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IJCTA-Volume 6 Issue 5/ September-October 2015
S.No
Title/Author Name
Page No
1
Implementing Six Sigma Methodology in Industrial Control Systems
-Osman Ibrahim Al-Agha,Abdelrasoul jabar Alzubaidi,Mohammed Ibrahim Al-Agha
Abstract
Control systems are impartial part of our life on this earth and for the existence of planets and stars moving around us. The whole system of the universe grows based on the equation governing the control systems (. As it is the case with all industrial control systems, we always face the problem of system instability due to the inherent dynamics of the system and the noise affecting the system.The ultimate goal is to make the actual output equals the set point within a finite time and minimum oscillations. To achieve this goal different types of controllers may be used. Massive effort for tuning these controllers is exerted. Improving the process capabilities can dramatically simplify the design problem, reduce the tuning effort and guarantee better system stability. Using the six sigma methodology helps in achieving the required process capabilities improvement hence improving the system stability and system throughput.
Key Words: Six Sigma, DPMO, DMAIC, Defects, Metrics, Process Capability Index, Stability.
642-648
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2
Automated Liquid Fuel Level Sensing and Controlling using Microcontroller
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Abdelrasoul jabar Alzubaidi,Osman Ibrahim
Abstract
This paper deals with the implementation of a microcontrollers for sensing and controlling the liquid fuel level. The purposed work is to automate the process of fuel pumping in a tank storage system and has the ability to detect the level of fuel in a tank, and accordingly display the status on the LCD screen digitally and raises an alarm. This application will provide an improvement on existing fuel level controllers by its use of calibrated circuit to indicate the liquid level and use of DC instead of AC power thereby eliminating the risk of electrocution.
Keywords: Microcontroller Fuel level sensors, Ultrasonic sensors, LCD Display
649-653
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3
Cost Contingency Reserve Evaluation Using Risk assessment For Telecommunication industry Projects
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Osman Ibrahim Al-Agha,Abdelrasoul jabar Alzubaidi,Mohammed Ibrahim Al-Agha
Abstract
when performing telecommunication projects a comprehensive risk management plan is an essential requirement to guarantee project delivery within planned schedule and budgeted cost. In this study, the project risk assessment is carried out to help the decision makers take right decisions specially regarding the contingency reserves required for both cost and schedule. The process of risk identification is pursued to identify the different risks expected and assess their probability and impacthence assigning scores for all identified risks. Using the score values attained along with the information available in schedule management plan and cost management plan the contingency reserve can be evaluated. Such an effort is essential to guarantee the viability and feasibility of these projects and to ensure that the required level of quality is delivered as per the quality management plan. In this study only cost contingency reserve will be evaluated using the risk assessment method.
Key Words: Risk Identification, Risk Probability, Risk Impact, Risk Score, Contingency Reserve, Risk Management Plan,Risk Register.
654-658
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4
Measuring the Speed of a Moving Object using Microcontroller
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Abdelrasoul jabar Alzubaidi,Osman Ibrahim Al-Agha
Abstract
This paper deals with the implementation of ultrasonic waves and microcontrollers for speed measurement. Since long ago, measurement of speeds of moving objects have been used in many purposes such as to detect high speed vehicles on roads and to find speeds of base balls. Today, it is of utmost importance to control speeds of automobiles on roads and hence, measuring speeds has become an essential requirement. For this purpose, radar guns are excessively used by police officers throughout the world at present. Those devices use radar waves and digital signal processors for doing the job. Hence, they are very expensive. In this work, it was attempted to design a simple and a low cost device. For that, ultrasonic waves were used instead of radar waves and microcontrollers were used instead of digital signal processors. Similar to radar guns, the design is based on Doppler Effect. A signal of a 40 kHz frequency was generated and it was received after colliding on a moving object. The respective frequency change was calculated by a microcontroller and the speed of the moving object can be seen on a display.
Keywords : Microcontroller, Doppler Effect, Ultrasonic , speed of moving objects.
659-663
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5
Securing Data And Preserving Privacy Access Control In Public Clouds
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N. Naveen Kumar,Bhaskara Siva Pati
Abstract
Cloud storage is a service model, in which data is stored, maintained, managed and backup remotely and made available to the users over the network. So now a days many organizations using cloud storage to store their confidential information where data owners are in charge of encrypting the data before uploading them on the cloud and re-encrypting the data whenever user credentials change. Data owners thus incur high computation and communication costs. To address this situation we are proposing an approach based ontwo level encryption where data owner has to perform a coarse-grained encryption before uploading data to the cloud server, and then cloud performs complete access control policy encryption on top of the encrypted data by the owner. Here we utilize an efficient group key management scheme that supports expressive ACPs. Our system assures the confidentiality of the data and preserves the privacy of users from the cloud while delegating most of the access control enforcement to the cloud.
664-668
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6
Customized Web Search based on Enhanced User Profile
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Akula Hima Bindu,M Kiran Kumar
Abstract
Almost all internet users use a search engine with more than 4 billion searches daily, but they are not satisfied with the results obtained so far. This is because of lack of standardization which provides inconsistent results. So there is a need to broadening the key-word search paradigm to relational data. From the past decade, this expansion has been an interesting area of research. Many of the searching techniques do not claim the performance up to the optimum level. When two dissimilar users give same query, similar results would be given by a normal search engine, no matter who ever submitted the query. This might not be a good approach for users who require dissimilar information. While surfing the net for the information users need data that satisfies their interest. We have proposed a framework for customized web search based on User Profile and Domain Knowledge. Using the User Profile and the Domain Knowledge, this framework continuous to update the user profile which in turn helps to build an improved user profile. This improved user profile is now helps in retrieving related web pages to the user.
Keywords— Relational data, Domain Knowledge, Enhanced User Profile
669-676
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7
Comparitive Study of Various Multi-Focus Image Fusion Techniques
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Dr.Vijay Kumar Banga,Astha Mahajan
Abstract
The main objective of vision fusion is to merging information from multiple images of the same view in order to deliver only the valuable information. The discrete cosine transforms (DCT) based methods of vision fusion are more appropriate and time-saving in real-time systems using DCT based standards of motionless images. In this paper, a well-ordered technique for fusion of multi-focus images based on variance calculated in DCT domain is shown. The overall objective of this paper is to compare different image fusion techniques. The comparison has shown that the Alternating Current (AC) coefficients calculated in DCT domain has quite better results. This paper ends up with the suitable future directions to extend this work.
Keywords:Image Fusion, DCT, DWT, PCA, IBLPCA
677-686
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8
Text Detection and Non-Text Filtering From Image Files
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K.Dhana Shree,G.Poorani,V.Karpagam
Abstract
Text detection and recognition is an emerging topic for researchers in the field of image processing, pattern recognition and multimedia. In order to fill the semantic gap between low level and high level features it draws the attention of Content based Image Retrieval (CBIR) community. Several methods have been developed for text detection and extraction that achieve reasonable accuracy for natural scene text as well as multi-oriented text[1]. To improve the text detection accuracy most of the methods use classifier and large number of training samples. To overcome the multi-orientation problem, the methods use connected component analysis. Since the images are high contrast images, the connected component analysis based features with classifier training work well for achieving better accuracy. Deciding classifier and geometrical features of the components is not that easy. To detect text of different orientation Gradient Vector Flow (GVF) and Grouping based Method for Arbitrarily Oriented Scene text Detection method is used. The GVF of edge pixels in the Sobel edge map of the input frame is explored to identify the dominant edge pixels which represent text components. The method extracts edge components corresponding to dominant pixels in the Sobel edge map, called Text Candidates (TC) of the text lines. Experimental results on different datasets including arbitrarily oriented text data, non-horizontal and horizontal text data, Hua’s data and ICDAR data sets show that the proposed method outperforms existing methods in terms of recall, precision and F-measure.
Key Words:Connected component (CC)-based approach, CC clustering, machine learning classifier, non-text filtering, scene text detection
687-694
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9
Application of the Mini-Models Based on n-Dimensional Simplex for Modeling of Buildings Energy Performance
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Marcin PIETRZYKOWSKI
Abstract
The paper presents the application of the mini-models' method (MM-method) based on n-dimensional simplex for modeling of energy efficiency. The article briefly describes the problem of buildings energy performance. The mini-models method is quite new and is a subject of intensive research. The MM-method is instance-based learning algorithm. In the method, group of points which are used in the model-learning process is constrained by a polytope (n-simplex) area. The MM-method can on a defined local area use any approximation algorithm to determine the mini-model and to compute its answer for the query point. The article examines the version that uses linear regression, describes learning technique and presents experiment results that shows effectiveness of mini-model in modeling of energy efficiency.
Keyword: mini-model, local self-learning, function approximation, building energy evaluation
695-700
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10
Link Anomaly Detection for Ascertaining Emerging Topics in Twitter
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S. Fairoja,R. Sathiyaraj
Abstract
Most of the time people frequently visit social networking sites rather than watching the information in news and others. The main intention here is to detecting the emerging topics in social sites like twitter. A traditional term-frequency-based approach will not be suitable to this situation, since the data shared in twitter posts contain not simply text messages but as well URLs, photos and videos. Most of us concentrate on emerging topics signaled by means of social issues with these sites. In particular, we concentrate on the mentions of users-links in between end users which can be generated dynamically (intentionally as well as unintentionally) by means of responds, retweets, in addition to mentions. The probability model of the mentioning behavior of a social end user captures both the number of mentions per post as well as the frequency of mentionee. We then aggregated the anomaly scores from numerous end users and we demonstrate that we may discover the trending topics simply using the reply/mention relationships in twitter posts. In this paper, the combination of mention-anomaly model with term frequency methods is proposed. We illustrate our strategy on the datasets obtained through twitter
701-704
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11
Labeling of the Arabic Words
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Hammad BALLAOUI,El Habib BEN LAHMAR,El Khadir LAMRANI,Nasser LABANI
Abstract
In this article we present our works on the morphosyntactic labeling and more particularly the determination of an Arabic word to the base of its affixes (prefixes and suffixes), of its particles of attributions and in contexts. Our approach bases itself on an Automat system in contextual words. The objective contextual words. The objective of the approach presented here is to associate a label with every lexical unity and to deduce ,in any final state of the automaton, to which category, kind Deterministic Finished State (AEFD). This proposed technique allows to analyze the words in two stages. The first stage shows that the system is going to handle every word entering as a noun, a verb or a particle to be attributed by one of the latter. The second stage constitutes a graphical representation of the set of the units found previously to determine the number and time do the words belong? the approach presented here is to associate a label with every lexical unity and to deduce ,in any final state of the automaton, to which category, kind.
705-711
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12
Big Data - Journey from Small Drop to Sea with Burning Challenges
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Sanjiv Kumar,Jai Shankar Bhatt
Abstract
In the present era when the focus of digital and computing world, information is towards the Data Management then Big Data is coming into light to serve the purposes in best suitable manner. By means of Big Data large amount of data with a huge great range can not only be stored, but managed and processed in proper manner. In this paper we have discussed the major issues and challenges uses the technologies Big Data. Along with issues and challenges some other aspects of big data has been discussed.
Keywords: Big data, big data management, big data issues, big data challenges
712-715
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13
Affect Computation in Children Speech Using a Mathematical Model in a Robotic Environment
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Nachamai.M
Abstract
This paper quotes a novel approach to deduce emotions from children in a machine-child interaction scenario. Emotion recognition can help the computer agents to adapt its interaction strategies to improve the efficiency of the application. In this work, four emotions are classified: confidence, hesitation, moody and puzzled. The emotions are deduced based on cue computations including lexical, prosody, spectral and syntactic. A gaussian support vector machine is deployed which takes the feature vector composed of the cues, and classifies each utterance of a speaker into one of the four classes. The approach has been implemented in PF-Star British English dataset. The methodology adopted is speaker- independent and yielded 75.98% accuracy in deducing the emotion classification. Keywords: Emotion recognition, speech analysis, Gaussian support vector machine, Affect computing.
716-720
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14
Gene Expression Data Mining for Cancer Detection
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Prachi Gupta,Dr.Ramachandra Pujeri
Abstract
Cancer is getting constantly challenged by many eminent and premier researchers. Due to advanced developments in instrumentation, it has become easier to collect a lot of experimental data in molecular biology. Analysis of such data is very vital as it leads to knowledge discovery that can further be validated by experiments. It has been used multiple times for cancer classification and of identification of marker genes associated with cancer. However, this technique often suffers the "curse of dimensionality". A very powerful application of microarray expression data is called classification analysis. This uses gene expression data to separate samples into multiple categories.
In this work gene selection will be approached first using gene filtering by determining the expressions ranges of the genes attributes and figuring out if they can be deferentially expressed across the samples. Filtered genes will then be subjected to hybrid K-Mean and Speed-constrained Multi-objective PSO (SMPSO) algorithm for clustering to identify set of genes that can be used to determine the types of Cancer. The selected genes will then be used to build classification models.
Index Terms – Microarrays, Data Mining, PSO, SMPSO, Gene Selection
721-724
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15
Project Cost Reduction by Requirement Risk Assessment & Mitigation at Requirement Gathering Stage
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Dr. Priti Puri,Pradnya Purandare
Abstract
Requirement gathering is very crucial and important phase for any project in organization, and flaws at requirement gathering can directly impact to the cost of the project by increasing the changes in projects at later stage. In this paper, we have tried to concentrate on identifying some risks, its impact and mitigation to those risks at requirement gathering phase which may directly reduce the cost of the projects
725-732
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16
Gesture Recognition For Mood Detection
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Prof.Shamla Mantri,Sonakshi Nathak,Sonal Gadiya,Ramolee Chaudhari,Sunny Bangale
Abstract
Depression is one of the most common mental health disorders with strong adverse effects on personal and social functioning. This project studies the contribution of facial gestures and fiducial points for mood analysis. Analysis of facial movements is carried through a framework based on three steps: Facial extraction, Facial reduction and Facial Analysis. The experiments are performed based on clinical data where video clips of patients and healthy controls are recorded during interactive interview sessions including questionnaires. The diagnosis is done and appropriate action is taken according to severity of the depression in the patient. These findings and implementation of the project suggest the feasibility of automatic detection of depression, promising a future of unexplored areas in automated facial analysis. We use consecutively, a questionnaire and automated facial image analysis to detect depression across a variety of clinical samples using Principal components analysis (PCA) to measure facial expressions. Findings and implementation thus performed suggests the feasibility of automatic detection of depression, promising a future of unexplored areas in automated facial image analysis and machine learning has exciting implications for clinical theory and practice
733-739
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17
Study About Internet Security and Privacy
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Hamed Pourzargham
Abstract
The internet has revolutionized different aspects of life including shopping, work and the social experiences of people all around the globe. Privacy which is the control and proper management of the person data of a person and security which entails the protection of data from any form of unauthorized access are essential issues for not only the Internet but the activities that take place in the web at large. The omission of either, can lead to significant security issues such as identity theft and malicious hacking all of which can have significant effects on the users. This ISI paper will analyze the current status of the Internet and the relevance it has on privacy as well as security. The paper will analyze privacy from different perspectives among them regulatory, organizational, technical and social perspectives
740-744
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18
A Survey on Interaction with 3D Model through Hand Movements
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Rachita S.Waghmare,Sushmita K.Ahire,Jueily S.Wayde,Pranita K.Fuldeore
Abstract
The aim of research is studying the viability of setting up a contactless identification system based on hand features. The identification solution will rely on a commercial 3D Leap Motion sensor for palm feature capture. Different classification algorithm can be used to evaluate the significance of different hand features. The selected classification strategies - nearest neighbor, supported vector machine, MD-DTW(Multidimensional dynamic time warping), multilayer perceptron, logistic regression and tree algorithms - have been evaluated through available Weka implementations.52 morphological features are collected for each user ,which include, palm characteristics, bones length and width and relative distance relationships among fingers, palm center and wrist. Testing showed that the controller is able to provide accurate tracking of hands and fingers, and to track movement. Sweet spot are used to guide the user to place the hand in the best orientation with respect to device in order to get the consistent samples and guarantee the best performance for device.
745-748
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19
A Study of Hierarchical and Partitioning Algorithms in Clustering Methods
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T Nithya,Dr.E Ramaraj
Abstract
In recent research environment, clustering plays as a vital role in data mining techniques. In this environment, the research paper mainly focuses on two different kinds of clustering algorithms there is, hierarchical and partitioning. In this algorithm, the research paper compares two types of algorithms such as hierarchical algorithms of K-means and partitioning algorithms of agglomerative algorithm. The aim of this research paper is focuses clustering functionalities, characteristics and classifications and also comparing with them.
Keywords: Clustering, Partitioning method, hierarchical method, k-means and agglomerative algorithm
749-755
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20
Protected Personalized Web Search Securing Privacy
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MD.Shaheer Banu
Abstract
In couple of years the usage of web search has increased exponentially which has been popular because of the way the search criteria implemented on the basis of requirements (requirement based search) or personalized web search (PWS). Personalized web search (PWS) is more effective and day by day it has achieved mileage in terms of improvement of quality and performance. But also in other way the risk has increased as many times the searches involves many personal aspects and data which drags attention toward security vulnerability. Even the more usages towards PWS bring reluctance in user’s mindset towards disclosure of their private information in between the search which had stood as an obstacle for the large explosion of PWS. This paper proposes a PWS framework names as UPS (User adaptable Privacy-protecting Search) which generalizes the user profiles adaptively through different queries introducing the concerns on client pointed out protection prerequisites. Hence the runtime generalization points towards raising the harmony between two prescient measurements assessing the effectiveness of personalization and the protection danger of uncovering the summed up profile. This task includes two greedy algorithms, 1) GreedyDP and 2) GreedyIL, both include runtime generalization. This paper involves approach towards online prediction mechanism to decide if at all personalizing a query might benefit the user or not. Adopting the algorithms GreedyIL with GreedyDP marginally improves the performance as well as the security concerns.
Keywords: Privacy Protection, profile, personalized web search, risk, UPS
756-760
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