Search results for: Data mining techniques

Authors: A. Saghaei, R. Ghasemi

Abstract:

Through 1980s, management accounting researchers described the increasing irrelevance of traditional control and performance measurement systems. The Balanced Scorecard (BSC) is a critical business tool for a lot of organizations. It is a performance measurement system which translates mission and strategy into objectives. Strategy map approach is a development variant of BSC in which some necessary causal relations must be established. To recognize these relations, experts usually use experience. It is also possible to utilize regression for the same purpose. Structural Equation Modeling (SEM), which is one of the most powerful methods of multivariate data analysis, obtains more appropriate results than traditional methods such as regression. In the present paper, we propose SEM for the first time to identify the relations between objectives in the strategy map, and a test to measure the importance of relations. In SEM, factor analysis and test of hypotheses are done in the same analysis. SEM is known to be better than other techniques at supporting analysis and reporting. Our approach provides a framework which permits the experts to design the strategy map by applying a comprehensive and scientific method together with their experience. Therefore this scheme is a more reliable method in comparison with the previously established methods.

Keywords: BSC, SEM, Strategy map.

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Authors: Susmita Das, Kala Praveen Bagadi

Abstract:

SDMA (Space-Division Multiple Access) is a MIMO (Multiple-Input and Multiple-Output) based wireless communication network architecture which has the potential to significantly increase the spectral efficiency and the system performance. The maximum likelihood (ML) detection provides the optimal performance, but its complexity increases exponentially with the constellation size of modulation and number of users. The QR decomposition (QRD) MUD can be a substitute to ML detection due its low complexity and near optimal performance. The minimum mean-squared-error (MMSE) multiuser detection (MUD) minimises the mean square error (MSE), which may not give guarantee that the BER of the system is also minimum. But the minimum bit error rate (MBER) MUD performs better than the classic MMSE MUD in term of minimum probability of error by directly minimising the BER cost function. Also the MBER MUD is able to support more users than the number of receiving antennas, whereas the rest of MUDs fail in this scenario. In this paper the performance of various MUD techniques is verified for the correlated MIMO channel models based on IEEE 802.16n standard.

Keywords: Multiple input multiple output, multiuser detection, orthogonal frequency division multiplexing, space division multiple access, Bit error rate

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Authors: Zhang Yan, Yu Bin

Abstract:

Principle component analysis is often combined with the state-of-art classification algorithms to recognize human faces. However, principle component analysis can only capture these features contributing to the global characteristics of data because it is a global feature selection algorithm. It misses those features contributing to the local characteristics of data because each principal component only contains some levels of global characteristics of data. In this study, we present a novel face recognition approach using non-negative principal component analysis which is added with the constraint of non-negative to improve data locality and contribute to elucidating latent data structures. Experiments are performed on the Cambridge ORL face database. We demonstrate the strong performances of the algorithm in recognizing human faces in comparison with PCA and NREMF approaches.

Keywords: classification, face recognition, non-negativeprinciple component analysis (NPCA)

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Authors: Bala Dhandayuthapani Veerasamy

Abstract:

Parallel programming models exist as an abstraction of hardware and memory architectures. There are several parallel programming models in commonly use; they are shared memory model, thread model, message passing model, data parallel model, hybrid model, Flynn-s models, embarrassingly parallel computations model, pipelined computations model. These models are not specific to a particular type of machine or memory architecture. This paper expresses the model program for concurrent approach to data parallel model through java programming.

Keywords: Concurrent, Data Parallel, JDK, Parallel, Thread

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Authors: Nuanpan Nangsue

Abstract:

Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.

Keywords: Auxiliary variable, missing data, ratio and regression type estimators.

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Authors: Abhishek, Seema Devi, Jyoti Ohri

Abstract:

A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV.

Keywords: ANFIS, AODV, fuzzy, MANET, reactive routing protocol, routing protocol, Truetime.

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Authors: A. K. Aswathy, Asha Manoharan, Arya Manoharan

Abstract:

The purpose of this study are to define the nature of oral sensory issues in children with autism spectrum disorder (ASD), identify important components of the assessment and treatment of this issues specific to this population, and delineate specific therapeutic techniques designed to improve assessment and treatment within therapeutic settings. Literature review and case example is used to define the predominant nature of the oral sensory issues that are experienced by some children on the autism spectrum. Characteristics of this complex disorder that can have an impact on feeding skill and behavior are also identified. These factors are then integrated to create assessment and intervention techniques that can be used in conjunction with traditional feeding approaches to facilitate improvements in eating as well as reducing oral apraxic component in this unique population. The complex nature of ASD and its many influences on feeding skills and behavior create the need for modification to both assessment and treatment approaches. Additional research is needed to create therapeutic protocols that can be used by speech-language pathologists to effectively assess and treat feeding and oro motor apraxic difficulties that are commonly encountered in children with ASD.

Keywords: Autism, feeding, intervention, oral sensory issues, oral apraxia.

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Authors: Huaizhong Li, C.Peng Lam

Abstract:

State-based testing is frequently used in software testing. Test data generation is one of the key issues in software testing. A properly generated test suite may not only locate the errors in a software system, but also help in reducing the high cost associated with software testing. It is often desired that test data in the form of test sequences within a test suite can be automatically generated to achieve required test coverage. This paper proposes an Ant Colony Optimization approach to test data generation for the state-based software testing.

Keywords: Software testing, ant colony optimization, UML.

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Authors: Bastian Haarmann, Lukas Sikorski

Abstract:

In this paper, we introduce an NLG application for the automatic creation of ready-to-publish texts from big data. The resulting fully automatic generated news stories have a high resemblance to the style in which the human writer would draw up such a story. Topics include soccer games, stock exchange market reports, and weather forecasts. Each generated text is unique. Readyto-publish stories written by a computer application can help humans to quickly grasp the outcomes of big data analyses, save timeconsuming pre-formulations for journalists and cater to rather small audiences by offering stories that would otherwise not exist. 

Keywords: Big data, natural language generation, publishing, robotic journalism.

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Authors: I. Severin, M. Caramihai, R. El Abdi, M. Poulain, A. Avadanii

Abstract:

In order to assess optical fiber reliability in different environmental and stress conditions series of testing are performed simulating overlapping of chemical and mechanical controlled varying factors. Each series of testing may be compared using statistical processing: i.e. Weibull plots. Due to the numerous data to treat, a software application has appeared useful to interpret selected series of experiments in function of envisaged factors. The current paper presents a software application used in the storage, modelling and interpretation of experimental data gathered from optical fibre testing. The present paper strictly deals with the software part of the project (regarding the modelling, storage and processing of user supplied data).

Keywords: Optical fibres, computer aided analysis, data models, data processing, graphical user interfaces.

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Authors: Vasily G. Moshnyaga

Abstract:

This paper presents an optimized MPEG2 video codec implementation, which drastically reduces the number of computations and memory accesses required for video compression. Unlike traditional scheme, we reuse data stored in frame memory to omit unnecessary coding operations and memory read/writes for unchanged macroblocks. Due to dynamic memory sharing among reference frames, data-driven macroblock characterization and selective macroblock processing, we perform less than 15% of the total operations required by a conventional coder while maintaining high picture quality.

Keywords: Data reuse, adaptive processing, video coding, MPEG

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Authors: Sarra Senhadji, Amar Kateb, Hafida Belbachir

Abstract:

Data replication in data grid systems is one of the important solutions that improve availability, scalability, and fault tolerance. However, this technique can also bring some involved issues such as maintaining replica consistency. Moreover, as grid environment are very dynamic some nodes can be more uploaded than the others to become eventually a bottleneck. The main idea of our work is to propose a complementary solution between replica consistency maintenance and dynamic load balancing strategy to improve access performances under a simulated grid environment.

Keywords: Consistency, replication, data grid, load balancing.

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Authors: Myungraee Cha, Jun Seok Kim, Seung Hwan Park, Jun-Geol Baek

Abstract:

In manufacturing industries, development of measurement leads to increase the number of monitoring variables and eventually the importance of multivariate control comes to the fore. Statistical process control (SPC) is one of the most widely used as multivariate control chart. Nevertheless, SPC is restricted to apply in processes because its assumption of data as following specific distribution. Unfortunately, process data are composed by the mixture of several processes and it is hard to estimate as one certain distribution. To alternative conventional SPC, therefore, nonparametric control chart come into the picture because of the strength of nonparametric control chart, the absence of parameter estimation. SVDD based control chart is one of the nonparametric control charts having the advantage of flexible control boundary. However,basic concept of SVDD has been an oversight to the important of data characteristic, density distribution. Therefore, we proposed DW-SVDD (Density Weighted SVDD) to cover up the weakness of conventional SVDD. DW-SVDD makes a new attempt to consider dense of data as introducing the notion of density Weight. We extend as control chart using new proposed SVDD and a simulation study of various distributional data is conducted to demonstrate the improvement of performance.

Keywords: Density estimation, Multivariate control chart, Oneclass classification, Support vector data description (SVDD)

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Authors: Kyoung-Mi Lee, Youn-Mi Lee

Abstract:

This paper proposes a way to track persons by making use of multiple non-overlapping cameras. Tracking persons on multiple non-overlapping cameras enables data communication among cameras through the network connection between a camera and a computer, while at the same time transferring human feature data captured by a camera to another camera that is connected via the network. To track persons with a camera and send the tracking data to another camera, the proposed system uses a hierarchical human model that comprises a head, a torso, and legs. The feature data of the person being modeled are transferred to the server, after which the server sends the feature data of the human model to the cameras connected over the network. This enables a camera that captures a person's movement entering its vision to keep tracking the recognized person with the use of the feature data transferred from the server.

Keywords: Person tracking, human model, networked cameras, vision-based surveillance.

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Authors: V. Hernandez-Perez, M. Abdulkadir, B. J. Azzopardi

Abstract:

In this work, new experimental data for slugging frequency in inclined gas-liquid flow are reported, and a new correlation is proposed. Scale experiments were carried out using a mixture of air and water in a 6 m long pipe. Two different pipe diameters were used, namely, 38 and 67 mm. The data were taken with capacitance type sensors at a data acquisition frequency of 200 Hz over an interval of 60 seconds. For the range of flow conditions studied, the liquid superficial velocity is observed to influence the frequency strongly. A comparison of the present data with correlations available in the literature reveals a lack of agreement. A new correlation for slug frequency has been proposed for the inclined flow, which represents the main contribution of this work.

Keywords: slug frequency, inclined flow

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Authors: Nazaket Gazieva

Abstract:

Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: Biometric voice prints, fundamental frequency, phonogram, speech signal, temporal characteristics.

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Authors: Shigeaki Sakurai, Ryohei Orihara

Abstract:

This paper proposes an improvement method of classification efficiency in a classification model. The model is used in a risk search system and extracts specific labels from articles posted at bulletin board sites. The system can analyze the important discussions composed of the articles. The improvement method introduces ensemble learning methods that use multiple classification models. Also, it introduces expressions related to the specific labels into generation of word vectors. The paper applies the improvement method to articles collected from three bulletin board sites selected by users and verifies the effectiveness of the improvement method.

Keywords: Text mining, Risk search system, Corporate reputation, Bulletin board site, Ensemble learning

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Authors: Mansoor Ahsan, Khalid Rafique, Farrukh Mazhar

Abstract:

Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.

Keywords: Unmanned aerial vehicle (UAV), autopilot, autonomous controls, PID controler gains tuning, optimization.

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Authors: Raja Asad Zaheer, Aisha Tanveer, Hafza Mehreen Fatima

Abstract:

Global Software Development (GSD) is becoming a common norm in software industry, despite of the fact that global distribution of the teams presents special issues for effective communication and coordination of the teams. Now trends are changing and project management for distributed teams is no longer in a limbo. GSD can be effectively established using agile and project managers can use different agile techniques/tools for solving the problems associated with distributed teams. Agile methodologies like scrum and XP have been successfully used with distributed teams. We have employed exploratory research method to analyze different recent studies related to challenges of GSD and their proposed solutions. In our study, we had deep insight in six commonly faced challenges: communication and coordination, temporal differences, cultural differences, knowledge sharing/group awareness, speed and communication tools. We have established that each of these challenges cannot be neglected for distributed teams of any kind. They are interlinked and as an aggregated whole can cause the failure of projects. In this paper we have focused on creating a scalable framework for detecting and overcoming these commonly faced challenges. In the proposed solution, our objective is to suggest agile techniques/tools relevant to a particular problem faced by the organizations related to the management of distributed teams. We focused mainly on scrum and XP techniques/tools because they are widely accepted and used in the industry. Our solution identifies the problem and suggests an appropriate technique/tool to help solve the problem based on globally shared knowledgebase. We can establish a cause and effect relationship using a fishbone diagram based on the inputs provided for issues commonly faced by organizations. Based on the identified cause, suitable tool is suggested, our framework suggests a suitable tool. Hence, a scalable, extensible, self-learning, intelligent framework proposed will help implement and assess GSD to achieve maximum out of it. Globally shared knowledgebase will help new organizations to easily adapt best practices set forth by the practicing organizations.

Keywords: Agile project management, agile framework, distributed teams, global software development.

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Authors: Tsunwai Gary Yip

Abstract:

Phase locked loops for data links operating at 10 Gb/s or faster are low phase noise devices designed to operate with a low jitter reference clock. Characterization of their jitter transfer function is difficult because the intrinsic noise of the device is comparable to the random noise level in the reference clock signal. A linear model is proposed to account for the intrinsic noise of a PLL. The intrinsic noise data of a PLL for 10 Gb/s links is presented. The jitter transfer function of a PLL in a test chip for 12.8 Gb/s data links was determined in experiments using the 400 MHz reference clock as the source of simultaneous excitations over a wide range of frequency. The result shows that the PLL jitter transfer function can be approximated by a second order linear model.

Keywords: Intrinsic phase noise, jitter in data link, PLL jitter transfer function, high speed clocking in electronic circuit

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Authors: M. Seifi, S. Fallah, M. Firoozrai

Abstract:

Matrix metalloproteinase-3 (MMP3) is key member of the MMP family, and is known to be present in coronary atherosclerotic. Several studies have demonstrated that MMP-3 5A/6A polymorphism modify each transcriptional activity in allele specific manner. We hypothesized that this polymorphism may play a role as risk factor for development of coronary stenosis. The aim of our study was to estimate MMP-3 (5A/6A) gene polymorphism on interindividual variability in risk for coronary stenosis in an Iranian population.DNA was extracted from white blood cells and genotypes were obtained from coronary stenosis cases (n=95) and controls (n=100) by PCR (polymerase chain reaction) and restriction fragment length polymorphism techniques. Significant differences between cases and controls were observed for MMP3 genotype frequencies (X2=199.305, p< 0.001); the 6A allele was less frequently seen in the control group, compared to the disease group (85.79 vs. 78%, 6A/6A+5A/6A vs. 5A/5A, P≤0.001). These data imply the involvement of -1612 5A/6A polymorphism in coronary stenosis, and suggest that probably the 6A/6A MMP-3 genotype is a genetic susceptibility factor for coronary stenosis.

Keywords: Coronary artery stenosis, matrixmetalloproteinase-3, polymorphism, polymerase chain reaction.

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Authors: Sudhir Kumar Tiwari

Abstract:

The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: Multi-disciplinary optimization, aircraft load, finite element analysis, Stick Model.

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Authors: Fernando Alonso, Rafael Fernandez, Sonia Frutos, Javier Soriano

Abstract:

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping can be used for automatic reasoning about the management information models, as a design aid, by means of new-generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Keywords: CIM, Knowledge-based Information Models, Ontology Languages, OWL, Description Logics, Integrated Network Management, Intelligent Agents, Automatic Reasoning Techniques.

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Authors: Gheida J. Shahrour, Martin J. Russell

Abstract:

The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that intersubject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: Person Recognition, Topic Recognition, Culture Recognition, 3D Body Movement Signals, Variability Compensation.

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Authors: Chen May Oh, Nadzrah Abu Bakar

Abstract:

This case study investigates the areas of self-reflection through the written content of four university students’ blogs. The study was undertaken to explore the categories of self-reflection in relation to the use of blogs. Data collection methods included downloading students’ blog entries and recording individual interviews to further support the data. Data was analyzed using computer assisted qualitative data analysis software, Nvivo, to categories and code the data. The categories of self-reflection revealed in the findings showed that university students used blogs to reflect on (1) life in varsity, (2) emotions and feelings, (3) various relationships, (4) personal growth, (5) spirituality, (6) health conditions, (7) busyness with daily chores, (8) gifts for people and themselves and (9) personal interests. Overall, all four of the students had positive experiences and felt satisfied using blogs for self-reflection.

Keywords: Blogging, personal growth, self-reflection, university students.

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Authors: S. Krustev, V. Angelova, P. Zaprjanova

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Selenium (Se) is an essential micro-nutrient for human and animals but it is highly toxic. Its organic compounds play an important role in biochemistry and nutrition of the cells. Concentration levels of this element in the different regions of the world vary considerably. This study aimed to compare the availability and levels of the Se in some rural areas of the Balkan Peninsula and relationship with the concentrations of other trace elements. For this purpose soil samples and wheat grains from different regions of Bulgaria, Serbia, Nord Macedonia, Romania, and Greece situated far from large industrial centers have been analyzed. The main methods for their determination were the atomic spectral techniques – atomic absorption and plasma atomic emission. As a result of this study, data on microelements levels from the main grain-producing regions of the Balkan Peninsula were determined and systematized. The presented results confirm the low levels of Se in this region: 0.222– 0.962 mg.kg^-1 in soils and 0.001 - 0.005 mg.kg^-1 in wheat grains and require measures to offset the effect of this deficiency.

Keywords: Agricultural soils, Balkan Peninsula, rural areas, selenium.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop

Abstract:

Frequent pattern discovery over data stream is a hard problem because a continuously generated nature of stream does not allow a revisit on each data element. Furthermore, pattern discovery process must be fast to produce timely results. Based on these requirements, we propose an approximate approach to tackle the problem of discovering frequent patterns over continuous stream. Our approximation algorithm is intended to be applied to process a stream prior to the pattern discovery process. The results of approximate frequent pattern discovery have been reported in the paper.

Keywords: Frequent pattern discovery, Approximate algorithm, Data stream analysis.

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Authors: Zhou Yu, Jiang Feng

Abstract:

An adaptive Chinese hand-talking system is presented in this paper. By analyzing the 3 data collecting strategies for new users, the adaptation framework including supervised and unsupervised adaptation methods is proposed. For supervised adaptation, affinity propagation (AP) is used to extract exemplar subsets, and enhanced maximum a posteriori / vector field smoothing (eMAP/VFS) is proposed to pool the adaptation data among different models. For unsupervised adaptation, polynomial segment models (PSMs) are used to help hidden Markov models (HMMs) to accurately label the unlabeled data, then the "labeled" data together with signerindependent models are inputted to MAP algorithm to generate signer-adapted models. Experimental results show that the proposed framework can execute both supervised adaptation with small amount of labeled data and unsupervised adaptation with large amount of unlabeled data to tailor the original models, and both achieve improvements on the performance of recognition rate.

Keywords: sign language recognition, signer adaptation, eMAP/VFS, polynomial segment model.

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Authors: P. Kumsawat, N. Pimpru, K. Attakitmongcol, A.Srikaew

Abstract:

In this paper, we proposed an efficient data compression strategy exploiting the multi-resolution characteristic of the wavelet transform. We have developed a sensor node called “Smart Sensor Node; SSN". The main goals of the SSN design are lightweight, minimal power consumption, modular design and robust circuitry. The SSN is made up of four basic components which are a sensing unit, a processing unit, a transceiver unit and a power unit. FiOStd evaluation board is chosen as the main controller of the SSN for its low costs and high performance. The software coding of the implementation was done using Simulink model and MATLAB programming language. The experimental results show that the proposed data compression technique yields recover signal with good quality. This technique can be applied to compress the collected data to reduce the data communication as well as the energy consumption of the sensor and so the lifetime of sensor node can be extended.

Keywords: Wireless sensor network, wavelet transform, data compression, ZigBee, skipped high-pass sub-band.

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Authors: Waldemiro Francisco Sorte Junior

Abstract:

The Japanese integrative approach to social systems can be observed in supply chain management as well as in the relationship between public and private sectors. Both the Lean Production System and the Developmental State Model are characterized by efforts towards the achievement of mutual goals, resulting in initiatives for capacity building which emphasize the system level. In Brazil, although organizations undertake efforts to build capabilities at the individual and organizational levels, the system level is being neglected. Fieldwork data confirmed the findings of other studies in terms of the lack of integration in supply chain management in the Brazilian automobile industry. Moreover, due to the absence of an active role of the Brazilian state in its relationship with the private sector, automakers are not fully exploiting the opportunities in the domestic and regional markets. For promoting a higher level of economic growth as well as to increase the degree of spill-over of technologies and techniques, a more integrative approach is needed.

Keywords: Integration, Lean Production System, DevelopmentalState Model, Brazilian automobile industry.

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