Search results for: data quality

Authors: Tarun Gulati, Kapil Gupta, Dushyant Gupta

Abstract:

High resolution images are always desired as they contain the more information and they can better represent the original data. So, to convert the low resolution image into high resolution interpolation is done. The quality of such high resolution image depends on the interpolation function and is assessed in terms of sharpness of image. This paper focuses on Wavelet based Interpolation Techniques in which an input image is divided into subbands. Each subband is processed separately and finally combined the processed subbandsto get the super resolution image. 

Keywords: SWT, DWTSR, DWTSWT, DWCWT.

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Authors: Sakol Udomsiri, Masahiro Iwahashi

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This paper presents comparative study on recent integer DCTs and a new method to construct a low sensitive structure of integer DCT for colored input signals. The method refers to sensitivity of multiplier coefficients to finite word length as an indicator of how word length truncation effects on quality of output signal. The sensitivity is also theoretically evaluated as a function of auto-correlation and covariance matrix of input signal. The structure of integer DCT algorithm is optimized by combination of lower sensitive lifting structure types of IRT. It is evaluated by the sensitivity of multiplier coefficients to finite word length expression in a function of covariance matrix of input signal. Effectiveness of the optimum combination of IRT in integer DCT algorithm is confirmed by quality improvement comparing with existing case. As a result, the optimum combination of IRT in each integer DCT algorithm evidently improves output signal quality and it is still compatible with the existing one.

Keywords: DCT, sensitivity, lossless, wordlength.

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of big data technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centres or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through VADER and RoBERTa model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and Term Frequency – Inverse Document Frequency (TFIDF) Vectorization and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide if the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: Counter vectorization, Convolutional Neural Network, Crawler, data technology, Long Short-Term Memory, LSTM, Web Scraping, sentiment analysis.

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Authors: Eugenie A. Kachvoryan, Astghik Z. Pepoyan, Maria V. Harutyunova, Anahit M. Manvelyan

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Taking into account the importance of Lake Sevan and Lake Sevan basin-s rivers for Armenian economy, the main goals of our investigations were the documentation of water quality and the biodiversity of invertebrates developed in Lake Sevan basin-s rivers and selected tributaries. Moderately satisfied ecological condition for the biodiversity of Lake Sevan basin-s rivers has been established, and the changes in species- composition of zoobenthos in Lake Sevan were detected. A growing tendency of antibiotic resistance among E. coli isolates in water resources has been shown.

Keywords: Biodiversity, ecosystem, Lake Sevan, water-quality, zoobenthos.

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Authors: Elena Carcano, Mirzi Betasolo

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This study helps Public Water Bureaus in giving reliable answers to water concession requests. Rapidly increasing water requests can be supported provided that further uses of a river course are not totally compromised, and environmental features are protected as well. Strictly speaking, a water concession can be considered a continuous drawing from the source and causes a mean annual streamflow reduction. Therefore, deciding if a water concession is appropriate or inappropriate seems to be easily solved by comparing the generic demand to the mean annual streamflow value at disposal. Still, the immediate shortcoming for such a comparison is that streamflow data are information available only for few catchments and, most often, limited to specific sites. Subsequently, comparing the generic water demand to mean daily discharge is indeed far from being completely satisfactory since the mean daily streamflow is greater than the water withdrawal for a long period of a year. Consequently, such a comparison appears to be of little significance in order to preserve the quality and the quantity of the river. In order to overcome such a limit, this study aims to complete the information provided by flow duration curves introducing a link between Flow Duration Curves (FDCs) and recession curves and aims to show the chronological sequence of flows with a particular focus on low flow data. The analysis is carried out on 25 catchments located in North-Eastern Italy for which daily data are provided. The results identify groups of catchments as hydrologically homogeneous, having the lower part of the FDCs (corresponding streamflow interval is streamflow Q between 300 and 335, namely: Q(300), Q(335)) smoothly reproduced by a common recession curve. In conclusion, the results are useful to provide more reliable answers to water request, especially for those catchments which show similar hydrological response and can be used for a focused regionalization approach on low flow data. A mathematical link between streamflow duration curves and recession curves is herein provided, thus furnishing streamflow duration curves information upon a temporal sequence of data. In such a way, by introducing assumptions on recession curves, the chronological sequence upon low flow data can also be attributed to FDCs, which are known to lack this information by nature.

Keywords: Chronological sequence of discharges, recession curves, streamflow duration curves, water concession.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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Authors: Odón R. Sánchez-Ccoyllo, Elizabeth Ayma-Choque, Alan Llacza

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Sulphur dioxide (SO₂) and surface-ozone (O₃) concentrations are associated with diseases. The objective of this research is to evaluate the effectiveness of the air-quality Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model with a horizontal resolution of 5 km x 5 km. For this purpose, the measurements of the hourly SO₂ and O₃ concentrations available in three air quality monitoring stations in Lima, Peru were used for the purpose of validating the simulations of the SO₂ and O₃ concentrations obtained with the WRF-Chem model in February 2018. For the quantitative evaluation of the simulations of these gases, statistical techniques were implemented, such as the average of the simulations; the average of the measurements; the Mean Bias (MeB); the Mean Error (MeE); and the Root Mean Square Error (RMSE). The results of these statistical metrics indicated that the simulated SO₂ and O₃ values over-predicted the SO₂ and O₃ measurements. For the SO₂ concentration, the MeB values varied from 0.58 to 26.35 µg/m³; the MeE values varied from 8.75 to 26.5 µg/m³; the RMSE values varied from 13.3 to 31.79 µg/m³; while for O₃ concentrations the statistical values of the MeB varied from 37.52 to 56.29 µg/m³; the MeE values varied from 37.54 to 56.70 µg/m³; the RMSE values varied from 43.05 to 69.56 µg/m³.

Keywords: Ground-ozone, Lima, Sulphur dioxide, WRF-Chem.

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Authors: Dipen A. Mistry, Bhupelly Dheeraj, Ravit Gautam, Manmohan Singh Meena, Suresh Mikkili

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In recent years the large scale use of the power electronic equipment has led to an increase of harmonics in the power system. The harmonics results into a poor power quality and have great adverse economical impact on the utilities and customers. Current harmonics are one of the most common power quality problems and are usually resolved by using shunt active filter (SHAF). The main objective of this work is to develop PI and Fuzzy logic controllers (FLC) to analyze the performance of Shunt Active Filter for mitigating current harmonics under balanced and unbalanced sinusoidal source voltage conditions for normal load and increased load. When the supply voltages are ideal (balanced), both PI and FLC are converging to the same compensation characteristics. However, the supply voltages are non-ideal (unbalanced), FLC offers outstanding results. Simulation results validate the superiority of FLC with triangular membership function over the PI controller.

Keywords: DC link voltage, Fuzzy logic controller, Harmonics, PI controller, Shunt Active Filter.

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Authors: Marichela Sepe

Abstract:

The sustainability of a place depends on a series of factors which contribute to the quality of life, sense of place and recognition of identity. An activity like walking, which in itself is obviously ''sustainable'', can become non sustainable if the context in which it is carried out does not meet the conditions for an adequate quality of life. This work is aimed at proposing the analytical method of Place Maker to identify the elements that do not feature in traditional mapping and which constitute the contemporary identity of the places, and the relative complex map to represent those elements and support sustainable urban identity design. The method's potential for areas with a predominantly pedestrian vocation is illustrated by means of the case study of the Ramblas in Barcelona.

Keywords: Place-identity, PlaceMaker, sustainability, walkability.

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Authors: Kwok W. Mui, Ling T. Wong, F. Xiao, Chin T. Cheung, Ho C. Yu

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This study addresses a concept of the Sustainable Building Environmental Model (SBEM) developed to optimize energy consumption in air conditioning and ventilation (ACV) systems without any deterioration of indoor environmental quality (IEQ). The SBEM incorporates two main components: an adaptive comfort temperature control module (ACT) and a new carbon dioxide demand control module (nDCV). These two modules take an innovative approach to maintain satisfaction of the Indoor Environmental Quality (IEQ) with optimum energy consumption; they provide a rational basis of effective control. A total of 2133 sets of measurement data of indoor air temperature (Ta), relative humidity (Rh) and carbon dioxide concentration (CO2) were conducted in some Hong Kong offices to investigate the potential of integrating the SBEM. A simulation was used to evaluate the dynamic performance of the energy and air conditioning system with the integration of the SBEM in an air-conditioned building. It allows us make a clear picture of the control strategies and performed any pre-tuned of controllers before utilized in real systems. With the integration of SBEM, it was able to save up to 12.3% in simulation of overall electricity consumption, and maintain the average carbon dioxide concentration within 1000ppm and occupant dissatisfaction in 20%. 

Keywords: —Sustainable building environmental model (SBEM), adaptive comfort temperature (ACT), new demand control ventilation (nDCV), energy saving.

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Authors: Paiboon Jeamponk, Tasanee Ponglaa, Patchapon Srisanguan

Abstract:

The aim of this research paper was based on an examination of sources of water supply and water quality for local consumption, conducted at eco- tourism villages of Suan Luang Sub- District Municipality of Amphawa District, Samut Songkram Province. The study incorporated both questionnaire and field work of water testing as the research tool and method. The sample size of 288 households was based on the population of the district, whereas the selected sample water sources were from 60 households: 30 samples were ground water and another 30 were surface water. Degree of heavy metal contamination in the water including copper, iron, manganese, zinc, cadmium and lead was investigated utilizing the Atomic Absorption- Direct Aspiration method. The findings unveiled that 96.0 percent of household water consumption was based on water supply, while the rest on canal, river and rain water. The household behavior of consumption revealed that 47.2 percent of people routinely consumed water without boiling or filtering prior to consumption. The investigation of water supply quality found that the degree of heavy metal contamination including metal, lead, iron, copper, manganese and cadmium met the standards of the Department of Health.

Keywords: Sources of water supply, water quality, water supply.

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Authors: Vishnu Pratap Singh Kirar

Abstract:

In the cloud computing hierarchy IaaS is the lowest layer, all other layers are built over it. Thus it is the most important layer of cloud and requisite more importance. Along with advantages IaaS faces some serious security related issue. Mainly Security focuses on Integrity, confidentiality and availability. Cloud computing facilitate to share the resources inside as well as outside of the cloud. On the other hand, cloud still not in the state to provide surety to 100% data security. Cloud provider must ensure that end user/client get a Quality of Service. In this report we describe possible aspects of cloud related security.

Keywords: Cloud Computing, Cloud Networking, IaaS, PaaS, SaaS, Cloud Security.

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Authors: Walid Cherif

Abstract:

Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: Data mining, knowledge discovery, machine learning, similarity measurement, supervised classification.

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Authors: Lei Guo, Xu Zhang, Weigang Hou

Abstract:

Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, software defined network, traffic grooming.

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Authors: Hyun-Woo Cho

Abstract:

The fault detection and diagnosis of complicated production processes is one of essential tasks needed to run the process safely with good final product quality. Unexpected events occurred in the process may have a serious impact on the process. In this work, triangular representation of process measurement data obtained in an on-line basis is evaluated using simulation process. The effect of using linear and nonlinear reduced spaces is also tested. Their diagnosis performance was demonstrated using multivariate fault data. It has shown that the nonlinear technique based diagnosis method produced more reliable results and outperforms linear method. The use of appropriate reduced space yielded better diagnosis performance. The presented diagnosis framework is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. The use of reduced model space helps to mitigate the sensitivity of the fault pattern to noise.

Keywords: Real-time Fault diagnosis, triangular representation of patterns in reduced spaces, Nonlinear kernel technique, multivariate statistical modeling.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

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This paper presents design trade-off and performance impacts of the amount of pipeline phase of control path signals in a wormhole-switched network-on-chip (NoC). The numbers of the pipeline phase of the control path vary between two- and one-cycle pipeline phase. The control paths consist of the routing request paths for output selection and the arbitration paths for input selection. Data communications between on-chip routers are implemented synchronously and for quality of service, the inter-router data transports are controlled by using a link-level congestion control to avoid lose of data because of an overflow. The trade-off between the area (logic cell area) and the performance (bandwidth gain) of two proposed NoC router microarchitectures are presented in this paper. The performance evaluation is made by using a traffic scenario with different number of workloads under 2D mesh NoC topology using a static routing algorithm. By using a 130-nm CMOS standard-cell technology, our NoC routers can be clocked at 1 GHz, resulting in a high speed network link and high router bandwidth capacity of about 320 Gbit/s. Based on our experiments, the amount of control path pipeline stages gives more significant impact on the NoC performance than the impact on the logic area of the NoC router.

Keywords: Network-on-Chip, Synchronous Parallel Pipeline, Router Architecture, Wormhole Switching

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

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Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.

Keywords: Business intelligence, data mining, functionalprogramming, intelligent system.

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

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Clustering in data mining is an unsupervised learning technique of aggregating the data objects into meaningful groups such that the intra cluster similarity of objects are maximized and inter cluster similarity of objects are minimized. Over the past decades several clustering tools were emerged in which clustering algorithms are inbuilt and are easier to use and extract the expected results. Data mining mainly deals with the huge databases that inflicts on cluster analysis and additional rigorous computational constraints. These challenges pave the way for the emergence of powerful expansive data mining clustering softwares. In this survey, a variety of clustering tools used in data mining are elucidated along with the pros and cons of each software.

Keywords: Cluster Analysis, Clustering Algorithms, Clustering Techniques, Association, Visualization.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop, Pairote Sattayatham

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Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte Carlo method in the approximation step. The data reduction has been performed horizontally and vertically through our EMR sampling method. The proposed method is analyzed by a series of experiments. We apply our algorithm on clustering and classification tasks to evaluate the utility of our approach.

Keywords: Data Stream, Monte Carlo, Sampling, DensityEstimation.

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Authors: C. Kridtayopas, W. Danvilai, P. Sopannarath, A. Kayan, W. Loongyai

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Both Betong chicken (KU Line) and Thai Native chickens were the high quality of the meat and low carcass fat compared to broiler chickens. The objective of this study was to determine the growth performance, carcass characteristic, meat quality and association of polymorphism in the ApoVLDL-II gene with fat accumulation in the female broiler, Thai Native and Betong (KU line) chickens at 4-14 weeks. The chickens were used and reared under the same environment and management (100 chicks per breed). The results showed that body weight (BW) of broiler chickens was significantly higher than Thai Native and Betong (KU line) chickens (P < 0.01) through all the experiment. At 4-8 weeks of age, feed conversion ratio (FCR) of broiler chickens was significantly better than Thai Native and Betong (KU line) chickens (P < 0.01), then increased at week 8-14. The percentage of breast, abdominal fat and subcutaneous fat of broiler chickens was significantly greater than Thai Native and Betong (KU line) chickens (P < 0.01). However, Thai Native chickens showed the highest percentage of liver (P < 0.01) when compared to other breeds. In addition, the percentage of wing of Thai Native and Betong (KU line) chickens were significantly (P < 0.01) higher than broiler chickens. Meat quality was also determined and found that, pH of breast meat left from slaughter 45 minutes (pH45) and 24 hours (pH24) of broiler was significantly higher than Thai Native and Betong (KU line) (P < 0.01) whereas the percentage of drip loss, thawing loss, cooking loss and shear force was not significantly different between breeds. The polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique was used to genotype the polymorphism in the ApoVLDL-II gene in the broiler, Thai Native and Betong (KU line) chickens. The results found that, the polymorphism in the ApoVLDL-II gene at VLDL6 loci was not associated with fat accumulation in those studied population.

Keywords: ApoVLDL-II Gene, Betong (KU line) chickens, broiler chickens, carcass characteristic, growth performance, meat quality, Thai Native Chickens.

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Authors: Meseret Teshome

Abstract:

This study has the objective of assessing the effect of kaizen (5S, Muda elimination and Quality Control Circle (QCC) on employees’ affective attitude (job satisfaction, commitment and job stress) in Kombolcha Textile Share Company. A conceptual model was developed to describe the relationship between Kaizen and Employees’ Affective Attitude (EAA) factors. The three factors of Employee Affective Attitude were measured using questionnaire derived from other validated questionnaire. In the data collection to conduct this study; questionnaire, unstructured interview, written documents and direct observations are used. To analyze the data, SPSS and Microsoft Excel were used. In addition, the internal consistency of similar items in the questionnaire instrument was measured for their equivalence by using the cronbach’s alpha test. In this study, the effect of 5S, Muda elimination and QCC on job satisfaction, commitment and job stress in Kombolcha Textile Share Company is assessed and factors that reduce employees’ job satisfaction with respect to kaizen implementation are identified. The total averages of means from the questionnaire are 3.1 for job satisfaction, 4.31 for job commitment and 4.2 for job stress. And results from interview and secondary data show that kaizen implementation have effect on EAA. In general, based on the thesis results it was concluded that kaizen (5S, muda elimination and QCC) have positive effect for improving EAA factors at KTSC. Finally, recommendations for improvement are given based on the results.

Keywords: Kaizen, job satisfaction, job commitment, job stress.

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: Terrestrial-satellite networks, latency, on-orbit satellite payload, simulation.

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Authors: Roelien Goede

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Data warehousing success is not high enough. User dissatisfaction and failure to adhere to time frames and budgets are too common. Most traditional information systems practices are rooted in hard systems thinking. Today, the great systems thinkers are forgotten by information systems developers. A data warehouse is still a system and it is worth investigating whether systems thinkers such as Churchman can enhance our practices today. This paper investigates data warehouse development practices from a systems thinking perspective. An empirical investigation is done in order to understand the everyday practices of data warehousing professionals from a systems perspective. The paper presents a model for the application of Churchman-s systems approach in data warehouse development.

Keywords: Data warehouse development, Information systemsdevelopment, Interpretive case study, Systems thinking

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Authors: T. Prommi, P. Thamsenanupap

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The influence of physicochemical water quality parameters on the abundance and diversity of caddisfly larvae was studied in seven sampling stations in Mae Tao and Mae Ku watersheds, Mae Sot District, Tak Province, northern Thailand. The streams: MK2 and MK8 as reference site, and impacted streams (MT1-MT5) were sampled bi-monthly during July 2011 to May 2012. A total of 4,584 individual of caddisfly larvae belonging to 10 family and 17 genera were found. The larvae of family Hydropsychidae were the most abundance, followed by Philopotamidae, Odontoceridae, and Leptoceridae, respectively. The genus Cheumatopsyche, Hydropsyche, and Chimarra were the most abundance genera in this study. Results of CCA ordination showed the total dissolved solids, sulfate, water temperature, dissolved oxygen and pH were the most important physicochemical factors to affect distribution of caddisflies communities. Changes in the caddisfly fauna may indicate changes in physicochemical factors owing to agricultural pollution, urbanization, or other human activities. Results revealed that the order Trichoptera, identified to species or genus, can be potentially used to assess environmental water quality status in freshwater ecosystems.

Keywords: Caddisfly larvae, environmental variables, diversity, streams.

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Authors: Mohammed Fethi Khalfi, Malika Kandouci

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Over the past decade, mobile has experienced a revolution that will ultimately change the way we communicate.All these technologies have a common denominator exploitation of computer information systems, but their operation can be tedious because of problems with heterogeneous data sources.To overcome the problems of heterogeneous data sources, we propose to use a technique of adding an extra layer interfacing applications of management or supervision at the different data sources.This layer will be materialized by the implementation of a mediator between different host applications and information systems frequently used hierarchical and relational manner such that the heterogeneity is completely transparent to the VoIP platform.

Keywords: TOIP, Data Integration, Mediation, informationcomputer system, heterogeneous data sources

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Authors: M. Sumana, K. S. Hareesha

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Secure computations are essential while performing privacy preserving data mining. Distributed privacy preserving data mining involve two to more sites that cannot pool in their data to a third party due to the violation of law regarding the individual. Hence in order to model the private data without compromising privacy and information loss, secure multiparty computations are used. Secure computations of product, mean, variance, dot product, sigmoid function using the additive and multiplicative homomorphic property is discussed. The computations are performed on vertically partitioned data with a single site holding the class value.

Keywords: Homomorphic property, secure product, secure mean and variance, secure dot product, vertically partitioned data.

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Authors: I. R. Farah, I. B. Ismail, M. B. Ahmed

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The huge development of new technologies and the apparition of open communication system more and more sophisticated create a new challenge to protect digital content from piracy. Digital watermarking is a recent research axis and a new technique suggested as a solution to these problems. This technique consists in inserting identification information (watermark) into digital data (audio, video, image, databases...) in an invisible and indelible manner and in such a way not to degrade original medium-s quality. Moreover, we must be able to correctly extract the watermark despite the deterioration of the watermarked medium (i.e attacks). In this paper we propose a system for watermarking satellite images. We chose to embed the watermark into frequency domain, precisely the discrete wavelet transform (DWT). We applied our algorithm on satellite images of Tunisian center. The experiments show satisfying results. In addition, our algorithm showed an important resistance facing different attacks, notably the compression (JEPG, JPEG2000), the filtering, the histogram-s manipulation and geometric distortions such as rotation, cropping, scaling.

Keywords: Digital data watermarking, Spatial Database, Satellite images, Discrete Wavelets Transform (DWT).

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Authors: Dae-ho Won, Jong-wook Hong, Yeon-Mo Yang, Jinung An

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To reduce accidents in the industry, WSNs(Wireless Sensor networks)- sensor data is used. WSNs- sensor data has the persistence and continuity. therefore, we design and exploit the buffer management system that has the persistence and continuity to avoid and delivery data conflicts. To develop modules, we use the multi buffers and design the buffer management modules that transfer sensor data through the context-aware methods.

Keywords: safe management system, buffer management, context-aware, input data stream

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: Hybrid MAC protocol, data integrity, lightweight encryption, Neighbor based key sharing, Sensor node data processing, Z-MAC.

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Authors: Rong-Terng Juang

Abstract:

Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: Autonomous vehicle, data recording, remote monitoring, controller area network.

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