Search results for: low data rate

Authors: S. Chikh, S. Boulifa

Abstract:

The present study addresses the problem of ammonia evaporation during filling of a vertical cylindrical tank and the influence of various external factors on the stability of storage by determining the conditions for minimum evaporation. Numerical simulation is carried out by solving the governing equations namely, continuity, momentum, energy, and diffusion of species. The effect of temperature of surrounding air, the filling speed of the reservoir and the temperature of the filling liquid ammonia on the evaporation rate is investigated. Results show that the temperature of the filling liquid has little effect on the liquid ammonia for a short period, which, in fact, is function of the filling speed. The evaporation rate along the free surface of the liquid is non-uniform. The inlet temperature affects the vapor ammonia temperature because of pressure increase. The temperature of the surrounding air affects the temperature of the vapor phase rather than the liquid phase. The maximum of evaporation is reached at the final step of filling. In order to minimize loss of ammonia vapors automatically causing losses in quantity of the liquid stored, it is suggested to ensure the proper insulation for the walls and roof of the reservoir and to increase the filling speed.

Keywords: Evaporation, liquid ammonia, storage tank, numerical simulation.

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Authors: Hina Kausher, Sangita Srivastava

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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

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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: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: Early stage prediction, heart rate variability, linear and non linear analysis, sudden cardiac death.

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Authors: T. Motsima

Abstract:

The under-5 mortality rate is high in sub-Saharan Africa with Lesotho being amongst the highest under-5 mortality rates in the world. The objective of the study is to determine the factors associated with under-5 mortality in Lesotho. The data used for this analysis come from the nationally representative household survey called the 2009 Lesotho Demographic and Health Survey. Odds ratios produced by the logistic regression models were used to measure the effect of each independent variable on the dependent variable. Female children were significantly 38% less likely to die than male children. Children who were breastfed for 13 to 18 months and those who were breastfed for more than 19 months were significantly less likely to die than those who were breastfed for 12 months or less. Furthermore, children of mothers who stayed in Quthing, Qacha’s Nek and Thaba Tseka ran the greatest risk of dying. The results suggested that: sex of child, type of birth, breastfeeding duration, district, source of energy and marital status were significant predictors of under-5 mortality, after correcting for all variables.

Keywords: Under-5 mortality, risk factors, millennium development goals, breastfeeding, logistic regression.

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Authors: Maurizio Mastroianni, Lou Savoni, Paul Henshaw, Gary W. Rankin

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The refueling of a transparent rectangular fuel tank fitted with a standard filler pipe and roll-over valve was experimentally studied. A fuel-conditioning cart, capable of handling fuels of different Reid vapor pressure at a constant temperature, was used to dispense fuel at the desired rate. The experimental protocol included transient recording of the tank and filler tube pressures while video recording the flow patterns in the filler tube and tank during the refueling process. This information was used to determine the effect of changes in the vent tube diameter, fuel-dispense flow rate and fuel Reid vapor pressure on the pressure-time characteristics and the occurrence of premature fuel filling shut-off and fuel spill-back. Pressure-time curves for the case of normal shut-off demonstrated the classic, three-phase characteristic noted in the literature. The variation of the maximum values of tank dome and filler tube pressures are analyzed in relation to the occurrence of premature shut-off.

Keywords: experimental study, fuel tank filling, premature shutoff, spill-back

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Authors: Jean François Chatelain, Imed Zaghbani, Joseph Monier

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The machining of Carbon Fiber Reinforced Plastics has come to constitute a significant challenge for many fields of industry. The resulting surface finish of machined parts is of primary concern for several reasons, including contact quality and impact on the assembly. Therefore, the characterization and prediction of roughness based on machining parameters are crucial for costeffective operations. In this study, a PCD tool comprised of two straight flutes was used to trim 32-ply carbon fiber laminates in a bid to analyze the effects of the feed rate and the cutting speed on the surface roughness. The results show that while the speed has but a slight impact on the surface finish, the feed rate for its part affects it strongly. A detailed study was also conducted on the effect of fiber orientation on surface roughness, for quasi-isotropic laminates used in aerospace. The resulting roughness profiles for the four-ply orientation lay-up were compared, and it was found that fiber angle is a critical parameter relating to surface roughness. One of the four orientations studied led to very poor surface finishes, and characteristic roughness profiles were identified and found to only relate to the ply orientations of multilayer carbon fiber laminates.

Keywords: Roughness, Detouring, Composites, Aerospace

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

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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: Jiayue Zhao, Hongjuan Wu, Guiwen Liu

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Old neighborhoods with a large elderly population depend on community-based elderly care facilities (community-based ECFs) for aging-in-place. Yet, due to scarce and scattered land, the facilities face inequitable distribution. This research uses spatial equity theory for measuring the spatial equity of community-based ECFs in old neighborhoods. Field surveys gather granular data and methods including coverage rate, Gini coefficient, Lorenz curve and G2SFCA. The findings showed that coverage is substantial but does not indicate supply is matching to demand, nor does it imply superior accessibility. The key contributions are that structuring spatial equity framework considering elderly residents’ travel behavior. This study dedicated to the international literature on spatial equity from the perspective of travel behavior and could provide valuable suggestions for the urban planning of old neighborhoods.

Keywords: Community-based ECFs, elderly residents’ travel behavior, old neighborhoods, spatial equity.

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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: Md. Z. Alam, Devi R. Asih, Md. N. Salleh

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Immobilization of lipase enzyme produced from palm oil mill effluent (POME) by the activated carbon (AC) among the low cost support materials was optimized. The results indicated that immobilization of 94% was achieved by AC as the most suitable support material. A sequential optimization strategy based on a statistical experimental design, including one-factor-at-a-time (OFAT) method was used to determine the equilibrium time. Three components influencing lipase immobilization were optimized by the response surface methodology (RSM) based on the face-centered central composite design (FCCCD). On the statistical analysis of the results, the optimum enzyme concentration loading, agitation rate and carbon active dosage were found to be 30 U/ml, 300 rpm and 8 g/L respectively, with a maximum immobilization activity of 3732.9 U/g-AC after 2 hrs of immobilization. Analysis of variance (ANOVA) showed a high regression coefficient (R²) of 0.999, which indicated a satisfactory fit of the model with the experimental data. The parameters were statistically significant at p<0.05.

Keywords: Activated carbon, adsorption, immobilization, POME based lipase.

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Authors: Chng Pei Eng, Boon Yih Mah, Chng Pei Cheng

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In this cyber age, the job market has been rapidly transforming and being digitalized. Submitting a paper-based curriculum vitae (CV) nowadays does not grant a job seeker a high employability rate. This paper calls for attention on the creation of mobile Curriculum Vitae or m-CV (http://mcurriculumvitae. blogspot.com), a sample of an individual CV developed using weblog, which can enhance the job hunter especially fresh graduate-s higher marketability rate. This study is designed to identify the perceptions held by Malaysian university students regarding m-CV grounded on a modified Technology Acceptance Model (TAM). It measures the strength and the direction of relationships among three major variables – Perceived Ease of Use (PEOU), Perceived Usefulness (PU) and Behavioral Intention (BI) to use. The finding shows that university students generally accepted adopting m-CV since they perceived m-CV to be more useful rather than easy to use. Additionally, this study has confirmed TAM to be a useful theoretical model in helping to understand and explain the behavioral intention to use Web 2.0 application-weblog publishing their CV. The result of the study has underlined another significant positive value of using weblog to create personal CV. Further research of m-CV has been highlighted in this paper.

Keywords: CV, mobile curriculum vitae, Technology Acceptance Model, weblog

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

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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: I. U. Wickramasinghe, D. J. Hargreaves, D. V. De Pellegrin

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This paper presents a strategy to predict the lifetime of rails subjected to large rolling contact loads that induce ratchetting strains in the rail head. A critical element concept is used to calculate the number of loading cycles needed for crack initiation to occur in the rail head surface. In this technique the finite element method (FEM) is used to determine the maximum equivalent ratchetting strain per load cycle, which is calculated by combining longitudinal and shear stains in the critical element. This technique builds on a previously developed critical plane concept that has been used to calculate the number of cycles to crack initiation in rolling contact fatigue under ratchetting failure conditions. The critical element concept simplifies the analytical difficulties of critical plane analysis. Finite element analysis (FEA) is used to identify the critical element in the mesh, and then the strain values of the critical element are used to calculate the ratchetting rate analytically. Finally, a ratchetting criterion is used to calculate the number of cycles to crack initiation from the ratchetting rate calculated.

Keywords: Critical element analysis, finite element modeling (FEM), wheel/rail contact.

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Authors: C. Kalamani, K. Paramasivam

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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: 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: Nahid-Al-Masood, Jubaer Ahmed, Amina Hasan Abedin, S. R. Deeba, Faeza Hafiz, Mahmuda Begum

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An electric utility-s main concern is to plan, design, operate and maintain its power supply to provide an acceptable level of reliability to its users. This clearly requires that standards of reliability be specified and used in all three sectors of the power system, i.e., generation, transmission and distribution. That is why reliability of a power system is always a major concern to power system planners. This paper presents the reliability analysis of Bangladesh Power System (BPS). Reliability index, loss of load probability (LOLP) of BPS is evaluated using recursive algorithm and considering no de-rated states of generators. BPS has sixty one generators and a total installed capacity of 5275 MW. The maximum demand of BPS is about 5000 MW. The relevant data of the generators and hourly load profiles are collected from the National Load Dispatch Center (NLDC) of Bangladesh and reliability index 'LOLP' is assessed for the period of last ten years.

Keywords: Recursive algorithm, LOLP, forced outage rate, cumulative probability.

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Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson

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This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.

Keywords: Capacity randomness, flow breakdown, freeway capacity, rainfall.

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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: Zainoldin, K.H., Baba, A.S.

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Yogurt is a coagulated milk product obtained from the lactic acid fermentation by the action of Lactobacillus bulgaricus and Streptococcus thermophilus. The additions of fruits into milk may enhance the taste and the therapeutical values of milk products. However fruits also may change the fermentation behaviour. In this present study, the changes in physicochemical, the peptide concentration, total phenolics content and the antioxidant potential of yogurt upon the addition of Hylocereus polyrhizus and Hylocereus undatus (white and red dragon fruit) were investigated. Fruits enriched yogurt (10%, 20%, 30% w/w) were prepared and the pH, TTA, syneresis measurement, peptide concentration, total phenolics content and DPPH antioxidant inhibition percentage were determined. Milk fermentation rate was enhanced in red dragon fruit yogurt for all doses (-0.3606 - -0.4126 pH/h) while only white dragon fruit yogurt with 20% and 30% (w/w) composition showed increment in fermentation rate (-0.3471 - -0.3609 pH/h) compared to plain yogurt (-0.3369pH/h). All dragon fruit enriched yogurts generally showed lower pH readings (pH 3.95 - 4.03) compared to plain yogurt (pH 4.05). Both fruit yogurts showed a higher lactic acid percentage (1.14-1.23%) compared to plain yogurt (1.08%). Significantly higher syneresis percentage (57.19 - 70.32%) compared to plain yogurt (52.93%) were seen in all fruit enriched yogurts. The antioxidant activity of plain yogurt (19.16%) was enhanced by the presence of white and red dragon fruit (24.97- 45.74%). All fruit enriched yogurt showed an increment in total phenolic content (36.44 - 64.43mg/ml) compared to plain yogurt (20.25mg/ml). However, the addition of white and red dragon fruit did not enhance the proteolysis of milk during fermentation. Therefore, it could be concluded that the addition of white and red dragon fruit into yogurt enhanced the milk fermentation rate, lactic acid content, syneresis percentage, antioxidant activity, and total phenolics content in yogurt.

Keywords: Antioxidant activity, Hylocereus polyrhizus, Hylocereus undatus, yogurt

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Authors: Alexander Y. Vaninsky

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Environmental performance of the U.S. States is investigated for the period of 1990 – 2007 using Stochastic Frontier Analysis (SFA). The SFA accounts for both efficiency measure and stochastic noise affecting a frontier. The frontier is formed using indicators of GDP, energy consumption, population, and CO2 emissions. For comparability, all indicators are expressed as ratios to total. Statistical information of the Energy Information Agency of the United States is used. Obtained results reveal the bell - shaped dynamics of environmental efficiency scores. The average efficiency scores rise from 97.6% in 1990 to 99.6% in 1999, and then fall to 98.4% in 2007. The main factor is insufficient decrease in the rate of growth of CO2 emissions with regards to the growth of GDP, population and energy consumption. Data for 2008 following the research period allow for an assumption that the environmental performance of the U.S. States has improved in the last years.

Keywords: Stochastic frontier analysis, environmental performance, interstate comparisons.

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Authors: A. Seleem, M. Mortada, M. El Morsi, M. Younan

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Diffusion stills have been effective in water desalination. The present work represents a model of the distillation process by using vertical single-effect diffusion stills. A semianalytical model has been developed to model the process. A software computer code using Engineering Equation Solver EES software has been developed to solve the equations of the developed model. An experimental setup has been constructed, and used for the validation of the model. The model is also validated against former literature results. The results obtained from the present experimental test rig, and the data from the literature, have been compared with the results of the code to find its best range of validity. In addition, a parametric analysis of the system has been developed using the model to determine the effect of operating conditions on the system's performance. The dominant parameters that affect the productivity of the still are the hot plate temperature that ranges from (55- 90°C) and feed flow rate in range of (0.00694-0.0211 kg/m2-s).

Keywords: Analytical Model, Solar Distillation, Sustainable Water Systems, Vertical Diffusion Still.

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an  enormous number of applications, cyber-threats have significantly  increased accordingly. Thus, accurate detection of malicious traffic in  a timely manner is a critical concern in today’s Internet for security.  One approach for intrusion detection is to use Machine Learning (ML)  techniques. Several methods based on ML algorithms have been  introduced over the past years, but they are largely limited in terms of  detection accuracy and/or time and space complexity to run. In this  work, we present a novel method for intrusion detection that  incorporates a set of supervised learning algorithms. The proposed  technique provides high accuracy and outperforms existing techniques  that simply utilizes a single learning method. In addition, our  technique relies on partial flow information (rather than full  information) for detection, and thus, it is light-weight and desirable for  online operations with the property of early identification. With the  mid-Atlantic CCDC intrusion dataset publicly available, we show that  our proposed technique yields a high degree of detection rate over 99%  with a very low false alarm rate (0.4%). 

 

Keywords: Intrusion Detection, Supervised Learning, Traffic Classification.

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Authors: Mahmoud A. Rabah

Abstract:

The present study shows a method to recover lead metal from wastewater of wet scrubber in secondary lead smelter. The wastewater is loaded with 42,000 ppm of insoluble lead compounds (TSP) submicron in diameter. The technical background benefits the use of cationic polyfloc solution to flocculate these colloidal solids before press filtration. The polymer solution is injected in the wastewater stream in a countercurrent flow design. The study demonstrates the effect of polymer dose, temperature, pH, flow velocity of the wastewater and different filtration media on the filtration extent. Results indicated that filtration rate (¦_r), quality of purified water, purifying efficiency (¦_e) and floc diameter decrease regularly with increase in mass flow rate and velocity up to turbulence of 0.5 m.sec^-1. Laminar flow is in favor of flocculation. Polyfloc concentration of 0.75 – 1.25 g/m³ wastewater is convenient. Increasing temperature of the wastewater and pneumatic pressure of filtration enhances ¦_r. High pH value deforms floc formation and assists degradation of the filtration fabric. The overall efficiency of the method amounts to 93.2 %. Lead metal was recovered from the filtrate cake using carbon as a reducing agent at 900°C.

Keywords: Wastewater, wet scrubbers, filtration, secondary lead.

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Authors: M. Mazraehli, F. Mehrabani, S. Zare

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In general, mechanical and hydraulic processes are not independent of each other in jointed rock masses. Therefore, the study on hydro-mechanical coupling of geomaterials should be a center of attention in rock mechanics. Rocks in their nature contain discontinuities whose presence extremely influences mechanical and hydraulic characteristics of the medium. Assuming this effect, experimental investigations on intact rock cannot help to identify jointed rock mass behavior. Hence, numerical methods are being used for this purpose. In this paper, water inflow into a tunnel under significant water table has been estimated using hydro-mechanical discrete element method (HM-DEM). Besides, effects of geomechanical and geometrical parameters including constitutive model, friction angle, joint spacing, dip of joint sets, and stress factor on the estimated inflow rate have been studied. Results demonstrate that inflow rates are not identical for different constitutive models. Also, inflow rate reduces with increased spacing and stress factor.

Keywords: Distinct element method, fluid flow, hydro-mechanical coupling, jointed rock mass, underground excavations.

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Authors: Zhang Yan, Yu Bin

Abstract:

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

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

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Authors: Bala Dhandayuthapani Veerasamy

Abstract:

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

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

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