Search results for: Usage performance of information systems

Authors: Thomas Klauß

Abstract:

In networks, mainly small and medium-sized businesses benefit from the knowledge, experiences and solutions offered by experts from industry and science or from the exchange with practitioners. Associations which focus, among other things, on networking, information and knowledge transfer and which are interested in supporting such cooperations are especially well suited to provide such networks and the appropriate web platforms. Using METORA as an example – a project developed and run by the Federal Association for Information Economy, Telecommunications and New Media e.V. (BITKOM) for the Federal Ministry of Economics and Technology (BMWi) – This paper will discuss how associations and other network organizations can achieve this task and what conditions they have to consider.

Keywords: Associations, collaboration, communities, crossdepartmental organizations, semantic web, web 2.0.

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Authors: Eunil Park, Kwangsu Cho

Abstract:

The wireless link can be unreliable in realistic wireless sensor networks (WSNs). Energy efficient and reliable data forwarding is important because each node has limited resources. Therefore, we must suggest an optimal solution that considers using the information of the node-s characteristics. Previous routing protocols were unsuited to realistic asymmetric WSNs. In this paper, we propose a Protocol that considers Both sides of Link-quality and Energy (PBLE), an optimal routing protocol that balances modified link-quality, distance and energy. Additionally, we propose a node scheduling method. PBLE achieves a longer lifetime than previous routing protocols and is more energy-efficient. PBLE uses energy, local information and both sides of PRR in a 1-hop distance. We explain how to send data packets to the destination node using the node's information. Simulation shows PBLE improves delivery rate and network lifetime compared to previous schemes. Moreover, we show the improvement in various WSN environments.

Keywords: energy-efficient, lifetime, PBLE, unreliable

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Authors: Z. Ezzouine, A. Nakheli

Abstract:

This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: Electromagnetic sensor, data acquisition, accurately, position measurement.

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Authors: Md. Asif Jahangir Chowdhury, Md. Shahriar Rizwan, M. S. Islam

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In CMOS integrated circuit design there is a trade-off between static power consumption and technology scaling. Recently, the power density has increased due to combination of higher clock speeds, greater functional integration, and smaller process geometries. As a result static power consumption is becoming more dominant. This is a challenge for the circuit designers. However, the designers do have a few methods which they can use to reduce this static power consumption. But all of these methods have some drawbacks. In order to achieve lower static power consumption, one has to sacrifice design area and circuit performance. In this paper, we propose a new method to reduce static power in the CMOS VLSI circuit using Variable Body Biasing technique without being penalized in area requirement and circuit performance.

Keywords: variable body biasing, state saving technique, stack effect, dual V-th, static power reduction.

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Authors: Abbas Haddadzadeh, Marzieh Sharif Paghaleh

Abstract:

Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.

Keywords: Crisis, HR System, Resilience, Strategic Human Resource Management.

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Authors: YuLung Wu

Abstract:

In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. Teachers can operate the proposed system and obtain the information of specific students without any computer science background. The teachers can find out failed students in advance and provide remedial learning resources.

Keywords: Knowledge Structure Graph, On-line LearningDiagnosis

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Authors: Byung-Ju Kim, Jong-Jin Shin, Hwa-Jin Nam, Jin-Soo Kim

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Skyline extraction in mountainous images can be used for navigation of vehicles or UAV(unmanned air vehicles), but it is very hard to extract skyline shape because of clutters like clouds, sea lines and field borders in images. We developed the edge-based skyline extraction algorithm using a proposed multistage edge filtering (MEF) technique. In this method, characteristics of clutters in the image are first defined and then the lines classified as clutters are eliminated by stages using the proposed MEF technique. After this processing, we select the last line using skyline measures among the remained lines. This proposed algorithm is robust under severe environments with clutters and has even good performance for infrared sensor images with a low resolution. We tested this proposed algorithm for images obtained in the field by an infrared camera and confirmed that the proposed algorithm produced a better performance and faster processing time than conventional algorithms.

Keywords: MEF, mountainous image, navigation, skyline

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: Product recommender system, Ensemble technique, Association rules, Decision tree, Artificial neural networks.

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Authors: A. Páchová

Abstract:

Working memory (WM) can be defined as the system which actively holds information in the mind to do tasks in spite of the distraction. Contrary, short-term memory (STM) is a system that represents the capacity for the active storing of information without distraction. There has been accumulating evidence that these types of memory are related to higher cognition (HC). The aim of this study was to verify the relationship between HC and memory (visual STM and WM, auditory STM and WM). 59 primary school children were tested by intelligence test, mathematical tasks (HC) and memory subtests. We have shown that visual but not auditory memory is a significant predictor of higher cognition. The relevance of these results are discussed.

Keywords: higher cognition, long-term memory, short-term memory, working memory

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Authors: Christina G. Siontorou

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This paper presents an integrated knowledge-based approach to multi-scale modeling of aquatic systems, with a view to enhancing predictive power and aiding environmental management and policy-making. The basic phases of this approach have been exemplified in the case of a bay in Saronicos Gulf (Attiki, Greece). The results showed a significant problem with rising phytoplankton blooms linked to excessive microbial growth, arisen mostly due to increased nitrogen inflows; therefore, the nitrification/denitrification processes of the benthic and water column sub-systems have provided the quality variables to be monitored for assessing environmental status. It is thereby demonstrated that the proposed approach facilitates modeling choices and implementation option decisions, while it provides substantial support for knowledge and experience capitalization in long-term water management.

Keywords: Aquatic ecosystem, integrated modeling, multi-scale modeling, ontological platform.

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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The problems arising from unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many researchers have found that the performance of existing classifiers tends to be biased towards the majority class. The k-nearest neighbors’ nonparametric discriminant analysis is a method that was proposed for classifying unbalanced classes with good performance. In this study, the methods of discriminant analysis are of interest in investigating misclassification error rates for classimbalanced data of three diabetes risk groups. The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification of class-imbalanced data of diabetes risk groups. Data from a project maintaining healthy conditions for 599 employees of a government hospital in Bangkok were obtained for the classification problem. The employees were divided into three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data including the variables of diabetes risk group, age, gender, blood glucose, and BMI were analyzed and bootstrapped for 50 and 100 samples, 599 observations per sample, for additional estimation of the misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples showed nonnormality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. Searching the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10) and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k=3 or k=4 and the defined prior probabilities of non-risk: risk: diabetic as 0.90: 0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of misclassification. The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: Bootstrap, diabetes risk groups, error rate, k-nearest neighbors.

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Authors: H. Shareef, A. Mohamed, S. A. Khalid, Aziah Khamis

Abstract:

This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation. 

Keywords: Artificial intelligence, Power tracing, Artificial neural network, ANFIS, Power system deregulation.

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Authors: M. Sadeghzadeh, M. Teshnehlab

Abstract:

Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant colony optimization, Classification, Datamining, Feature selection.

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Authors: Paulo R. M. de Andrade, Adriano B. Albuquerque, Otávio F. Frota, Robson V. Silveira, Fátima A. da Silva

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Information technology has been gaining more and more space whether in industry, commerce or even for personal use, but the misuse of it brings harm to the environment and human health as a result. Contribute to the sustainability of the planet is to compensate the environment, all or part of what withdraws it. The green computing also came to propose practical for use in IT in an environmentally correct way in aid of strategic management and communication. This work focuses on showing how a mobile application can help businesses reduce costs and reduced environmental impacts caused by its processes, through a case study of a public company in Brazil.

Keywords: E-government, green computing, information technology, mobile computing, sustainable development.

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Authors: M. Ionascu, L. Olimid

Abstract:

In the last few years, several steps were taken in order to improve the quality of corporate governance for Romanian listed companies. Higher standards of corporate governance is documented in the literature to lead to a better information environment, and, consequently, to increase analysts forecast accuracy. Accordingly, the purpose of this paper is to investigate the extent to which corporate governance policies affect analysts forecasts for companies listed on Bucharest Stock Exchange. The results showed that there is indeed a negative correlation between a corporate governance index – used as a proxy for the quality of corporate governance practices - and analysts forecast errors.

Keywords: corporate governance, aanalysts' forecasts, information environment

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Authors: Maassoumeh Javadi Baygi, Abdul Rahman B Ramli, Borhanuddin Mohd Ali, Syamsiah Mashohor

Abstract:

The expectation of network performance from the early days of ARPANET until now has been changed significantly. Every day, new advancement in technological infrastructure opens the doors for better quality of service and accordingly level of perceived quality of network services have been increased over the time. Nowadays for many applications, late information has no value or even may result in financial or catastrophic loss, on the other hand, demands for some level of guarantee in providing and maintaining quality of service are ever increasing. Based on this history, having a QoS aware routing system which is able to provide today's required level of quality of service in the networks and effectively adapt to the future needs, seems as a key requirement for future Internet. In this work we have extended the traditional AntNet routing system to support QoS with multiple metrics such as bandwidth and delay which is named Q-Net. This novel scalable QoS routing system aims to provide different types of services in the network simultaneously. Each type of service can be provided for a period of time in the network and network nodes do not need to have any previous knowledge about it. When a type of quality of service is requested, Q-Net will allocate required resources for the service and will guarantee QoS requirement of the service, based on target objectives.

Keywords: Quality of Service, Routing, Ant Colony Optimization, Ant-based algorithms.

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Authors: Habibollah Javanmard

Abstract:

In order to reduce cost, increase quality, and for timely supplying production systems has considerably taken the advantages of supply chain management and these advantages are also competitive. Selection of appropriate supplier has an important role in improvement and efficiency of systems. The models of supplier selection which have already been used by researchers have considered selection one or more suppliers from potential suppliers but in this paper selecting one supplier as partner from one supplier that have minimum one period supplying to buyer is considered. This paper presents a conceptual model for partner selection and application of Degree of Adoptive (DOA) model for final selection. The attributes weight in this model is prepared through AHP model. After making the descriptive model, determining the attributes and measuring the parameters of the adaptive is examined in an auto industry of Iran(Zagross Khodro co.) and results are presented.

Keywords: Partnership, Degree of Adaptive, AHP, SupplyChain.

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Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem

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Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic ABSA approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Keywords: Sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity.

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Authors: B. M. Manjunatha, D. V. Ashok Kumar, M. Vijay Kumar

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This paper proposes five level diode clamped Z source Inverter. The existing PWM techniques used for ZSI are restricted for two level. The two level Z Source Inverter have high harmonic distortions which effects the performance of the grid connected PV system. To improve the performance of the system the number of voltage levels in the output waveform need to be increased. This paper presents comparative analysis of a five level diode clamped Z source Inverter with different carrier based Modified Pulse Width Modulation techniques. The parameters considered for comparison are output voltage, voltage gain, voltage stress across switch and total harmonic distortion when powered by same DC supply. Analytical results are verified using MATLAB.

Keywords: Diode Clamped, Pulse Width Modulation, total harmonic distortion, Z Source Inverter.

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Authors: G. Van Dijck, M. M. Van Hulle, M. Wevers

Abstract:

A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated according to the classification performance. Features derived from the continuous wavelet transform are potentially strongly correlated. GA-s that do not take the correlation structure of features into account are inefficient. The proposed algorithm forms clusters of correlated features and searches for a good candidate set of clusters. Secondly a search within the clusters is performed. Different simulations of the algorithm on a real-case data set with strong correlations between features show the increased classification performance. Comparison is performed with a standard GA without use of the correlation structure.

Keywords: Classification, genetic algorithm, hierarchicalagglomerative clustering, wavelet transform.

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Authors: N. Mahendran, R. Madhuranthi

Abstract:

Wireless sensor networks (WSNs), are constantly in demand to process information more rapidly with less energy and area cost. Presently, processor based solutions have difficult to achieve high processing speed with low-power consumption. This paper presents a simple and accurate data processing scheme for low power wireless sensor node, based on reduced number of processing element (PE). The presented model provides a simple recursive structure (SRS) to process the sampled data in the wireless sensor environment and to reduce the power consumption in wireless sensor node. Based on this model, to process the incoming samples and produce a smaller amount of data sufficient to reconstruct the original signal. The ModelSim simulator used to simulate SRS structure. Functional simulation is carried out for the validation of the presented architecture. Xilinx Power Estimator (XPE) tool is used to measure the power consumption. The experimental results show the average power consumption of 91 mW; this is 42% improvement compared to the folded tree architecture.

Keywords: Power consumption, energy efficiency, low power WSN node, recursive structure, sleep/wake scheduling.

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Authors: I. Erins, J. Erina

Abstract:

The aim of the present article is to determine the impact of the external and internal factors of bank performance on the profitability indicators of the CEE countries banks in the period from 2006 to 2012. On the basis of research conducted abroad on bank and macroeconomic profitability indicators, in order to obtain research results, the authors evaluated return on average assets (ROAA) and return on average equity (ROAE) indicators of the CEE countries banks. The authors analyzed profitability indicators of banks using descriptive methods, SPSS data analysis methods, as well as data correlation and linear regression analysis. The authors concluded that most internal and external indicators of bank performance have no direct influence the profitability of the banks in the CEE countries. The only exceptions are credit risk and bank size, which affect one of the measures of bank profitability – return on average equity.

Keywords: Banks, CEE countries, Profitability ROAA, ROAE.

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Authors: Gugyong Kim, Sugnsu Kang, Yongjun Lee, Sooncheol Park, Wonwook Jung

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When cars are released from the factory, strut noises are very small and therefore it is difficult to perceive them. As the use time and travel distance increase, however, strut noises get larger so as to cause users much uneasiness. The noises generated at the field include engine noises and flow noises and therefore it is difficult to clearly discern the noises generated from struts. This study developed a test method which can reproduce field strut noises in the lab. Using the newly developed noise evaluation test, this study analyzed the effects that insulator performance degradation and failure can have on car noises. The study also confirmed that the insulator durability test by the simple back-and-forth motion cannot completely reflect the state of the parts failure in the field. Based on this, the study also confirmed that field noises can be reproduced through a durability test that considers heat aging.

Keywords: Insulator, noise, performance degradation, strut

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Authors: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar

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This paper presents the problem of modeling and simulating of transient phenomena in conveying pipeline systems based on the rigid column and full elastic methods. Transient analysis is important and one of the more challenging and complicated flow problem in the design and the operation of water pipeline systems. Transient can produce large pressure forces and rapid fluid acceleration into a water pipeline system, these disturbances may result in device failures, system fatigue or pipe ruptures, and even the dirty water intrusion. Several methods have been introduced and used to analyze transient flow, an accurate analysis and suitable protection devices should be used to protect water pipeline systems. The fourth-order Runge-Kutta method has been used to solve the dynamic and continuity equations in the rigid column method, while the characteristics method used to solve these equations in the full elastic method. The results obtained provide that the model is an efficient tool for flow transient analysis and provide approximately identical results by using these two methods. Moreover; using the simple surge tank ”open surge tank” reduces the unfavorable effects of transients.

Keywords: Elastic method, Flow transient, Open surge tank, Pipeline, Protection devices, Numerical model, Rigid column method.

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Authors: J. Siame, H. Kasaini

Abstract:

The proof of concept experiments were conducted to determine the feasibility of using small amounts of Dissolved Sulphur (DS) from the gaseous phase to precipitate platinum ions in chloride media. Two sets of precipitation experiments were performed in which the source of sulphur atoms was either a thiosulphate solution (Na2S2O3) or a sulphur dioxide gas (SO2). In liquid-liquid (L-L) system, complete precipitation of Pt was achieved at small dosages of Na2S2O3 (0.01 – 1.0 M) in a time interval of 3-5 minutes. On the basis of this result, gas absorption tests were carried out mainly to achieve sulphur solubility equivalent to 0.018 M. The idea that huge amounts of precious metals could be recovered selectively from their dilute solutions by utilizing the waste SO2 streams at low pressure seemed attractive from the economic and environmental point of views. Therefore, mass transfer characteristics of SO2 gas associated with reactive absorption across the gas-liquid (G-L) interface were evaluated under different conditions of pressure (0.5 – 2 bar), solution temperature ranges from 20 – 50 oC and acid strength (1 – 4 M, HCl). This paper concludes with information about selective precipitation of Pt in the presence of cations (Fe2+, Co2+, and Cr3+) in a CSTR and recommendation to scale up laboratory data to industrial pilot scale operations.

Keywords: CSTR, diffusivity, platinum, selective precipitation, sulphur dioxide, thiosulphate.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

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Email has become a fast and cheap means of online communication. The main threat to email is Unsolicited Bulk Email (UBE), commonly called spam email. The current work aims at identification of unigrams in more than 2700 UBE that advertise body-enhancement drugs. The identification is based on the requirement that the unigram is neither present in dictionary, nor is a slang term. The motives of the paper are many fold. This is an attempt to analyze spamming behaviour and employment of wordmutation technique. On the side-lines of the paper, we have attempted to better understand the spam, the slang and their interplay. The problem has been addressed by employing Tokenization technique and Unigram BOW model. We found that the non-lexicon words constitute nearly 66% of total number of lexis of corpus whereas non-slang words constitute nearly 2.4% of non-lexicon words. Further, non-lexicon non-slang unigrams composed of 2 lexicon words, form more than 71% of the total number of such unigrams. To the best of our knowledge, this is the first attempt to analyze usage of non-lexicon non-slang unigrams in any kind of UBE.

Keywords: Body Enhancement, Lexicon, Medicinal, Slang, Unigram, Unsolicited Bulk e-mail (UBE)

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Authors: A. Kablan

Abstract:

The prediction of financial time series is a very complicated process. If the efficient market hypothesis holds, then the predictability of most financial time series would be a rather controversial issue, due to the fact that the current price contains already all available information in the market. This paper extends the Adaptive Neuro Fuzzy Inference System for High Frequency Trading which is an expert system that is capable of using fuzzy reasoning combined with the pattern recognition capability of neural networks to be used in financial forecasting and trading in high frequency. However, in order to eliminate unnecessary input in the training phase a new event based volatility model was proposed. Taking volatility and the scaling laws of financial time series into consideration has brought about the development of the Intraday Seasonality Observation Model. This new model allows the observation of specific events and seasonalities in data and subsequently removes any unnecessary data. This new event based volatility model provides the ANFIS system with more accurate input and has increased the overall performance of the system.

Keywords: Adaptive Neuro-fuzzy Inference system, High Frequency Trading, Intraday Seasonality Observation Model.

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Authors: Chuan Li, Ming Liang, Qibing Yu

Abstract:

To improve the dynamics response of the vehicle passive suspension, a two-terminal mass is suggested to connect in parallel with the suspension strut. Three performance criteria, tire grip, ride comfort and suspension deflection, are taken into consideration to optimize the suspension parameters. However, the three criteria are conflicting and non-commensurable. For this reason, the Chebyshev goal programming method is applied to find the best tradeoff among the three objectives. A simulation case is presented to describe the multi-objective optimization procedure. For comparison, the Chebyshev method is also employed to optimize the design of a conventional passive suspension. The effectiveness of the proposed design method has been clearly demonstrated by the result. It is also shown that the suspension with a two-terminal mass in parallel has better performance in terms of the three objectives.

Keywords: Vehicle, passive suspension, two-terminal mass, optimization, Chebyshev goal programming

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Authors: A. Ghaffari, A. S. Mostafavi

Abstract:

Complex assemblies of interacting proteins carry out most of the interesting jobs in a cell, such as metabolism, DNA synthesis, mitosis and cell division. These physiological properties play out as a subtle molecular dance, choreographed by underlying regulatory networks that control the activities of cyclin-dependent kinases (CDK). The network can be modeled by a set of nonlinear differential equations and its behavior predicted by numerical simulation. In this paper, an innovative approach has been proposed that uses genetic algorithms to mine a set of behavior data output by a biological system in order to determine the kinetic parameters of the system. In our approach, the machine learning method is integrated with the framework of existent biological information in a wiring diagram so that its findings are expressed in a form of system dynamic behavior. By numerical simulations it has been illustrated that the model is consistent with experiments and successfully shown that such application of genetic algorithms will highly improve the performance of mathematical model of the cell division cycle to simulate such a complicated bio-system.

Keywords: Cell cycle, Cyclin-dependent kinase, Fission yeast, Genetic algorithms, Mathematical modeling, Wiring diagram

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Authors: Preetam Kumar, Saswat Chakrabarti

Abstract:

Overloading is a technique to accommodate more number of users than the spreading factor N. This is a bandwidth efficient scheme to increase the number users in a fixed bandwidth. One of the efficient schemes to overload a CDMA system is to use two sets of orthogonal signal waveforms (O/O). The first set is assigned to the N users and the second set is assigned to the additional M users. An iterative interference cancellation technique is used to cancel interference between the two sets of users. In this paper, the performance of an overloading scheme in which the first N users are assigned Walsh-Hadamard orthogonal codes and extra users are assigned the same WH codes but overlaid by a fixed (quasi) bent sequence [11] is evaluated. This particular scheme is called Quasi- Orthogonal Sequence (QOS) O/O scheme, which is a part of cdma2000 standard [12] to provide overloading in the downlink using single user detector. QOS scheme are balance O/O scheme, where the correlation between any set-1 and set-2 users are equalized. The allowable overload of this scheme is investigated in the uplink on an AWGN and Rayleigh fading channels, so that the uncoded performance with iterative multistage interference cancellation detector remains close to the single user bound. It is shown that this scheme provides 19% and 11% overloading with SDIC technique for N= 16 and 64 respectively, with an SNR degradation of less than 0.35 dB as compared to single user bound at a BER of 0.00001. But on a Rayleigh fading channel, the channel overloading is 45% (29 extra users) at a BER of 0.0005, with an SNR degradation of about 1 dB as compared to single user performance for N=64. This is a significant amount of channel overloading on a Rayleigh fading channel.

Keywords: DS-CDMA, Iterative Interference CancellationOrthogonal codes, Overloading.

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