Search results for: Data Parallel

Authors: Makoto Nagatomo, Yasuo Uchida, Makoto Sakamoto, Tuo Zhang, Tatsuma Kurogi, Takao Ito, Tsunehiro Yoshinaga, Satoshi Ikeda, Masahiro Yokomichi, Hiroshi Furutani

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This paper presents a four-dimensional computational model, k-neighborhood template A-type three-dimensional bounded cellular acceptor (abbreviated as A-3BCA(k)), and discusses the hierarchical properties. An A-3BCA(k) is a four-dimensional automaton which consists of a pair of a converter and a configuration-reader. The former converts the given four-dimensional tape to the three- and two- dimensional configuration and the latter determines the acceptance or nonacceptance of given four-dimensional tape whether or not the derived two-dimensional configuration is accepted. We mainly investigate the difference of the accepting power based on the difference of the configuration-reader. It is shown that the difference of the accepting power of the configuration-reader tends to affect directly that of the A-3BCA(k) for the case when the converter is deterministic. On the other hand, results are not analogous for the nondeterministic case.

Keywords: Cellular acceptor, configuration-reader, converter, finite automaton, four-dimension, on-line tessellation acceptor, parallel/sequential array acceptor, turing machine.

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Authors: Barenten Suciu

Abstract:

In this paper, a theoretical study on the forced vibration of one degree of freedom system equipped with inerter, working under load-type or displacement-type excitation, is presented. Differential equations of movement are solved under cosinusoidal excitation, and explicit relations for the magnitude, resonant magnitude, phase angle, resonant frequency, and critical frequency are obtained. Influence of the inertance and damping on these dynamic characteristics is clarified. From the obtained results, one concludes that the inerter increases the magnitude of vibration and the phase angle of the damped mechanical system. Moreover, the magnitude ratio and difference of phase angles are not depending on the actual type of excitation. Consequently, such kind of similitude allows for the comparison of various theoretical and experimental results, which can be broadly found in the literature.

Keywords: One degree of freedom vibration, inerter, parallel connection, load-type excitation, displacement-type excitation.

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Authors: B.R. Potgieter, G. Venter

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Numerical design optimization is a powerful tool that can be used by engineers during any stage of the design process. There are many different applications for structural optimization. A specific application that will be discussed in the following paper is experimental data matching. Data obtained through tests on a physical structure will be matched with data from a numerical model of that same structure. The data of interest will be the dynamic characteristics of an antenna structure focusing on the mode shapes and modal frequencies. The structure used was a scaled and simplified model of the Karoo Array Telescope-7 (KAT-7) antenna structure. This kind of data matching is a complex and difficult task. This paper discusses how optimization can assist an engineer during the process of correlating a finite element model with vibration test data.

Keywords: Finite Element Model (FEM), Karoo Array Telescope(KAT-7), modal frequencies, mode shapes, optimization, shape optimization, size optimization, vibration tests

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Authors: Guo Wenyu, Qu Youli

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A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: Compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA.

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Authors: Tristan O’Neill, Trina Myers, Jarrod Trevathan

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The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: Liu Ning, Zhong Chongquan, Teng Hongfei

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EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.

Keywords: EPA system, Industrial Ethernet, Periodic data, Real-time performance

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Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

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Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: Data quality, feature selection, probability distribution, string classification, string length.

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Authors: Ehsan Vaziri Goodarzi, Mahmood Houshmand, Omid Fatahi Valilai, Vahidreza Ghezavati, Shahrooz Bamdad

Abstract:

One important paradigm of industry 4.0 is Cloud Manufacturing (CM). In CM everything is considered as a service, therefore, the CM platform should consider all service provider's capabilities and tries to integrate services in an equilibrium state. This research develops a framework for implementing manufacturing cloud service composition in the equilibrium state. The developed framework using well-known tools called axiomatic design (AD) and game theory. The research has investigated the factors for forming equilibrium for measures of the manufacturing cloud service composition. Functional requirements (FRs) represent the measures of manufacturing cloud service composition in the equilibrium state. These FRs satisfied by related Design Parameters (DPs). The FRs and DPs are defined by considering the game theory, QoS, consumer needs, parallel and cooperative services. Ultimately, four FRs and DPs represent the framework. To insure the validity of the framework, the authors have used the first AD’s independent axiom.

Keywords: Axiomatic design, manufacturing cloud service composition, cloud manufacturing, Industry 4.0.

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Authors: Junghoon Lee, Gyung-Leen Park, Ho-Young Kwak, Cheol Min Kim

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This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.

Keywords: sensor network, intelligent farm, middleware, event detection

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Authors: S. Impey, D. Berry, S. Furtado, M. Galvin, L. Grogan, O. Hardiman, L. Hederman, M. Heverin, V. Wade, L. Douris, D. O'Sullivan, G. Stephens

Abstract:

Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: Healthcare, knowledge acquisition, maximal data sets, action design science.

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Authors: Salam Khalifa, Naveed Ahmed

Abstract:

We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignement method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, Temporally Coherent 3D Animation.

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Authors: Naoki Yamamoto, Jun Murakami, Chiharu Okuma, Yutaro Shigeto, Satoko Saito, Takashi Izumi, Nozomi Hayashida

Abstract:

Multi-dimensional principal component analysis (PCA) is the extension of the PCA, which is used widely as the dimensionality reduction technique in multivariate data analysis, to handle multi-dimensional data. To calculate the PCA the singular value decomposition (SVD) is commonly employed by the reason of its numerical stability. The multi-dimensional PCA can be calculated by using the higher-order SVD (HOSVD), which is proposed by Lathauwer et al., similarly with the case of ordinary PCA. In this paper, we apply the multi-dimensional PCA to the multi-dimensional medical data including the functional independence measure (FIM) score, and describe the results of experimental analysis.

Keywords: multi-dimensional principal component analysis, higher-order SVD (HOSVD), functional independence measure (FIM), medical data, tensor decomposition

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: Data analytics, green production, industrial energy management, optimization, renewable energies, simulation.

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Authors: Sergey N. Sayapin, Anatoly P. Karpenko, Suan H. Dang

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Comparative analysis of robotic vehicles for pipe inspection is presented in this paper. The promising concept of self-propelled intelligent robotic vehicle (SPIRV) based on octahedral dodekapod for inspection and operation in active branched pipelines with variable cross-sections is reasoned. SPIRV is able to move in pipeline, regardless of its spatial orientation. SPIRV can also be used to move along the outside of the pipelines as well as in space between surfaces of annular tubes. Every one of faces of the octahedral dodekapod can clamp/unclamp a thing with a closed loop surface of various forms as well as put pressure on environmental surface of contact. These properties open new possibilities for its applications in SPIRV. We examine design principles of octahedral dodekapod as future intelligent building blocks for various robotic vehicles that can self-move and self-reconfigure.

Keywords: Modular robot, octahedral dodekapod, pipe inspection robot, spatial parallel structure.

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Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which cover the variety of figure proportions in both height and girth. 3,000 data have been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from the some states of India to produce the sizing system suitable for clothing manufacture and retailing. The data are used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from the large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: Anthropometric data, data mining, decision tree, garments manufacturing, ready-made garments, sizing systems.

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Authors: Huynh Quyet Thang, Vo Sy Nam

Abstract:

Schema matching plays a key role in many different applications, such as schema integration, data integration, data warehousing, data transformation, E-commerce, peer-to-peer data management, ontology matching and integration, semantic Web, semantic query processing, etc. Manual matching is expensive and error-prone, so it is therefore important to develop techniques to automate the schema matching process. In this paper, we present a solution for XML schema automated matching problem which produces semantic mappings between corresponding schema elements of given source and target schemas. This solution contributed in solving more comprehensively and efficiently XML schema automated matching problem. Our solution based on combining linguistic similarity, data type compatibility and structural similarity of XML schema elements. After describing our solution, we present experimental results that demonstrate the effectiveness of this approach.

Keywords: XML Schema, Schema Matching, SemanticMatching, Automatic XML Schema Matching.

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Authors: A. Habibizad Navin, A. Sadighi, M. Naghian Fesharaki, M. Mirnia, M. Teshnelab, R. Keshmiri

Abstract:

This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.

Keywords: Data oriented modelling, image, clustering, segmentation, classification, ADBT and image processing.

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Authors: Neelima Gupta, Seema Aggarwal

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Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.

Keywords: Biclustering, mutual information.

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Authors: T. Aydin, M. F. Alaeddinoglu

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People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatiotemporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newlyformed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: Apriori algorithm, association rules, data mining, spatio-temporal data.

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Authors: Sushma Satpute, Vaishali Katkar, Nilesh Sahare

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XML files contain data which is in well formatted manner. By studying the format or semantics of the grammar it will be helpful for fast retrieval of the data. There are many algorithms which describes about searching the data from XML files. There are no. of approaches which uses data structure or are related to the contents of the document. In these cases user must know about the structure of the document and information retrieval techniques using NLPs is related to content of the document. Hence the result may be irrelevant or not so successful and may take more time to search.. This paper presents fast XML retrieval techniques by using new indexing technique and the concept of RXML. When indexing an XML document, the system takes into account both the document content and the document structure and assigns the value to each tag from file. To query the system, a user is not constrained about fixed format of query.

Keywords: XML Retrieval, Indexed Search, Information Retrieval.

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Authors: Joel Arrais, João E. Pereira, João Fernandes, José Luís Oliveira

Abstract:

The scientific achievements coming from molecular biology depend greatly on the capability of computational applications to analyze the laboratorial results. A comprehensive analysis of an experiment requires typically the simultaneous study of the obtained dataset with data that is available in several distinct public databases. Nevertheless, developing a centralized access to these distributed databases rises up a set of challenges such as: what is the best integration strategy, how to solve nomenclature clashes, how to solve database overlapping data and how to deal with huge datasets. In this paper we present GeNS, a system that uses a simple and yet innovative approach to address several biological data integration issues. Compared with existing systems, the main advantages of GeNS are related to its maintenance simplicity and to its coverage and scalability, in terms of number of supported databases and data types. To support our claims we present the current use of GeNS in two concrete applications. GeNS currently contains more than 140 million of biological relations and it can be publicly downloaded or remotely access through SOAP web services.

Keywords: Data integration, biological databases

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Authors: Malcolm R Davidson, Ram P. Bharti, Petar Liovic, Dalton J.E. Harvie

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The electrokinetic flow resistance (electroviscous effect) is predicted for steady state, pressure-driven liquid flow at low Reynolds number in a microfluidic contraction of rectangular cross-section. Calculations of the three dimensional flow are performed in parallel using a finite volume numerical method. The channel walls are assumed to carry a uniform charge density and the liquid is taken to be a symmetric 1:1 electrolyte. Predictions are presented for a single set of flow and electrokinetic parameters. It is shown that the magnitude of the streaming potential gradient and the charge density of counter-ions in the liquid is greater than that in corresponding two-dimensional slit-like contraction geometry. The apparent viscosity is found to be very close to the value for a rectangular channel of uniform cross-section at the chosen Reynolds number (Re = 0.1). It is speculated that the apparent viscosity for the contraction geometry will increase as the Reynolds number is reduced.

Keywords: Contraction, Electroviscous, Microfluidic, Numerical.

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Authors: C. Kalamani, K. Paramasivam

Abstract:

Test data compression is an efficient method for reducing the test application cost. The problem of reducing test data has been addressed by researchers in three different aspects: Test Data Compression, Built-in-Self-Test (BIST) and Test set compaction. The latter two methods are capable of enhancing fault coverage with cost of hardware overhead. The drawback of the conventional methods is that they are capable of reducing the test storage and test power but when test data have redundant length of runs, no additional compression method is followed. This paper presents a modified Run Length Coding (RLC) technique with Multilevel Selective Huffman Coding (MLSHC) technique to reduce test data volume, test pattern delivery time and power dissipation in scan test applications where redundant length of runs is encountered then the preceding run symbol is replaced with tiny codeword. Experimental results show that the presented method not only improves the test data compression but also reduces the overall test data volume compared to recent schemes. Experiments for the six largest ISCAS-98 benchmarks show that our method outperforms most known techniques.

Keywords: Modified run length coding, multilevel selective Huffman coding, built-in-self-test modified selective Huffman coding, automatic test equipment.

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Authors: Saleh Abduallah Saleh, Mohammad Basir Bin Saud, Mohd Azwardi Md Isa

Abstract:

It is very important for a developing nation to developing their infrastructure on the prime priority because their infrastructure particularly their roads and transportation functions as a blood in the system. Almost 1.1 billion populations share the travel and transportation industry in India. On the other hand, the Pakistan transportation industry is also extensive and elevating about 170 million users of transportation. Indian and Pakistani specifically within bus industry are well connected within and between the urban and rural areas. The transportation industry is radically helping the economic alleviation of both countries. Due to high economic instability, unemployment and poverty rate both countries governments are very serious and committed to help for boosting their economy. They believe that any form of transportation development would play a vital role in the development of land, infrastructure which could indirectly support many other industries’ developments, such as tourism, freighting and shipping businesses, just to mention a few. However, it seems that their previous transportation planning in the due course has failed to meet the fast growing demand. As with the span of time, both the countries are looking forward to a long-term, and economical solutions, because the demand is from time to time keep appreciating and reacting according to other key economic drivers. Content analysis method and case study approach is used in this paper and secondary data from the bureau of statistic is used for case analysis. The paper focused on the mobility concerns of the lower and middle-income people in India and Pakistan. The paper is aimed to highlight the weaknesses, opportunities and limitations resulting from low priority industry for a government, which is making the either country's public suffer. The paper has concluded that the main issue is identified as the slow, inappropriate, and unfavorable decisions which are not in favor of long-term country’s economic development and public interest. The paper also recommends to future research avenues for public and private transportation, which is continuously failing to meet the public expectations.

Keywords: Bus transportation industries, transportation demand, government parallel initiatives, road and traffic congestions.

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Authors: Mohamed Watfa, William Daher, Hisham Al Azar

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The main idea behind in network aggregation is that, rather than sending individual data items from sensors to sinks, multiple data items are aggregated as they are forwarded by the sensor network. Existing sensor network data aggregation techniques assume that the nodes are preprogrammed and send data to a central sink for offline querying and analysis. This approach faces two major drawbacks. First, the system behavior is preprogrammed and cannot be modified on the fly. Second, the increased energy wastage due to the communication overhead will result in decreasing the overall system lifetime. Thus, energy conservation is of prime consideration in sensor network protocols in order to maximize the network-s operational lifetime. In this paper, we give an energy efficient approach to query processing by implementing new optimization techniques applied to in-network aggregation. We first discuss earlier approaches in sensors data management and highlight their disadvantages. We then present our approach “Energy Efficient Indexed Aggregation" (EEIA) and evaluate it through several simulations to prove its efficiency, competence and effectiveness.

Keywords: Sensor Networks, Data Base, Data Fusion, Aggregation, Indexing, Energy Efficiency

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: Classification, fuzzy logic, tolerance relations, rainfall data.

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Authors: A. Sabzali, M. Nikaeen, B. Bina

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The purpose of the experiments described in this article was the comparison of integrated fixed film activated sludge (IFAS) and activated sludge (AS) system. The IFAS applied system consists of the cigarette filter rods (wasted filter in tobacco factories) as a biofilm carrier. The comparison with activated sludge was performed by two parallel treatment lines. Organic substance, ammonia and TP removal was investigated over four month period. Synthetic wastewater was prepared with ordinary tap water and glucose as the main sources of carbon and energy, plus balanced macro and micro nutrients. COD removal percentages of 94.55%, and 81.62% were achieved for IFAS and activated sludge system, respectively. Also, ammonia concentration significantly decreased by increasing the HRT in both systems. The average ammonia removal of 97.40 % and 96.34% were achieved for IFAS and activated sludge system, respectively. The removal efficiency of total phosphorus (TP-P) was 60.64%, higher than AS process by 56.63% respectively.

Keywords: Wastewater, biofilm carrier, cigarette filters rods, Activated Sludge, IFAS, nitrification.

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Authors: Shun Hattori

Abstract:

In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services with the Web-mined knowledge have begun to be developed for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore, this paper introduces the simplest Web Sensor and spatiotemporallynormalized Web Sensor to extract spatiotemporal data about a target phenomenon from weblogs searched by keyword(s) representing the target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity analyses of coefficient correlation with temperature, rainfall, snowfall, and earthquake statistics per day by region of Japan Meteorological Agency as physical-world data: spatial granularity (region-s population density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., “rain" vs. “heavy rain"), and media granularity (weblogs vs. microblogs such as Tweets).

Keywords: Granularity analysis, knowledge extraction, spatiotemporal data mining, Web credibility, Web mining, Web sensor.

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Authors: P. K. Gupta

Abstract:

The present paper deals with the experimental and computational study of axial collapse of the aluminum metallic shells having combined tube-frusta geometry between two parallel plates. Shells were having bottom two third lengths as frusta and remaining top one third lengths as tube. Shells were compressed to recognize their modes of collapse and associated energy absorption capability. An axisymmetric Finite Element computational model of collapse process is presented and analysed, using a non-linear FE code FORGE2. Six noded isoparametric triangular elements were used to discretize the deforming shell. The material of the shells was idealized as rigid visco-plastic. To validate the computational model experimental and computed results of the deformed shapes and their corresponding load-compression and energy-compression curves were compared. With the help of the obtained results progress of the axisymmetric mode of collapse has been presented, analysed and discussed.

Keywords: Axial compression, crashworthiness, energy absorption, FORGE2, metallic shells.

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Authors: Harshit Mehrotra, Gaurav Agrawal, M.C. Srivastava

Abstract:

Computerized lip reading has been one of the most actively researched areas of computer vision in recent past because of its crime fighting potential and invariance to acoustic environment. However, several factors like fast speech, bad pronunciation, poor illumination, movement of face, moustaches and beards make lip reading difficult. In present work, we propose a solution for automatic lip contour tracking and recognizing letters of English language spoken by speakers using the information available from lip movements. Level set method is used for tracking lip contour using a contour velocity model and a feature vector of lip movements is then obtained. Character recognition is performed using modified k nearest neighbor algorithm which assigns more weight to nearer neighbors. The proposed system has been found to have accuracy of 73.3% for character recognition with speaker lip movements as the only input and without using any speech recognition system in parallel. The approach used in this work is found to significantly solve the purpose of lip reading when size of database is small.

Keywords: Contour Velocity Model, Lip Contour Tracking, LipReading, Visual Character Recognition.

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