Search results for: technique effect

Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

Abstract:

In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS, microfluidics.

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Authors: Pashayev A., Askerov D., C. Ardil, Sadiqov R., Abdullayev P.

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

Abstract:

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: Instance selection, data reduction, MapReduce, kNN.

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Authors: Adesoji T. Jaiyeola, Josiah Adeyemo

Abstract:

This paper presents an extensive review of literature relevant to the modelling techniques adopted in sediment yield and hydrological modelling. Several studies relating to sediment yield are discussed. Many research areas of sedimentation in rivers, runoff and reservoirs are presented. Different types of hydrological models, different methods employed in selecting appropriate models for different case studies are analysed. Applications of evolutionary algorithms and artificial intelligence techniques are discussed and compared especially in water resources management and modelling. This review concentrates on Genetic Programming (GP) and fully discusses its theories and applications. The successful applications of GP as a soft computing technique were reviewed in sediment modelling. Some fundamental issues such as benchmark, generalization ability, bloat, over-fitting and other open issues relating to the working principles of GP are highlighted. This paper concludes with the identification of some research gaps in hydrological modelling and sediment yield.

Keywords: Artificial intelligence, evolutionary algorithm, genetic programming, sediment yield.

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Authors: Dong Xie, Jun Zhao, Yiming Weng

Abstract:

The objective of this study was to synthesize and characterize the poly(alkenoic acid)s with different molecular structures, use these polymers to formulate a dental cement restorative, and study the effect of molecular structures on reaction kinetics, viscosity, and mechanical strengths of the formed polymers and cement restoratives. In this study, poly(alkenoic acid)s with different molecular structures were synthesized. The purified polymers were formulated with commercial Fuji II LC glass fillers to form the experimental cement restoratives. The reaction kinetics was studied via 1HNMR spectroscopy. The formed restoratives were evaluated using compressive strength, diametral tensile strength, flexural strength, hardness and wear-resistance tests. Specimens were conditioned in distilled water at 37oC for 24 h prior to testing. Fuji II LC restorative was used as control. The results show that the higher the arm number and initiator concentration, the faster the reaction was. It was also found that the higher the arm number and branching that the polymer had, the lower the viscosity of the polymer in water and the lower the mechanical strengths of the formed restorative. The experimental restoratives were 31-53% in compressive strength, 37- 55% in compressive modulus, 80-126% in diametral tensile strength, 76-94% in flexural strength, 4-21% in fracture toughness and 53-96% in hardness higher than Fuji II LC. For wear test, the experimental restoratives were only 5.4-13% of abrasive and 6.4-12% of attritional wear depths of Fuji II LC in each wear cycle. The aging study also showed that all the experimental restoratives increased their strength continuously during 30 days, unlike Fuji II LC. It is concluded that polymer molecular structures have significant and positive impact on mechanical properties of dental cement restoratives.

Keywords: Poly(alkenoic acid)s, molecular structures, dental cement, mechanical strength.

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Authors: Rasha A. Abdullah, Mohammed. A. Razooqi, Adwan N. H. Al-Ajili

Abstract:

A SnO2/CdS/CdTe heterojunction was fabricated by thermal evaporation technique. The fabricated cells were annealed at 573K for periods of 60, 120 and 180 minutes. The structural properties of the solar cells have been studied by using X-ray diffraction. Capacitance- voltage measurements were studied for the as-prepared and annealed cells at a frequency of 102 Hz. The capacitance- voltage measurements indicated that these cells are abrupt. The capacitance decreases with increasing annealing time. The zero bias depletion region width and the carrier concentration increased with increasing annealing time. The carrier transport mechanism for the CdS/CdTe heterojunction in dark is tunneling recombination. The ideality factor is 1.56 and the reverse bias saturation current is 9.6×10-10A. The energy band lineup for the n- CdS/p-CdTe heterojunction was investigated using current - voltage and capacitance - voltage characteristics.

Keywords: SnO2/CdS/CdTe heterojunction, XRD, C-V measurement, I-V measurement, energy band diagram.

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

Abstract:

Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.

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Authors: Sallama Athab, Hala Bahjat, Zhang Yinghui

Abstract:

Background detection is essential in video analyses; optimization is often needed in order to achieve real time calculation. Information gathered by dual cameras placed in the front and rear part of an Autonomous Vehicle (AV) is integrated for background detection. In this paper, real time calculation is achieved on the proposed technique by using Priority Regions (PR) and Parallel Processing together where each frame is divided into regions then and each region process is processed in parallel. PR division depends upon driver view limitations. A background detection system is built on the Temporal Difference (TD) and Gaussian Filtering (GF). Temporal Difference and Gaussian Filtering with multi threshold and sigma (weight) value are be based on PR characteristics. The experiment result is prepared on real scene. Comparison of the speed and accuracy with traditional background detection techniques, the effectiveness of PR and parallel processing are also discussed in this paper.

Keywords: Autonomous Vehicle, Background Detection, Dual Camera, Gaussian Filtering, Parallel Processing.

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Authors: A. Rabin, G. Mazor, I. Ladizhenski, R. Z. Shneck

Abstract:

The hardness and hardenability of AISI D2 cold work tool steel with conventional quenching (CQ), deep cryogenic quenching (DCQ) and rapid deep cryogenic quenching heat treatments caused by temporary porous coating based on magnesium sulfate was investigated. Each of the cooling processes was examined from the perspective of the full process efficiency, heat flux in the austenite-martensite transformation range followed by characterization of the temporary porous layer made of magnesium sulfate using confocal laser scanning microscopy (CLSM), surface and core hardness and hardenability using Vickers hardness technique. The results show that the cooling rate (CR) at the austenite-martensite transformation range has a high influence on the hardness of the studied steel.

Keywords: AISI D2, controllable cooling, magnesium sulfate coating, rapid cryogenic heat treatment, temporary porous layer.

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Authors: Alicia Y. C. Tang, Rukaini Abdullah, Sharifuddin M. Zain, Noorsaadah A. Rahman

Abstract:

This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.

Keywords: Qualitative reasoning, causal graph, organicreactions, explanation, QPT, modeling constructs.

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Authors: Pashayev A., Askerov D., C. Ardil, Sadiqov R., Abdullayev P.

Abstract:

Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.

Keywords: Identification of a technical condition, aviation gasturbine engine, fuzzy logic and neural networks.

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Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Jamalizadeh, M.R., Moghaddamnia, A., Piri, J., Arbabi, V., Homayounifar, M., Shahryari, A.

Abstract:

Dust storms are one of the most costly and destructive events in many desert regions. They can cause massive damages both in natural environments and human lives. This paper is aimed at presenting a preliminary study on dust storms, as a major natural hazard in arid and semi-arid regions. As a case study, dust storm events occurred in Zabol city located in Sistan Region of Iran was analyzed to diagnose and predict dust storms. The identification and prediction of dust storm events could have significant impacts on damages reduction. Present models for this purpose are complicated and not appropriate for many areas with poor-data environments. The present study explores Gamma test for identifying inputs of ANNs model, for dust storm prediction. Results indicate that more attempts must be carried out concerning dust storms identification and segregate between various dust storm types.

Keywords: Dust Storm, Gamma Test, Prediction, ANNs, Zabol.

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Authors: M. Mansouri, P. Jaklitsch, E. Teiniker

Abstract:

SQL injection on web applications is a very popular kind of attack. There are mechanisms such as intrusion detection systems in order to detect this attack. These strategies often rely on techniques implemented at high layers of the application but do not consider the low level of system calls. The problem of only considering the high level perspective is that an attacker can circumvent the detection tools using certain techniques such as URL encoding. One technique currently used for detecting low-level attacks on privileged processes is the tracing of system calls. System calls act as a single gate to the Operating System (OS) kernel; they allow catching the critical data at an appropriate level of detail. Our basic assumption is that any type of application, be it a system service, utility program or Web application, “speaks” the language of system calls when having a conversation with the OS kernel. At this level we can see the actual attack while it is happening. We conduct an experiment in order to demonstrate the suitability of system call analysis for detecting SQL injection. We are able to detect the attack. Therefore we conclude that system calls are not only powerful in detecting low-level attacks but that they also enable us to detect highlevel attacks such as SQL injection.

Keywords: Linux system calls, Web attack detection, Interception.

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Authors: Jung-Hyun Kim, Jihyung Kim, Kwangjae Lim, Dong Seung Kwon

Abstract:

Network coding has recently attracted attention as an efficient technique in multicast/broadcast services. The problem of finding the optimal network coding mechanism maximizing the bandwidth efficiency is hard to solve and hard to approximate. Lots of network coding-based schemes have been suggested in the literature to improve the bandwidth efficiency, especially network coding-based automatic repeat request (NCARQ) schemes. However, existing schemes have several limitations which cause the performance degradation in resource limited systems. To improve the performance in resource limited systems, we propose NCARQ with overlapping selection (OS-NCARQ) scheme. The advantages of OS-NCARQ scheme over the traditional ARQ scheme and existing NCARQ schemes are shown through the analysis and simulations.

Keywords: ARQ, Network coding, Multicast/Broadcast services, Packet-based systems.

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Authors: Mohamed A. Hammad, Dzul Azri Mohamed Noor, Syed Azhar Syed Sulaiman, Ahmed A. Khamis, Abeer Kharshid, Nor Azizah Aziz

Abstract:

The effect of statins dose intensity (SDI) on glycemic control in patients with existing diabetes is unclear. Also, there are many contradictory findings were reported in the literature; thus, it is limiting the possibility to draw conclusions. This project was designed to compare the effect of SDI on glycated hemoglobin (HbA1c%) control in outpatients with Type 2 diabetes in the endocrine clinic at Hospital Pulau Pinang, Malaysia, between July 2015 and August 2016. A prospective cohort study was conducted, where records of 345 patients with Type 2 diabetes (Moderate-SDI group 289 patients and high-SDI cohort 56 patients) were reviewed to identify demographics and laboratory tests. The target of glycemic control (HbA1c < 7% for patient < 65 years, and < 8% for patient ≥ 65 years) was estimated, and the results were presented as descriptive statistics. From 289 moderate-SDI cohorts with a mean age of 57.3 ± 12.4 years, only 86 (29.8%) cases were shown to have controlled glycemia, while there were 203 (70.2%) cases with uncontrolled glycemia with confidence interval (CI) of 95% (6.2–10.8). On the other hand, the high-SDI group of 56 patients with Type 2 diabetes with a mean age 57.7±12.4 years is distributed among 11 (19.6%) patients with controlled diabetes, and 45 (80.4%) of them had uncontrolled glycemia, CI: 95% (7.1–11.9). The study has demonstrated that the relative risk (RR) of uncontrolled glycemia in patients with Type 2 diabetes that used high-SDI is 1.15, and the excessive relative risk (ERR) is 15%. The absolute risk (AR) is 10.2%, and the number needed to harm (NNH) is 10. Outpatients with Type 2 diabetes who use high-SDI of statin have a higher risk of uncontrolled glycemia than outpatients who had been treated with a moderate-SDI.

Keywords: Cohort study, diabetes control, dose intensity, HbA1c, Malaysia, statin, Type 2 diabetes mellitus, uncontrolled glycemia.

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Authors: T.T. Wong, C.W. Leung, M.C. Wong

Abstract:

Cooktop burners are widely used nowadays. In cooktop burner design, nozzle efficiency and greenhouse gas(GHG) emissions mainly depend on heat transfer from the premixed flame to the impinging surface. This is a complicated issue depending on the individual and combined effects of various input combustion variables. Optimal operating conditions for sustainable burner design were rarely addressed, especially in the case of multiple slot-jet burners. Through evaluating the optimal combination of combustion conditions for a premixed slot-jet array, this paper develops a practical approach for the sustainable design of gas cooktop burners. Efficiency, CO and NOx emissions in respect of an array of slot jets using premixed flames were analysed. Response surface experimental design were applied to three controllable factors of the combustion process, viz. Reynolds number, equivalence ratio and jet-to-vessel distance. Desirability Function Approach(DFA) is the analytic technique used for the simultaneous optimization of the efficiency and emission responses.

Keywords: optimization, premixed slot jets

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Authors: M A Hannan, A. Hussain, S. A. Samad, K. A. Ishak, A. Mohamed

Abstract:

This paper presents a general trainable framework for fast and robust upright human face and non-human object detection and verification in static images. To enhance the performance of the detection process, the technique we develop is based on the combination of fast neural network (FNN) and classical neural network (CNN). In FNN, a useful correlation is exploited to sustain high level of detection accuracy between input image and the weight of the hidden neurons. This is to enable the use of Fourier transform that significantly speed up the time detection. The combination of CNN is responsible to verify the face region. A bootstrap algorithm is used to collect non human object, which adds the false detection to the training process of the human and non-human object. Experimental results on test images with both simple and complex background demonstrate that the proposed method has obtained high detection rate and low false positive rate in detecting both human face and non-human object.

Keywords: Algorithm, detection of human and non-human object, FNN, CNN, Image training.

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Authors: G. Parmar, S. Mukherjee, R. Prasad

Abstract:

The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.

Keywords: Order reduction, Particle swarm optimization, Relative mapping error, Stability.

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Authors: Mongkorn Klingajay, Tawatchai Jitson

Abstract:

The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.

Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.

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Authors: Sandhya Rijal, Saroj Adhikari, Ramesh R. Pant

Abstract:

Non-Timber Forest Products (NTFPs) have attracted substantial interest in the recent years with the increasing recognition that these can provide essential community needs for improved and diversified rural livelihood and support the objectives of biodiversity conservation. Nevertheless, various challenges are witnessed in their sustainable harvest and management. Assuming that sustainable management with community stewardship can offer one of the solutions to existing challenges, the study assesses the linkages between NTFPs and rural livelihood in Lamabagar village of Dolakha, Nepal. The major objective was to document the status of NTFPs and their contributions in households of Lamabagar. For status documentation, vegetation sampling was done using systematic random sampling technique. 30 plots of 10 m × 10 m were laid down in six parallel transect lines at horizontal distance of 160 m in two different community forests. A structured questionnaire survey was conducted in 76 households (excluding non-response rate) using stratified random sampling technique for contribution analysis. Likewise, key informant interview and focus group discussions were also conducted for data triangulations. 36 different NTFPs were recorded from the vegetation sample in two community forests of which 50% were used for medicinal purposes. The other uses include fodder, religious value, and edible fruits and vegetables. Species like Juniperus indica, Daphne bholua Aconitum spicatum, and Lyonia ovalifolia were frequently used for trade as a source of income, which was sold in local market. The protected species like Taxus wallichiana and Neopicrorhiza scrophulariiflora were also recorded in the area for which the trade is prohibited. The protection of these species urgently needs community stewardship. More than half of the surveyed households (55%) were depending on NTFPs for their daily uses, other than economic purpose whereas 45% of them sold those products in the market directly or in the form of local handmade products as a source of livelihood. NTFPs were the major source of primary health curing agents especially for the poor and unemployed people in the study area. Hence, the NTFPs contributed to livelihood under three different categories: subsistence, supplement income and emergency support, depending upon the economic status of the households. Although the status of forest improved after handover to the user group, the availability of valuable medicinal herbs like Rhododendron anthopogon, Swertia nervosa, Neopicrorhiza scrophulariiflora, and Aconitum spicatum were declining. Inadequacy of technology, lack of easy transport access, and absence of good market facility were the major limitations for external trade of NTFPs in the study site. It was observed that people were interested towards conservation only if they could get some returns: economic in terms of rural settlements. Thus, the study concludes that NTFPs could contribute rural livelihood and support conservation objectives only if local communities are provided with the easy access of technology, market and capital.

Keywords: Contribution, medicinal, subsistence, sustainable harvest.

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Authors: Azeem Ahmad, Magnus Goransson, Aamir Shahzad

Abstract:

The selection of appropriate requirements for product releases can make a big difference in a product success. The selection of requirements is done by different requirements prioritization techniques. These techniques are based on pre-defined and systematic steps to calculate the requirements relative weight. Prioritization is complicated by new development settings, shifting from traditional co-located development to geographically distributed development. Stakeholders, connected to a project, are distributed all over the world. These geographically distributions of stakeholders make it hard to prioritize requirements as each stakeholder have their own perception and expectations of the requirements in a software project. This paper discusses limitations of the Analytical Hierarchy Process with respect to geographically distributed stakeholders- (GDS) prioritization of requirements. This paper also provides a solution, in the form of a modified AHP, in order to prioritize requirements for GDS. We will conduct two experiments in this paper and will analyze the results in order to discuss AHP limitations with respect to GDS. The modified AHP variant is also validated in this paper.

Keywords: Requirements Prioritization, GeographicallyDistributed Stakeholders, AHP, Modified AHP.

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Authors: Mandeep Kumar, Hari Singh

Abstract:

The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Keywords: ANOVA, DOE, inconel, machining, optimization.

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Authors: Ghada S. Moussa

Abstract:

With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management.

This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.

Keywords: Appearance attributes, Geometric attributes, Support vector machine, Vehicle classification.

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Authors: Birol Gülnar, Hacer Aker

Abstract:

Student-s movements have been going increasing in last decades. International students can have different psychological and sociological problems in their adaptation process. Depression is one of the most important problems in this procedure. This research purposed to reveal level of foreign students- depression, kinds of interpersonal communication networks (host/ethnic interpersonal communication) and media usage (host/ethnic media usage). Additionally study aimed to display the relationship between depression and communication (host/ethnic interpersonal communication and host/ethnic media usage) among foreign university students. A field research was performed among 283 foreign university students who have been attending 8 different universities in Turkey. A purposeful sampling technique was used in this research cause of data collect facilities. Results indicated that 58.3% of foreign students- depression stage was “intermediate" while 33.2% of foreign students- depression level was “low". Add to this, host interpersonal communication behaviors and Turkish web sites usages were negatively and significantly correlated with depression.

Keywords: International students, depression, interpersonal communication behaviors, media using.

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Authors: M. M. Pawade, S. S. Banwait

Abstract:

Electrical Discharge Machine (EDM) is especially used for the manufacturing of 3-D complex geometry and hard material parts that are extremely difficult-to-machine by conventional machining processes. In this paper authors review the research work carried out in the development of die-sinking EDM within the past decades for the improvement of machining characteristics such as Material Removal Rate, Surface Roughness and Tool Wear Ratio. In this review various techniques reported by EDM researchers for improving the machining characteristics have been categorized as process parameters optimization, multi spark technique, powder mixed EDM, servo control system and pulse discriminating. At the end, flexible machine controller is suggested for Die Sinking EDM to enhance the machining characteristics and to achieve high-level automation. Thus, die sinking EDM can be integrated with Computer Integrated Manufacturing environment as a need of agile manufacturing systems.

Keywords: Electrical Discharge Machine, Flexible Machine Controller, Material Removal Rate, Tool Wear Ratio.

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Authors: Hamza A. Al-Sewadi, Akram N. A. Aldakari

Abstract:

Copyright protection and ownership proof of digital multimedia are achieved nowadays by digital watermarking techniques. A text watermarking algorithm for protecting the property rights and ownership judgment of color images is proposed in this paper. Embedding is achieved by inserting texts elements randomly into the color image as noise. The YIQ image processing model is found to be faster than other image processing methods, and hence, it is adopted for the embedding process. An optional choice of encrypting the text watermark before embedding is also suggested (in case required by some applications), where, the text can is encrypted using any enciphering technique adding more difficulty to hackers. Experiments resulted in embedding speed improvement of more than double the speed of other considered systems (such as least significant bit method, and separate color code methods), and a fairly acceptable level of peak signal to noise ratio (PSNR) with low mean square error values for watermarking purposes.

Keywords: Steganography, watermarking, private keys, time complexity measurements.

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Authors: M. Delavar, A.A. Ghoreyshi, M. Jahanshahi, M. Irannejad

Abstract:

This study investigates the capacity of granular activated carbon (GAC) for the storage of methane through the equilibrium adsorption. An experimental apparatus consist of a dual adsorption vessel was set up for the measurement of equilibrium adsorption of methane on GAC using volumetric technique (pressure decay). Experimental isotherms of methane adsorption were determined by the measurement of equilibrium uptake of methane in different pressures (0-50 bar) and temperatures (285.15-328.15°K). The experimental data was fitted to Freundlich and Langmuir equations to determine the model isotherm. The results show that the experimental data is equally well fitted by the both model isotherms. Using the experimental data obtained in different temperatures the isosteric heat of methane adsorption was also calculated by the Clausius-Clapeyron equation from the Sips isotherm model. Results of isosteric heat of adsorption show that decreasing temperature or increasing methane uptake by GAC decrease the isosteric heat of methane adsorption.

Keywords: Methane adsorption, Activated carbon, Modelisotherm, Isosteric heat

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Authors: Elangeshwaran Pathmanathan, Rosdiazli Ibrahim, Vijanth Sagayan Asirvadam

Abstract:

This paper aims to develop a NOx emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression (LS-SVR). Malaysia DOE is actively imposing the Clean Air Regulation to mandate the installation of analytical instrumentation known as Continuous Emission Monitoring System (CEMS) to report emission level online to DOE . As a hardware based analyzer, CEMS is expensive, maintenance intensive and often unreliable. Therefore, software predictive technique is often preferred and considered as a feasible alternative to replace the CEMS for regulatory compliance. The LS-SVR model is built based on the emissions from an acid gas incinerator that operates in a LNG Complex. Simulated Annealing (SA) is first used to determine the initial hyperparameters which are then further optimized based on the performance of the model using Nelder-Mead simplex algorithm. The LS-SVR model is shown to outperform a benchmark model based on backpropagation neural networks (BPNN) in both training and testing data.

Keywords: artificial neural networks, industrial pollution, predictive algorithms, support vector machines

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Authors: T. Kumaresan, S. Sanjushree, C. Palanisamy

Abstract:

Image spam is a kind of email spam where the spam text is embedded with an image. It is a new spamming technique being used by spammers to send their messages to bulk of internet users. Spam email has become a big problem in the lives of internet users, causing time consumption and economic losses. The main objective of this paper is to detect the image spam by using histogram properties of an image. Though there are many techniques to automatically detect and avoid this problem, spammers employing new tricks to bypass those techniques, as a result those techniques are inefficient to detect the spam mails. In this paper we have proposed a new method to detect the image spam. Here the image features are extracted by using RGB histogram, HSV histogram and combination of both RGB and HSV histogram. Based on the optimized image feature set classification is done by using k- Nearest Neighbor(k-NN) algorithm. Experimental result shows that our method has achieved better accuracy. From the result it is known that combination of RGB and HSV histogram with k-NN algorithm gives the best accuracy in spam detection.

Keywords: File Type, HSV Histogram, k-NN, RGB Histogram, Spam Detection.

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