, Non-Financial Indicators

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Authors: C. Lodato, S. Lopes

Abstract:

This paper describes a segmentation algorithm based on the cooperation of an optical flow estimation method with edge detection and region growing procedures. The proposed method has been developed as a pre-processing stage to be used in methodologies and tools for video/image indexing and retrieval by content. The addressed problem consists in extracting whole objects from background for producing images of single complete objects from videos or photos. The extracted images are used for calculating the object visual features necessary for both indexing and retrieval processes. The first task of the algorithm exploits the cues from motion analysis for moving area detection. Objects and background are then refined using respectively edge detection and region growing procedures. These tasks are iteratively performed until objects and background are completely resolved. The developed method has been applied to a variety of indoor and outdoor scenes where objects of different type and shape are represented on variously textured background.

Keywords: Motion Detection, Object Extraction, Optical Flow, Segmentation.

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Authors: Randa Ibrahim Elanwar, Mohsen Rashwan, Samia Mashali

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In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.

Keywords: Arabic, Hidden Markov Models, online handwriting, word segmentation

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Authors: Vassilis S. Kodogiannis, John N. Lygouras

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In this research study, an intelligent detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the M2A Swallowable Imaging Capsule - a patented, video color-imaging disposable capsule. Schemes have been developed to extract texture features from the fuzzy texture spectra in the chromatic and achromatic domains for a selected region of interest from each color component histogram of endoscopic images. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and artificial neural networks and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The achieved high detection accuracy of the proposed system has provided thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.

Keywords: Medical imaging, Computer aided diagnosis, Endoscopy, Neuro-fuzzy networks, Fuzzy integral.

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Authors: Anju Shri, Parvinder S. Sandhu, Vikas Gupta, Sanyam Anand

Abstract:

In literature, there are metrics for identifying the quality of reusable components but the framework that makes use of these metrics to precisely predict reusability of software components is still need to be worked out. These reusability metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the software component and hence improve the productivity due to probabilistic increase in the reuse level. As CK metric suit is most widely used metrics for extraction of structural features of an object oriented (OO) software; So, in this study, tuned CK metric suit i.e. WMC, DIT, NOC, CBO and LCOM, is used to obtain the structural analysis of OO-based software components. An algorithm has been proposed in which the inputs can be given to K-Means Clustering system in form of tuned values of the OO software component and decision tree is formed for the 10-fold cross validation of data to evaluate the in terms of linguistic reusability value of the component. The developed reusability model has produced high precision results as desired.

Keywords: CK-Metric, Desicion Tree, Kmeans, Reusability.

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Authors: M. Laamim, A. Benazzouz, A. Rochd, A. Ghennioui, A. El Fadili, M. Benzaazoua

Abstract:

Smart grids have recently sparked a lot of interest in the energy sector as they allow for the modernization and digitization of the existing power infrastructure. Smart grids have several advantages in terms of reducing the environmental impact of generating power from fossil fuels due to their capacity to integrate large amounts of distributed energy resources. On the other hand, smart grid technologies necessitate many field investigations and requirements. This paper focuses on the major difficulties that governments face around the world and compares them to the situation in Morocco. Also presented in this study are the current works and projects being developed to improve the penetration of smart grid technologies into the electrical system. Furthermore, the findings of this study will be useful to promote the smart grid revolution in Morocco, as well as to construct a strong foundation and develop future needs for better penetration of technologies that aid in the integration of smart grid features.

Keywords: Smart grids, microgrids, virtual power plants, digital twin, distributed energy resources, vehicle-to-grid, advanced metering infrastructure.

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Authors: O. Yavuz, L. Ozyilmaz

Abstract:

HIV-1 genome is highly heterogeneous. Due to this variation, features of HIV-I genome is in a wide range. For this reason, the ability to infection of the virus changes depending on different chemokine receptors. From this point of view, R5 HIV viruses use CCR5 coreceptor while X4 viruses use CXCR5 and R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the experiments on HIV-1 genome. In this study, R5X4 type of HIV viruses were classified using Auto Regressive (AR) model through Artificial Neural Networks (ANNs). The statistical data of R5X4, R5 and X4 viruses was analyzed by using signal processing methods and ANNs. Accessible residues of these virus sequences were obtained and modeled by AR model since the dimension of residues is large and different from each other. Finally the pre-processed data was used to evolve various ANN structures for determining R5X4 viruses. Furthermore ROC analysis was applied to ANNs to show their real performances. The results indicate that R5X4 viruses successfully classified with high sensitivity and specificity values training and testing ROC analysis for RBF, which gives the best performance among ANN structures.

Keywords: Auto-Regressive Model, HIV, Neural Networks, ROC Analysis.

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Authors: M. Sadeghi, A.H. Jafari, S.M.P. Firoozabadi

Abstract:

Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.

Keywords: Chaos, Deep Brain Stimulation, Parkinson's Disease, Stimulation Parameters, tremor.

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Authors: D. Moussazadeh, A. Aytug

Abstract:

The architecture of the museum is the most exciting space for an architecture to discover and investigate. Undoubtedly, those museums that have been largely supported by people have come to be cultural memorabilia, moreover holding competitions in museums, producing new publications for theoretical or intellectual debates, and new designs lead the museums to be the most effective and attractive place for work and study. The importance of museums as centers of knowledge, science and art has increased over the last century. Museums have moved from being a place specific to the first-class of the community, to a place used by the whole community widely. By considering these reasons, the value and importance of museums in today's society is imperative. Finding common features for museum architecture in the decades after 1990s has become more difficult than previous decades. The purpose of this article is to examine the effect of museums and their position in society on architectural design of museums from the beginning to the present. In other words, this research aims to investigate the history of museums, their roles, duties, uses, their relationship with users and their position and, consequently, the impact of all these factors on the design of museum architecture. Finally, the main objective of this article is to find the position of museums in the community and their architectural form in the present century.

Keywords: Museum, form, architecture.

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Authors: Seyyed Yasser Hashemi

Abstract:

Skew detection and correction (SDC) has a direct effect in efficiency and exactitude of documents’ segmentation and analysis and thus is considered as a very important step in documents’ analysis field. Skew is a major problem in documents’ analysis for every language. For Arabic/Persian document scripts this problem is more severe because of special features of these languages. In this paper an efficient and fast algorithm for Document Skew Detection (DSD) based on the concept of segmentation and Center of Gravity (COG) is proposed. This algorithm is examined for 150 Arabic/Persian and English documents and SDC process are done successfully for 93 percent of documents with error rate of less than 1°. This algorithm shows better results for English documents compared to Arabic/Persian documents. The proposed method is also represents favorable results for handwritten, printed and also complicated documents such as newspapers and journals even with very low quality and resolution.

Keywords: Arabic/Persian document, Baseline, Centre of gravity, Document segmentation, Skew detection and correction.

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Authors: Z. Rihova, K. Saksl, C. Siemers, D. Ostroushko

Abstract:

Titanium alloys like the modern alloy Ti 6Al 2Sn 4Zr 6Mo (Ti-6246) combine excellent specific mechanical properties and corrosion resistance. On the other hand,due to their material characteristics, machining of these alloys is difficult to perform. The aim of the current study is the analyses of wear mechanisms of coated cemented carbide tools applied in orthogonal cutting experiments of Ti-6246 alloy. Round bars were machined with standard coated tools in dry conditions on a CNC latheusing a wide range of cutting speeds and cutting depths. Tool wear mechanisms were afterwards investigated by means of stereo microscopy, optical microscopy, confocal microscopy and scanning electron microscopy. Wear mechanisms included fracture of the tool tip (total failure) and abrasion. Specific wear features like crater wear, micro cracks and built-up edgeformation appeared depending of the mechanical and thermal conditions generated in the workpiece surface by the cutting action.

Keywords: Alloy 6246, machining, tool wear, optical microscopy, SEM, EDX analysis

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Authors: Magda Bădescu, Daniela Jitaru, C.Grigoraş, L.Bădescu, I. Topala, Manuela Ciocoiu

Abstract:

The purpose of our study was to compare spontaneous re-epithelisation characteristics versus assisted re-epithelisation. In order to assess re-epithelisation of the injured skin, we have imagined and designed a burn wound model on Wistar rat skin. Our aim was to create standardised, easy reproducible and quantifiable skin lesions involving entire epidermis and superficial dermis. We then have applied the above mentioned therapeutic strategies to compare regeneration of epidermis and dermis, local and systemic parameter changes in different conditions. We have enhanced the reepithelisation process under a moist atmosphere of a polyurethane wound dress modified with helium non-thermal plasma, and with the aid of direct cold-plasma treatment respectively. We have followed systemic parameters change: hematologic and biochemical parameters, and local features: oxidative stress markers and histology of skin in the above mentioned conditions. Re-epithelisation is just a part of the skin regeneration process, which recruits cellular components, with the aid of epidermal and dermal interaction via signal molecules.

Keywords: Plasma medicine, re-epithelisation and tissue regeneration

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Authors: Razvan Bocu, Sabin Tabirca

Abstract:

The study of proteomics reached unexpected levels of interest, as a direct consequence of its discovered influence over some complex biological phenomena, such as problematic diseases like cancer. This paper presents a new technique that allows for an accurate analysis of the human interactome network. It is basically a two-step analysis process that involves, at first, the detection of each protein-s absolute importance through the betweenness centrality computation. Then, the second step determines the functionallyrelated communities of proteins. For this purpose, we use a community detection technique that is based on the edge betweenness calculation. The new technique was thoroughly tested on real biological data and the results prove some interesting properties of those proteins that are involved in the carcinogenesis process. Apart from its experimental usefulness, the novel technique is also computationally effective in terms of execution times. Based on the analysis- results, some topological features of cancer mutated proteins are presented and a possible optimization solution for cancer drugs design is suggested.

Keywords: Betweenness centrality, interactome networks, proteinprotein interactions, protein communities, cancer.

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Authors: Mansab Ali, Muhammad Khalid Khan

Abstract:

The advances in wireless communication have opened unlimited horizons but there are some challenges as well. The Nature derived air medium between MS (Mobile Station) and BS (Base Station) is beyond human control and produces channel impairment. The impact of the natural conditions at the air medium is the biggest issue in wireless communication. Natural conditions make reliability more cumbersome; here reliability refers to the efficient recovery of the lost or erroneous data. The SR-ARQ (Selective Repeat-Automatic Repeat Request) protocol is a de facto standard for any wireless technology at the air interface with its standard reliability features. Our focus in this research is on the reliability of the control or feedback signal of the SR-ARQ protocol. The proposed mechanism, RSR-ARQ (Reliable SR-ARQ) is an enhancement of the SR-ARQ protocol that has ensured the reliability of the control signals through channel impairment sensitive mechanism. We have modeled the system under two-state discrete time Markov Channel. The simulation results demonstrate the better recovery of the lost or erroneous data that will increase the overall system performance.

Keywords: ISR-ARQ, MAA, RSR-ARQ, SAA.

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Authors: D. Satish Kumar, S. Karthik

Abstract:

A dual tiered network model is designed to overcome the problem of energy alert and fault tolerance. This model minimizes the delay time and overcome failure of links. Performance analysis of the dual tiered network model is studied in this paper where the CA and LS schemes are compared with DEO optimal. We then evaluate  the Integrated Network Topological Control and Key Management (INTK) Schemes, which was proposed to add security features of the wireless sensor networks. Clustering efficiency, level of protections, the time complexity is some of the parameters of INTK scheme that were analyzed. We then evaluate the Cluster based Energy Competent n-coverage scheme (CEC n-coverage scheme) to ensure area coverage for wireless sensor networks.

Keywords: CEC n-coverage scheme, Clustering efficiency, Dual tired network, Wireless sensor networks.

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Authors: Shinichiro Sasahara, Yusuke Tomotsune, Yuichi Ohi, Shun Suzuki, Akihiro Seki, Junko Sakano, Yoshihiko Yamazaki, Ichiyo Matsuzaki

Abstract:

Via a large scale cross-sectional study among Japanese white color workers, the authors aimed to elucidate: (1) the distributions of Sense of Coherence (SOC), which reflect stress coping abilities, (2) the distributions of Life experience; (3) and the association between SOC and Life experience. Anonymous self-administered questionnaires were sent to 15,891 in 2001 and 21,922 in 2011 employees at educational and research institutions in Tsukuba Research Park City. A total of 5,868 (36.9%) and 9,528 (43.5%) respectively workers completed and returned the questionnaire; 5,715 and 9,515 respectively workers without missing data were analyzed. SOC scale scores differed by gender, age, and other demographic features in both study years. Among the life experiences, workers who have got over parenting or management position were higher SOC scale scores adjusted by gender and age. The life experiences that workers have got over could develop their stronger SOC in their life course.

Keywords: field study, life experience, mental health, SOC (sense of coherence)

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Authors: D. Karthikeyan, G. Balakrishnan

Abstract:

Human faces, as important visual signals, express a significant amount of nonverbal info for usage in human-to-human communication. Age, specifically, is more significant among these properties. Human age estimation using facial image analysis as an automated method which has numerous potential real‐world applications. In this paper, an automated age estimation framework is presented. Support Vector Regression (SVR) strategy is utilized to investigate age prediction. This paper depicts a feature extraction taking into account Gray Level Co-occurrence Matrix (GLCM), which can be utilized for robust face recognition framework. It applies GLCM operation to remove the face's features images and Active Appearance Models (AAMs) to assess the human age based on image. A fused feature technique and SVR with GA optimization are proposed to lessen the error in age estimation.

Keywords: Support vector regression, feature extraction, gray level co-occurrence matrix, active appearance models.

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Authors: Adam Świtoński, Agnieszka Michalczuk, Henryk Josiński, Andrzej Polański, KonradWojciechowski

Abstract:

The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.

Keywords: Biometrics, dynamic time warping, gait identification, motion capture, time series classification, quaternion distance functions, attribute ranking.

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Authors: G. Balakrishnan, G. Sainarayanan, R. Nagarajan, Sazali Yaacob

Abstract:

This paper presents a review on vision aided systems and proposes an approach for visual rehabilitation using stereo vision technology. The proposed system utilizes stereo vision, image processing methodology and a sonification procedure to support blind navigation. The developed system includes a wearable computer, stereo cameras as vision sensor and stereo earphones, all moulded in a helmet. The image of the scene infront of visually handicapped is captured by the vision sensors. The captured images are processed to enhance the important features in the scene in front, for navigation assistance. The image processing is designed as model of human vision by identifying the obstacles and their depth information. The processed image is mapped on to musical stereo sound for the blind-s understanding of the scene infront. The developed method has been tested in the indoor and outdoor environments and the proposed image processing methodology is found to be effective for object identification.

Keywords: Blind navigation, stereo vision, image processing, object preference, music tones.

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Authors: E. N. Sathishkumar, K. Thangavel, T. Chandrasekhar

Abstract:

Feature selection is a process to select features which are more informative. It is one of the important steps in knowledge discovery. The problem is that all genes are not important in gene expression data. Some of the genes may be redundant, and others may be irrelevant and noisy. Here a novel approach is proposed Hybrid K-Mean-Quick Reduct (KMQR) algorithm for gene selection from gene expression data. In this study, the entire dataset is divided into clusters by applying K-Means algorithm. Each cluster contains similar genes. The high class discriminated genes has been selected based on their degree of dependence by applying Quick Reduct algorithm to all the clusters. Average Correlation Value (ACV) is calculated for the high class discriminated genes. The clusters which have the ACV value as 1 is determined as significant clusters, whose classification accuracy will be equal or high when comparing to the accuracy of the entire dataset. The proposed algorithm is evaluated using WEKA classifiers and compared. The proposed work shows that the high classification accuracy.

Keywords: Clustering, Gene Selection, K-Mean-Quick Reduct, Rough Sets.

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Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

Different order modulations combined with different coding schemes, allow sending more bits per symbol, thus achieving higher throughputs and better spectral efficiencies. However, it must also be noted that when using a modulation technique such as 64- QAM with less overhead bits, better signal-to-noise ratios (SNRs) are needed to overcome any Inter symbol Interference (ISI) and maintain a certain bit error ratio (BER). The use of adaptive modulation allows wireless technologies to yielding higher throughputs while also covering long distances. The aim of this paper is to implement an Adaptive Modulation and Coding (AMC) features of the WiMAX PHY in MATLAB and to analyze the performance of the system in different channel conditions (AWGN, Rayleigh and Rician fading channel) with channel estimation and blind equalization. Simulation results have demonstrated that the increment in modulation order causes to increment in throughput and BER values. These results derived a trade-off among modulation order, FFT length, throughput, BER value and spectral efficiency. The BER changes gradually for AWGN channel and arbitrarily for Rayleigh and Rician fade channels.

Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX.

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Authors: Petr Teply

Abstract:

The New Basel Capital Accord (Basel II) influences how financial institutions around the world, and especially European Union institutions, determine the amount of capital to reserve. However, as the recent global crisis has shown, the revision of Basel II is needed to reflect current trends, such as increased volatility and correlation, in the world financial markets. The overall objective of Basel II is to increase the safety and soundness of the international financial system. Basel II builds on three main pillars: Pillar I deals with the minimum capital requirements for credit, market and operational risk, Pillar II focuses on the supervisory review process and finally Pillar III promotes market discipline through enhanced disclosure requirements for banks. The aim of this paper is to provide the historical background, key features and impact of Basel II on financial markets. Moreover, we discuss new proposals for international bank regulation (sometimes referred to as Basel III) which include requirements for higher quality, constituency and transparency of banks' capital and risk management, regulation of OTC markets and introduction of new liquidity standards for internationally active banks.

Keywords: Basel II, Basel III, risk management, bank regulation

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Authors: S. Kamyabi, M. Salari, H. Shahabi

Abstract:

One of the processes of slope that occurs every year in Iran and some parts of world and cause a lot of criminal and financial harms is called landslide. They are plenty of method to stability landslide in soil and rock slides. The use of the best method with the least cost and in the shortest time is important for researchers. In this research, determining the best method of stability is investigated by using of Decision Support systems. DSS is made for this purpose and was used (for Hasan Salaran area in Kurdistan). Field study data from topography, slope, geology, geometry of landslide and the related features was used. The related data entered decision making managements programs (DSS) (ALES).Analysis of mass stability indicated the instability potential at present. Research results show that surface and sub surface drainage the best method of stabilizing. Analysis of stability shows that acceptable increase in security coefficient is a consequence of drainage.

Keywords: Landslide, Decision Support systems, stability, Hasan Salaran landslide, Kurdistan province, Iran.

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