Search results for: Data reuse

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

Abstract:

In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: Scalable Architectures, Sustainability, Application Design, Disruptive Technology, Machine Learning, Natural Language Processing, AI, Social Media Platform, Cloud Computing, Advanced Networking, Storage Devices, Advanced Monitoring, Metering Infrastructure, Climate change.

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Authors: Iman Zangeneh, Mostafa Moradi, Ali Mokhtarbaf

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The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

Keywords: data replication, data hiding, consistency, dynamicdata replication strategy

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Authors: Oliver Grün

Abstract:

The success of IT-projects concerning the implementation of business application Software is strongly depending upon the application of an efficient requirements management, to understand the business requirements and to realize them in the IT. But in fact, the Potentials of the requirements management are not fully exhausted by small and medium sized enterprises (SME) of the IT sector. To work out recommendations for action and furthermore a possible solution, allowing a better exhaust of potentials, it shall be examined in a scientific research project, which problems occur out of which causes. In the same place, the storage of knowledge from the requirements management, and its later reuse are important, to achieve sustainable improvements of the competitive of the IT-SMEs. Requirements Engineering is one of the most important topics in Product Management for Software to achieve the goal of optimizing the success of the software product.

Keywords: ERP, Requirements Management

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Authors: Kwok Tak Kit

Abstract:

The government and community have raised their awareness of the benefits of water reuse. Deforestation has a significant effect to climate change as it causes the drying out of the tropical rainforest and hence increases the chance of natural threaten the storage and supply of clean water. This paper focuses on discussion of the relationship of the natural water collection system, afforestation and country parks towards environmental sustainability and circular economy, with a case study of water conservation policy and strategy in Hong Kong and Singapore for further research.

Keywords: Afforestation, environmental sustainability, water conservation, circular economy, climate change.

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Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

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Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: Clustering, data mining, DBSCAN, k-means, k-medoids, sensor data.

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: Big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review.

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Authors: A. Buruzs, A. Torma

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The relationship of the automotive industry with raw material supply is a major challenge and presents obstacles. Automobiles are ones of the most complex products using a large variety of materials. Safety, eco-friendliness and comfort requirements, physical, chemical and economic limitations set the framework in which this industry continuously optimizes the efficient and responsible use of resources. The concept of circular economy covers the issues of waste generation, resource scarcity and economic advantages. However, circularity is already known for the automobile industry – several efforts are done to foster material reuse, product remanufacturing and recycling. The aim of this study is to give an overview on how the producers comply with the growing demands on one hand, and gain efficiency and increase profitability on the other hand from circular economy.

Keywords: Automotive industry, circular economy, international requirements, natural resources.

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Authors: Younies Mahmoud, Mai Mabrouk, Elsayed Sallam

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Analyzing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics.

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Authors: Nikola Karanovic, Aleksandar Djuric

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This paper introduces a method of calculating the quantities of construction materials and construction waste on site in city of Novi Sad. In buildings is about 40% of the total weight of materials that are in circulation in the world economic space. The best solution for this waste is to be stored at source, at the point of generation. There are several treatment options for this type of waste, reduction at source, reuse, recycling. Beside its negative effects on the environment, construction waste can be and resource. Novi Sad is divided in 16 single family resident zones and 10 multi family resident zones. For every zone of the city, quantities of used construction materials and construction waste were obtained. Rational use of natural resources is an essential factor in applying the principles of development with savings.

Keywords: Construction materials, Construction waste, Novi Sad, Recycling

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Authors: Petr Vcelak, Jana Kleckova

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Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Keywords: DASTA, De-identification, DICOM, Health Level Seven, Medical data, OCR, Personal data

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Authors: Chiung-Hui Chen

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Traditional service channel is losing its edge due to emerging service technology. To establish interaction with the clients, the service industry is using effective mechanism to give clients direct access to services with emerging technologies. Thus, as service science receives attention, special and unique consumption pattern evolves; henceforth, leading to new market mechanism and influencing attitudes toward life and consumption patterns. The market demand for customized services is thus valued due to the emphasis of personal value, and is gradually changing the demand and supply relationship in the traditional industry. In respect of interior design service, in the process of traditional interior design, a designer converts to a concrete form the concept generated from the ideas and needs dictated by a user (client), by using his/her professional knowledge and drawing tool. The final product is generated through iterations of communication and modification, which is a very time-consuming process. Although this process has been accelerated with the help of computer graphics software today, repeated discussions and confirmations with users are still required to complete the task. In consideration of what is addressed above a space user’s life model is analyzed with visualization technique to create an interaction system modeled after interior design knowledge. The space user document intuitively personal life experience in a model requirement chart, allowing a researcher to analyze interrelation between analysis documents, identify the logic and the substance of data conversion. The repeated data which is documented are then transformed into design information for reuse and sharing. A professional interior designer may sort out the correlation among user’s preference, life pattern and design specification, thus deciding the critical design elements in the process of service design.

Keywords: Information Design, Life Model-Based, Aesthetic Computing, Communication.

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Authors: Masahiro Kuzunishi, Tetsuya Furukawa, Ke Lu

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Classifying data hierarchically is an efficient approach to analyze data. Data is usually classified into multiple categories, or annotated with a set of labels. To analyze multi-labeled data, such data must be specified by giving a set of labels as a semantic range. There are some certain purposes to analyze data. This paper shows which multi-labeled data should be the target to be analyzed for those purposes, and discusses the role of a label against a set of labels by investigating the change when a label is added to the set of labels. These discussions give the methods for the advanced analysis of multi-labeled data, which are based on the role of a label against a semantic range.

Keywords: Classification Hierarchies, Data Analysis, Multilabeled Data, Orders of Sets of Labels

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Authors: Nikol Žižková

Abstract:

The aim of this study was to observe the behavior of polymer-modified cement mortars with regard to the use of a pozzolanic admixture. Polymer-modified mortars (PMMs) containing various types of waste glass (waste packing glass and fluorescent tube glass) were produced always with 20% of cement substituted with a pozzolanic-active material. Ethylene/vinyl acetate copolymer (EVA) was used for polymeric modification. The findings confirm the possibility of using the waste glass examined herein as a partial substitute for cement in the production of PMM, which contributes to the preservation of non-renewable raw material resources and to the efficiency of waste glass material reuse.

Keywords: Recycled waste glass, polymer-modified mortars, pozzolanic admixture.

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Authors: G. Candel, D. Naccache

Abstract:

t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: Concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning.

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Authors: Fatma Belghith, Hassen Loukil, Nouri Masmoudi

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This paper presents the hardware design of a unified architecture to compute the 4x4, 8x8 and 16x16 efficient twodimensional (2-D) transform for the HEVC standard. This architecture is based on fast integer transform algorithms. It is designed only with adders and shifts in order to reduce the hardware cost significantly. The goal is to ensure the maximum circuit reuse during the computing while saving 40% for the number of operations. The architecture is developed using FIFOs to compute the second dimension. The proposed hardware was implemented in VHDL. The VHDL RTL code works at 240 MHZ in an Altera Stratix III FPGA. The number of cycles in this architecture varies from 33 in 4-point- 2D-DCT to 172 when the 16-point-2D-DCT is computed. Results show frequency improvements reaching 96% when compared to an architecture described as the direct transcription of the algorithm.

Keywords: HEVC, Modified Integer Transform, FPGA.

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Authors: Woong Hee Kim, Ilhwan Park

Abstract:

Steganography is the art of hiding and transmitting data through apparently innocuous carriers in an effort to conceal the existence of the data. A lot of steganography algorithms have been proposed recently. Many of them use the digital image data as a carrier. In data hiding scheme of halftoning and coordinate projection, still image data is used as a carrier, and the data of carrier image are modified for data embedding. In this paper, we present three features for analysis of data hiding via halftoning and coordinate projection. Also, we present a classifier using the proposed three features.

Keywords: Steganography, steganalysis, digital halftoning, data hiding.

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Authors: Noura Meshaan Al-Otaibi, Amin Yousef Noaman

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Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. This research suggests the use of Service Oriented Architecture (SOA) to integrate biological data from different data sources. This work shows SOA will solve the problems that facing integration process and if the biologist scientists can access the biological data in easier way. There are several methods to implement SOA but web service is the most popular method. The Microsoft .Net Framework used to implement proposed architecture.

Keywords: Bioinformatics, Biological data, Data Integration, SOA and Web Services.

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Authors: S. Sarumathi, N. Shanthi, S. Vidhya, P. Ranjetha

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Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.

Keywords: Data Mining, STATISTICA Data Miner, Text Miner, Enterprise Server, Classification, Association, Clustering, Regression.

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Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

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In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: Communication, computer network, data collection, probe.

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Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

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Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: Data mining, fuzzy sets, linguistic summarization, patent data.

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Authors: A.Khaja Kamaluddin, B.Muhammed Yousoof

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Routing places an important role in determining the quality of service in wireless networks. The routing methods adopted in wireless networks have many drawbacks. This paper aims to review the current routing methods used in wireless networks. This paper proposes an innovative solution to overcome the problems in routing. This solution is aimed at improving the Quality of Service. This solution is different from others as it involves the resuage of the part of the virtual circuits. This improvement in quality of service is important especially in propagation of multimedia applications like video, animations etc. So it is the dire need to propose a new solution to improve the quality of service in ATM wireless networks for multimedia applications especially during this era of multimedia based applications.

Keywords: Packet buffering, Routing Table, Virtual Circuits (VC)

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Authors: S. Farokhzad, M. Reza Salehnamadi

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Grid environments include aggregation of geographical distributed resources. Grid is put forward in three types of computational, data and storage. This paper presents a research on data grid. Data grid is used for covering and securing accessibility to data from among many heterogeneous sources. Users are not worry on the place where data is located in it, provided that, they should get access to the data. Metadata is used for getting access to data in data grid. Presently, application metadata catalogue and SRB middle-ware package are used in data grids for management of metadata. At this paper, possibility of updating, streamlining and searching is provided simultaneously and rapidly through classified table of preserving metadata and conversion of each table to numerous tables. Meanwhile, with regard to the specific application, the most appropriate and best division is set and determined. Concurrency of implementation of some of requests and execution of pipeline is adaptability as a result of this technique.

Keywords: Grids, data grid, metadata, update.

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Authors: Tuong Huan Nguyen, Quoc Bao Vo, Hai L. Vu

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In this paper we propose a new traffic simulation package, TDMSim, which supports both macroscopic and microscopic simulation on free-flowing and regulated traffic systems. Both simulators are based on travel demands, which specify the numbers of vehicles departing from origins to arrive at different destinations. The microscopic simulator implements the carfollowing model given the pre-defined routes of the vehicles but also supports the rerouting of vehicles. We also propose a macroscopic simulator which is built in integration with the microscopic simulator to allow the simulation to be scaled for larger networks without sacrificing the precision achievable through the microscopic simulator. The macroscopic simulator also enables the reuse of previous simulation results when simulating traffic on the same networks at later time. Validations have been conducted to show the correctness of both simulators.

Keywords: Macroscopic, Microscopic, Simulation, Traffic, Travel demand, Fundamental diagrams.

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Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation.

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Authors: Walid K. M. Bani Salameh, Hesham Ahmad, Mohammad Al-Shannag

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In Jordan having deficit atmospheric precipitation, an increase in water demand occurs during summer months. Jordan can be regarded with a relatively high potential for wastewater recycling and reuse. The main purpose of this paper was to investigate the removal of total suspended solids (TSS) and chemical oxygen demand (COD) for olive mill wastewater (OMW) by electrocoagulation (EC) process. In the combination of electrocoagulation by using coupled iron–aluminum electrodes, the optimum working pH was found to be around 6. Results indicated that the electrocoagulation process allowed removal of TSS and COD of about 82.5% and 47.5%, respectively at 45 mA/cm2 after 70 minutes by using coupled iron–aluminum electrodes. It was demonstrated that the maximum TSS and COD removals were obtained at some optimum experimental parameters for current density, pH, and reaction time.

Keywords: Olive Mill Wastewater, Electrode, Electrocoagulation (EC), TSS, COD.

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Authors: Bhausaheb L. Pangarkar, Saroj B. Parjane, M.G. Sane

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In India, the quarrel between the budding human populace and the planet-s unchanging supply of freshwater and falling water tables has strained attention the reuse of gray water as an alternative water resource in rural development. This paper present the finest design of laboratory scale gray water treatment plant, which is a combination of natural and physical operations such as primary settling with cascaded water flow, aeration, agitation and filtration, hence called as hybrid treatment process. The economical performance of the plant for treatment of bathrooms, basins and laundries gray water showed in terms of deduction competency of water pollutants such as COD (83%), TDS (70%), TSS (83%), total hardness (50%), oil and grease (97%), anions (46%) and cations (49%). Hence, this technology could be a good alternative to treat gray water in residential rural area.

Keywords: Gray water treatment plant, gray water, naturaltechnology, pollutant.

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Authors: S. Dhib, S. A. Addouche, T. Loukil, A. Elmhamedi

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In this paper, a reverse supply chain network is investigated for a decision making. This decision is surrounded by complex flows of returned products, due to the increasing quantity, the type of returned products and the variety of recovery option products (reuse, recycling, and refurbishment). The most important problem in the reverse logistic network (RLN) is to orient returned products to the suitable type of recovery option. However, returned products orientations from collect sources to the recovery disposition have not well considered in performance model. In this study, we propose a performance model for designing a network configuration on reverse logistics. Conceptual and analytical models are developed with taking into account operational, economic and environmental factors on designing network.

Keywords: Reverse logistics, Network design, Performance model, Open loop configuration.

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Authors: Fahad Shahbaz Khan, Rao Muhammad Anwer, Olof Torgersson

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The vast amount of information hidden in huge databases has created tremendous interests in the field of data mining. This paper examines the possibility of using data clustering techniques in oral medicine to identify functional relationships between different attributes and classification of similar patient examinations. Commonly used data clustering algorithms have been reviewed and as a result several interesting results have been gathered.

Keywords: Oral Medicine, Cluto, Data Clustering, Data Mining.

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Authors: Kunwar D. Yadav, Dayanand Sharma

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Surat City in India is famous for textile and dyeing industries which generate textile sludge in huge quantity. Textile sludge contains harmful chemicals which are poisonous and carcinogenic. The safe disposal and reuse of textile dyeing sludge are challenging for owner of textile industries and government of the state. The aim of present study was the vermicomposting of textile industries dyeing sludge with cow dung and Eisenia foetida as earthworm spices. The vermicompost reactor of 0.3 m³ capacity was used for vermicomposting. Textile dyeing sludge was mixed with cow dung in different proportion, i.e., 0:100 (C1), 10:90 (C2), 20:80 (C3), 30:70 (C4). Vermicomposting duration was 120 days. All the combinations of the feed mixture, the pH was increased to a range 7.45-7.78, percentage of total organic carbon was decreased to a range of 31-33.3%, total nitrogen was decreased to a range of 1.15-1.32%, total phosphorus was increased in the range of 6.2-7.9 (g/kg).

Keywords: Cow dung, Eisenia foetida, textile sludge, vermicompost.

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: Data mining, data analysis, prediction, optimization, building operational performance.

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