Search results for: Correlated Binary data

Authors: M. Hamdi, R. Rhouma, S. Belghith

Abstract:

Generating random numbers are mainly used to create secret keys or random sequences. It can be carried out by various techniques. In this paper we present a very simple and efficient pseudo random number generator (PRNG) based on chaotic maps and S-Box tables. This technique adopted two main operations one to generate chaotic values using two logistic maps and the second to transform them into binary words using random S-Box tables. The simulation analysis indicates that our PRNG possessing excellent statistical and cryptographic properties.

Keywords: Chaotic map, Cryptography, Random Numbers, Statistical tests, S-box.

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Authors: R. Poonkuzhali, M. Y. Sanavullah, A. Sabari, T. Dhivyaa

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Opportunistic Routing (OR) increases the transmission reliability and network throughput. Traditional routing protocols preselects one or more predetermined nodes before transmission starts and uses a predetermined neighbor to forward a packet in each hop. The opportunistic routing overcomes the drawback of unreliable wireless transmission by broadcasting one transmission can be overheard by manifold neighbors. The first cooperation-optimal protocol for Multirate OR (COMO) used to achieve social efficiency and prevent the selfish behavior of the nodes. The novel link-correlation-aware OR improves the performance by exploiting the miscellaneous low correlated forward links. Context aware Adaptive OR (CAOR) uses active suppression mechanism to reduce packet duplication. The Context-aware OR (COR) can provide efficient routing in mobile networks. By using Cooperative Opportunistic Routing in Mobile Ad hoc Networks (CORMAN), the problem of opportunistic data transfer can be tackled. While comparing to all the protocols, COMO is the best as it achieves social efficiency and prevents the selfish behavior of the nodes.

Keywords: CAOR, COMO, COR, CORMAN, MANET, Opportunistic Routing, Reliability, Throughput.

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Authors: Tahsien Mohamed Okasha, Warda Youssef Mohamed Morsy, Hanan Elsayed Zaghla

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We hypothesized that post cardiac arrest patients with Glasgow Coma Scale (GCS) score of less than 8 and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. 17 subjects were enrolled in this study all over one year. The study was carried out using Quasi-experimental research design. Four tools were used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). The mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% subjects were initially arrested in form of ventricular tachycardia (VT), 23.5% initially arrested in form of ventricular fibrillation (VF), and 29.4% in form of A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also, initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. Therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than 8. Replication of the study on larger probability sample, with randomized control trial design is recommended with further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia is recommended.

Keywords: Therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest, initial arrest rhythm.

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Authors: K. A. Mistry, I. B. Patel, A. H. Prajapati

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In the present work, the alloy of Bismuth-lead is prepared on the basis of percentage of molecular weight 9:1, 5:5 and 1:9 ratios and grown by Zone- Refining Technique under a vacuum atmosphere. The EDAX of these samples are done and the results are reported. Micro hardness test has been used as an alternative test for measuring material’s tensile properties. The effect of temperature and load on the hardness of the grown alloy has been studied. Further the comparative studies of work hardening coefficients are reported.

Keywords: EDAX, hardening coefficient, Micro hardness, Bi-Pb alloy.

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Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz

Abstract:

The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

Keywords: Data clustering, medical data, principal components analysis.

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Authors: Handan Ertaş

Abstract:

The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process.It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: Konya, Organizational Justice, Organizational.

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Authors: Mona Soliman Habib

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This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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Authors: Youkyung Park, SeungYup Kang, SungHo Kim, SimKyun Yook

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IMCS is Integrated Monitoring and Control System for thermal power plant. This system consists of mainly two parts; controllers and OIS (Operator Interface System). These two parts are connected by Ethernet-based communication. The controller side of communication is managed by CNet module and OIS side is managed by data server of OIS. CNet module sends the data of controller to data server and receives commend data from data server. To minimizes or balance the load of data server, this module buffers data created by controller at every cycle and send buffered data to data server on request of data server. For multiple data server, this module manages the connection line with each data server and response for each request from multiple data server. CNet module is included in each controller of redundant system. When controller fail-over happens on redundant system, this module can provide data of controller to data sever without loss. This paper presents three main features – separation of get task, usage of ring buffer and monitoring communication status –of CNet module to carry out these functions.

Keywords: Ethernet communication, DCS, power plant, ring buffer, data integrity

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity is associated with cardiovascular disease risk factors and metabolic syndrome (MetS). In this study, associations between adipokines and adipokine as well as obesity indices were evaluated. Plasma adipokine levels may exhibit variations according to body adipose tissue mass. Besides, upon consideration of obesity as an inflammatory disease, adipokines may play some roles in this process. The ratios of proinflammatory adipokines to adiponectin may act as highly sensitive indicators of body adipokine status. The aim of the study is to present some adipokine indices, which are thought to be helpful for the evaluation of childhood obesity and also to determine the best discriminators in the diagnosis of MetS. 80 prepubertal children (aged between 6-9.5 years) included in the study were divided into three groups; 30 children with normal weight (NW), 25 morbid obese (MO) children and 25 MO children with MetS. Physical examinations were performed. Written informed consent forms were obtained from the parents. The study protocol was approved by Ethics Committee of Namik Kemal University Medical Faculty. Anthropometric measurements, such as weight, height, waist circumference (C), hip C, head C, neck C were recorded. Values for body mass index (BMI), diagnostic obesity notation model assessment Index-II (D2 index) as well as waist-to-hip, head-to-neck ratios were calculated. Adiponectin, resistin, leptin, chemerin, vaspin, progranulin assays were performed by ELISA. Adipokine-to-adiponectin ratios were obtained. SPSS Version 20 was used for the evaluation of data. p values ≤ 0.05 were accepted as statistically significant. Values of BMI and D2 index, waist-to-hip, head-to-neck ratios did not differ between MO and MetS groups (p ≥ 0.05). Except progranulin (p ≤ 0.01), similar patterns were observed for plasma levels of each adipokine. There was not any difference in vaspin as well as resistin levels between NW and MO groups. Significantly increased leptin-to-adiponectin, chemerin-to-adiponectin and vaspin-to-adiponectin values were noted in MO in comparison with those of NW. The most valuable adipokine index was progranulin-to-adiponectin (p ≤ 0.01). This index was strongly correlated with vaspin-to-adiponectin ratio in all groups (p ≤ 0.05). There was no correlation between vaspin-to-adiponectin and chemerin-to--adiponectin in NW group. However, a correlation existed in MO group (r = 0.486; p ≤ 0.05). Much stronger correlation (r = 0.609; p ≤ 0.01) was observed in MetS group between these two adipokine indices. No correlations were detected between vaspin and progranulin as well as vaspin and chemerin levels. Correlation analyses showed a unique profile confined to MetS children. Adiponectin was found to be correlated with waist-to-hip (r = -0.435; p ≤ 0.05) as well as head-to-neck (r = 0.541; p ≤ 0.05) ratios only in MetS children. In this study, it has been investigated if adipokine indices have priority over adipokine levels. In conclusion, vaspin-to-adiponectin, progranulin-to-adiponectin, chemerin-to-adiponectin along with waist-to-hip and head-to-neck ratios were the optimal combinations. Adiponectin, waist-to-hip, head-to-neck, vaspin-to-adiponectin, chemerin-to-adiponectin ratios had appropriate discriminatory capability for MetS children.

Keywords: Adipokine indices, metabolic syndrome, obesity indices, pediatric obesity.

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Authors: M. Victor Jose, V. Seenivasagam

Abstract:

This paper describes a logical method to enhance security on the grid computing to restrict the misuse of the grid resources. This method is an economic and efficient one to avoid the usage of the special devices. The security issues, techniques and solutions needed to provide a secure grid computing environment are described. A well defined process for security management among the resource accesses and key holding algorithm is also proposed. In this method, the identity management, access control and authorization and authentication are effectively handled.

Keywords: Grid security, Irregular binary series, Key holding mechanism, Resource identity, Secure resource access.

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Authors: Youngpo Lee, Seokho Yoon

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In this paper, we propose a side-peak cancellation scheme for code acquisition of composite binary offset carrier (CBOC) signals. We first model the family of CBOC signals in a generic form, and then, propose a side-peak cancellation scheme by combining correlation functions between the divided sub-carrier and received signals. From numerical results, it is shown that the proposed scheme removes the side-peak completely, and moreover, the resulting correlation function demonstrates the better power ratio performance than the CBOC autocorrelation.

Keywords: CBOC, side-peak, ambiguity problem, synchronization

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Authors: Pegah Farokhzad

Abstract:

Family has a crucial role in maintaining the physical, social and mental health of the children. Most of the mental and anxiety problems of children reflect the complex interpersonal situations among family members, especially parents. In other words, anxiety problems of the children are correlated with deficit relationships of family members and improper childrearing styles. The parental child rearing styles leads to positive and negative consequences which affect the children’s mental health. Therefore, the present research was aimed to compare the parental childrearing styles and anxiety of children with stuttering and normal population. It was also aimed to study the relationship between parental child rearing styles and anxiety of children. The research sample included 54 boys with stuttering and 54 normal boys who were selected from the children (boys) of Tehran, Iran in the age range of 5 to 8 years in 2013. In order to collect data, Baum-rind Childrearing Styles Inventory and Spence Parental Anxiety Inventory were used. Appropriate descriptive statistical methods and multivariate variance analysis and t test for independent groups were used to test the study hypotheses. Statistical data analyses demonstrated that there was a significant difference between stuttering boys and normal boys in anxiety (t = 7.601, p< 0.01); but there was no significant difference between stuttering boys and normal boys in parental childrearing styles (F = 0.129). There was also not found significant relationship between parental childrearing styles and children anxiety (F = 0.135, p< 0.05). It can be concluded that the influential factors of children’s society are parents, school, teachers, peers and media. So, parental childrearing styles are not the only influential factors on anxiety of children, and other factors including genetic, environment and child experiences are effective in anxiety as well. Details are discussed.

Keywords: Anxiety, Childrearing Styles, Stuttering.

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Authors: A. Bouzabata, A. Boukhari

Abstract:

Curcuma longa L. (Zingiberaceae), commonly known as turmeric, has a long history of traditional uses for culinary purposes as a spice and a food colorant. The present study aimed to document the ethnobotanical knowledge about Curcuma longa, and to assess the variation in the herbalists’ experience in Northeastern Algeria. Data were collected using semi-structured questionnaires and direct interviews with 30 herbalists. Ethnobotanical indices, including the fidelity level (FL%), the relative frequency citation (RFC), and use value (UV) were determined by quantitative methods. Diversity in the level of knowledge was analyzed using univariate, non-parametric, and multivariate statistical methods. Three main categories of uses were recorded for C. longa: for food, for medicine, and for cosmetic purposes. As a medicine, turmeric was used for the treatment of gastrointestinal, dermatological, and hepatic diseases. Medicinal and food uses were correlated with both forms of preparation (rhizome and powder). The age group did not influence the use. Multivariate analyses showed a significant variation in traditional knowledge, associated with the use value, origin, quality, and efficacy of the drug. The findings suggested that the geographical origin of C. longa affected the use in Algeria.

Keywords: Curcuma longa, curcuma indices, ethnobotanical knowledge, variation.

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: Big data, big data Analytics, Hadoop framework, cloud computing.

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

Abstract:

Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption.

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Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

Abstract:

Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: Data integration, data warehousing, federated architecture, online analytical processing.

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Authors: Martin Lnenicka

Abstract:

Governments collect and produce large amounts of data. Increasingly, governments worldwide have started to implement open data initiatives and also launch open data portals to enable the release of these data in open and reusable formats. Therefore, a large number of open data repositories, catalogues and portals have been emerging in the world. The greater availability of interoperable and linkable open government data catalyzes secondary use of such data, so they can be used for building useful applications which leverage their value, allow insight, provide access to government services, and support transparency. The efficient development of successful open data portals makes it necessary to evaluate them systematic, in order to understand them better and assess the various types of value they generate, and identify the required improvements for increasing this value. Thus, the attention of this paper is directed particularly to the field of open data portals. The main aim of this paper is to compare the selected open data portals on the national level using content analysis and propose a new evaluation framework, which further improves the quality of these portals. It also establishes a set of considerations for involving businesses and citizens to create eservices and applications that leverage on the datasets available from these portals.

Keywords: Big data, content analysis, criteria comparison, data quality, open data, open data portals, public sector.

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Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan

Abstract:

The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.

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Authors: M. Saeki

Abstract:

This paper presents the results of an experimental study on the performance of a triboelectric separator of plastic mixtures used for recycling. The separator consists of four cylindrical electrodes. The principle behind the separation technique is based on the difference in the Coulomb force acting on the plastic particles after triboelectric charging. The separation of mixtures of acrylonitrile butadiene styrene (ABS) and polystyrene (PS) using this method was studied. The effects of the triboelectric charging time and applied voltage on the separation efficiency were investigated. The experimental results confirm that it is possible to obtain a high purity and recovery rate for the initial compositions considered in this study.

Keywords: Coulomb force, recycling, triboelectric separator, waste plastics.

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Authors: Yeonsoo Jang, Dongweon Yoon, Ki Ho Kwon, Jaeyoon Lee, Wooju Lee

Abstract:

Phase error in communications systems degrades error performance. In this paper, we present a simple approximation for the average error probability of the binary phase shift keying (BPSK) in the presence of phase error having a uniform distribution on arbitrary intervals. For the simple approximation, we use symmetry and periodicity of a sinusoidal function. Approximate result for the average error probability is derived, and the performance is verified through comparison with simulation result.

Keywords: Average error probability, Phase shift keying, Phase error

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Authors: Jaechun No

Abstract:

As data to be stored in storage subsystems tremendously increases, data protection techniques have become more important than ever, to provide data availability and reliability. In this paper, we present the file system-based data protection (WOWSnap) that has been implemented using WORM (Write-Once-Read-Many) scheme. In the WOWSnap, once WORM files have been created, only the privileged read requests to them are allowed to protect data against any intentional/accidental intrusions. Furthermore, all WORM files are related to their protection cycle that is a time period during which WORM files should securely be protected. Once their protection cycle is expired, the WORM files are automatically moved to the general-purpose data section without any user interference. This prevents the WORM data section from being consumed by unnecessary files. We evaluated the performance of WOWSnap on Linux cluster.

Keywords: Data protection, Protection cycle, WORM

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Authors: Pavel Vazan, Pavol Tanuska, Michal Kebisek

Abstract:

The paper gives the pilot results of the project that is oriented on the use of data mining techniques and knowledge discoveries from production systems through them. They have been used in the management of these systems. The simulation models of manufacturing systems have been developed to obtain the necessary data about production. The authors have developed the way of storing data obtained from the simulation models in the data warehouse. Data mining model has been created by using specific methods and selected techniques for defined problems of production system management. The new knowledge has been applied to production management system. Gained knowledge has been tested on simulation models of the production system. An important benefit of the project has been proposal of the new methodology. This methodology is focused on data mining from the databases that store operational data about the production process.

Keywords: data mining, data warehousing, management of production system, simulation

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya, M. Sharmila

Abstract:

There have been a lot of efforts and researches undertaken in developing efficient tools for performing several tasks in data mining. Due to the massive amount of information embedded in huge data warehouses maintained in several domains, the extraction of meaningful pattern is no longer feasible. This issue turns to be more obligatory for developing several tools in data mining. Furthermore the major aspire of data mining software is to build a resourceful predictive or descriptive model for handling large amount of information more efficiently and user friendly. Data mining mainly contracts with excessive collection of data that inflicts huge rigorous computational constraints. These out coming challenges lead to the emergence of powerful data mining technologies. In this survey a diverse collection of data mining tools are exemplified and also contrasted with the salient features and performance behavior of each tool.

Keywords: Business Analytics, Data Mining, Data Analysis, Machine Learning, Text Mining, Predictive Analytics, Visualization.

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Authors: Dennis A. Apuan

Abstract:

Categorical data based on description of the agricultural landscape imposed some mathematical and analytical limitations. This problem however can be overcome by data transformation through coding scheme and the use of non-parametric multivariate approach. The present study describes data transformation from qualitative to numerical descriptors. In a collection of 103 random soil samples over a 60 hectare field, categorical data were obtained from the following variables: levels of nitrogen, phosphorus, potassium, pH, hue, chroma, value and data on topography, vegetation type, and the presence of rocks. Categorical data were coded, and Spearman-s rho correlation was then calculated using PAST software ver. 1.78 in which Principal Component Analysis was based. Results revealed successful data transformation, generating 1030 quantitative descriptors. Visualization based on the new set of descriptors showed clear differences among sites, and amount of variation was successfully measured. Possible applications of data transformation are discussed.

Keywords: data transformation, numerical descriptors, principalcomponent analysis

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Authors: Mihai Gheorghe

Abstract:

Freelancing in IT has seen an increased popularity during the last years mainly because of the fast Internet adoption in the countries with emerging economies, correlated with the continuous seek for reduced development costs as well with the rise of online platforms which address planning, coordination and various development tasks. This paper conducts an overview of the most relevant Freelance Marketplaces available and studies the market structure, distribution of the workforce and trends in IT freelancing.

Keywords: Freelancing in IT, Freelance Marketplaces, Freelance Market Structure, Globalization, Online Staffing, Trends in Freelancing.

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Authors: Aleksandra Zysk, Pawel Badura

Abstract:

Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.

Keywords: Classification, singing, spectral analysis, vocal emission, vocal register.

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Authors: Essam Al Daoud

Abstract:

To improve the classification rate of the face recognition, features combination and a novel non-linear kernel are proposed. The feature vector concatenates three different radius of local binary patterns and Gabor wavelet features. Gabor features are the mean, standard deviation and the skew of each scaling and orientation parameter. The aim of the new kernel is to incorporate the power of the kernel methods with the optimal balance between the features. To verify the effectiveness of the proposed method, numerous methods are tested by using four datasets, which are consisting of various emotions, orientations, configuration, expressions and lighting conditions. Empirical results show the superiority of the proposed technique when compared to other methods.

Keywords: Face recognition, Gabor wavelet, LBP, Non-linearkerner

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

Abstract:

Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: Semantic data integration, biological ontology, linked data, semantic web, OWL, RDF.

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Authors: Hossein Khademolhosseini, Mehdi Hosseinzadeh

Abstract:

The residue number system (RNS), due to its properties, is used in applications in which high performance computation is needed. The carry free nature, which makes the arithmetic, carry bounded as well as the paralleling facility is the reason of its capability of high speed rendering. Since carry is not propagated between the moduli in this system, the performance is only restricted by the speed of the operations in each modulus. In this paper a novel method of number representation by use of redundancy is suggested in which {rn- 2,rn-1,rn} is the reference moduli set where r=2k+1 and k =1, 2,3,.. This method achieves fast computations and conversions and makes the circuits of them much simpler.

Keywords: Binary to RNS converter, Carry save adder, Computer arithmetic, Residue number system.

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