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Architectural Development and Functional Verification of SuperSpeed USB 3.0 PHY Layer Controller [ Full-Text ]
Hasan Baig and Jeong-A Lee
Universal serial bus has supported a wide variety of devices from keyboard, mouse, flash memory device, game peripheral, imaging up to high speed broad band devices. In addition, user applications demand a higher performance connection between the PC and other increasingly sophisticated peripherals. USB 3.0 addresses this need by adding even faster transfer rates. It promises a data transfer rate of 4.8 Gbps as compared to its predecessor interface USB 2.0 which has a raw data rate at 480Mbps. This implementation of synthesizable Media Access (MAC) layer of SuperSpeed USB Memory Device, with a pipelining concept of processing the packets, is proposed to support high speed transfer rate and high throughputs. Alongside, the use of efficient handshaking signals complies with optimum performance of the overall device. Master controller has also been implemented to have a command over MAC Layer and the other layers that will be implemented in a future research. This implementation meets the required specifications and ensures the data rate of atleast 4.0Gbps.
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Voice Recognition System Using Wavelet Transform and Neural Networks [ Full-Text ]
Bayan Alsaaidah, Abdulsalam Alarabeyyat and Moh'd Rasoul Al-Hadidi
Speech is the natural way that the people interact with each other. And by there voice, they can do and remote any job. This study aims to make the voice recognition system more efficient by converting the original data to seven levels; each level presents a wavelet transform and then examines which level of the seven levels presents the best solution. This system is applied on 40 samples which presents eight words. This research is based on speech recognized words using Neural Networks, based on limited dictionary. This paper begins with introduction of this study, then presents some related works, and explained the experiment of this study; finally the conclusion and future works are presented.
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A review of Facial Caricature Generator [ Full-Text ]
Suriati Bte Sadimon, Mohd Shahrizal Sunar and Habibollah Haron
Caricature is a pictorial description of a person or subject in a summarizing way using exaggeration of the most distinguish features and oversimplification of the common features in order to make that subject ‘unique’ and to preserve the recognizable likeness of the subject. Facial caricature generator is developed to assist the user in producing facial caricature automatically or semi-automatically. It is derived from the rapid advance in computer graphics and computer vision as well as introduced as a part of non-photorealistic rendering technologies. Recently, facial caricature generator becomes particularly interesting research topic due to the advantageous features of privacy, security, simplification, amusement and their rampant emergent real-world application such as in magazine, digital entertainment, Internet and mobile application. This paper reviews the uses of caricature in variety of applications, theories and rules in the art of drawing caricature, how these theories are simulated in the development of caricature generation system and the current research trend in this field. There are two main categories of facial caricature generator based on their input data type: human centered approach and image centered approach. It also briefly explains the general process of generating caricature. The state of the art techniques in generating caricature are described in detail by classifying it into four approaches: interactive, regularity-based, learning-based and predefined database of caricature illustration. Expressive caricature is also introduced which is evolved from the neutral caricature. This paper also discusses relevant issues, problems and several promising directions for future research.
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Embedded Intelligent Web-based Controller Driven by Database-triggers [ Full-Text ]
Ahmad Aljaafreh, Majdi Khalel and Bassam Al-Mahadeen
In this paper, we take advantage of the power of database-triggers in industrial field to build a trigger-based Intelligent Controller for Distributed SCADA Systems to provide fast response and intelligent system. In addition to utilizing HTTP protocol as a communications infrastructure to exchange data between distributed stations and main servers. The system provides monitoring solution compatible with Personal computers, Phones, PDA's. This paper discusses a new Web Distributed SCADA approach that matches contemporary needs and requirements using open and proven database triggers technology. It completely eliminates many of the existing concerns and costs associated with IP technology. This paper proposes a new solution for world-wide remote industrial control and monitoring. This solution is cost-less, efficient, and highly fast. This new solution provides a smart controller using a neuro-fuzzy algorithm. This solution provides interoperability with industrial related applications such as supervisory control and data acquisition (SCADA) systems. This system uses the power of the database triggers and the flexibility of HTTP protocol as a communications infrastructure. It also uses normal web-hosting service that supports MySQL database and server-based scripting language such as PHP. A database trigger is generated by an interpreter based on conditions set by an administrator. Multiple mirror servers are used as redundant servers and one core server.
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Butter Churning Process Automating Based on Acoustic Signals [ Full-Text ]
Ahmad Aljaafreh
This paper describes a system for automating butter churning process by utilizing digital signal processing techniques based on the the sound of the churning process. Butter churning is a process to extract butter from the whole milk by mechanical motion. To the best of our knowledge we are the first who thinks of automating butter churning process based on churning acoustic signature. The argument of this paper is that sound of the churning varies according to the phase of the whole process. The churning process is divided in this paper into three phases. The first, is the churning phase, the second is the butter-begin phase, where the butter start coming, and the last phase is the butter collection phase, where the butter grains is gathered and the churning process ends. This paper characterizes the sound of each churning phase. A feature vector is extracted from each phase sound based on spectrum distribution. Artificial neural network is used in this paper as a classifier. Results show that the sound of each phase can be used to characterize the phases of the churning process. The shushing sound of the butter grains motion is recognized in this paper and can be utilized to automate the churning process. This paper also describes the design and in implementation of the system using dsPIC digital signal controller.
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Solving equations numerically and by MATLAB code using the generated function with three terms (second order equation) [ Full-Text ]
Sameh Abdelwahab Nasr Eisa
We can solve equations numerically using a lot of methods and also using the second order equation like Muller method. In this paper I used the generated function idea which depends on polynomials to convert each subinterval to second order equation using the linear equations system in order to get approximation accurate solution. I made a MATLAB code that simulate this method and deduced wonderful results included in this paper.
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Watermarking Algorithm for Secure Video Retrieval [ Full-Text ]
M. A. Mohd Shukran
With the proliferation of digital multimedia content, issues of copyright protection have become more important in video retrieval system because the copying of digital video does not result in the decrease in quality that occurs when analog video is copied. One method of copyright protection is to embed a digital code, “watermark”, into the video sequence. The watermark can then unambiguously identify the copyright holder of the video sequence. In this paper we propose a new video watermark embedding algorithm that would insert watermarks into video sequences and also detect if a given video sequence contains a given watermark. The video standard that has been chosen is the H.264 standard as it offers a significant efficiency improvement over the previous video compression standards. A couple of tests that can be considered representative for most image manipulations and attacks were performed. The proposed algorithm has passed all attack tests. The watermarking mechanisms in this paper have been proved to be robust and efficient to protect the copyright of H.264 coded video within the video retrieval system.
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A Hybrid Particle Swarm Optimization Algorithm to Human Skin Region Detection [ Full-Text ]
R. Vijayanandh and G. Balakrishnan
In this paper, a new dynamic multi-segmentation by Particle Swarm Optimization (PSO) based on hybridization with Hillclimbing segmentation with K-Means Clustering algorithm is proposed for human skin region detection. It consists of two steps. In the first step, the input RGB color image is converted into CIEL*a*b color space. Then this is clustered by Hillclimbing segmentation with K-Means clustering algorithm, which will be useful to find the number of clusters and the local optimal solutions. In the second step, these local solutions are hybridized with PSO algorithm using YCbCr explicit skin color conditions in order to find the global solution. This global solution helps to detect the robust skin region. The hybridization results have shown the efficiency of the proposed method and the results are compared with our existing work.
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Analyze Semantic of Object-Oriented Model Using RiTa.WordNet [ Full-Text ]
Noraida Haji Ali, Noor Syakirah Ibrahim, Nor Fazlida Mohd Sani and Noor Maizura Mohamad Noor
The importance of modeling is obvious with its use to predict cost and time requirement especially in completing a system. However, there is no equivalent standard for evaluating the quality of conceptual models. Thomasson has also shown the difficulties in designing the appropriate UML class diagram such as naming the notation element. The UML class diagram designed by students always neglects the quality in modeling such as consistency and accuracy. This study proposes the use of WordNet in order to achieve the quality in modeling. RiTa.WordNet will be used as a tool to extract synsets from WordNet. The use of RiTa.WordNet shows that synonyms extracted can be used to match the UML class name designed by students. This application will be used to increase the accuracy of object-oriented model.
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A Novel Job Rotation Schedule Model Regarding Posture Variety Solving by a Cellular Genetic Algorithm [ Full-Text ]
Hossein Rajabalipour Cheshmehgaz and Habibollah Haron
Job rotation is a known method that is often used to reduce monotonous workloads on workers with repetitive workstation-based jobs. Changes in a worker’s body posture can contribute to reduce the monotony; particularly, while there exists none or only minimal external force exertion. The purpose of this research is to develop a method to incorporate posture variety, individually, for each particular body area, into the rotation. This method can increase the possibility of having overall posture variety during work-hours or shift-by-shift for workers. To this end, fuzzy dissimilarity magnitudes between two jobs based on linguistic variables are defined and then used to propose new criteria. According to the criteria, an integer-programming model for the rotation is developed. Owing to the large search space in which to find a very good solution (approximated optimum solution), a conventional genetic algorithm and a customized cellular genetic algorithm are employed and compared. In addition to being intuitively logical, the algorithms are examined in a simplified test case with six different assembly jobs (performing assigned tasks repetitively), and the results indicate that the cellular genetic algorithm can efficiently find better job rotation schedules to satisfy the criteria.
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Non Repudiation for Remote Voting System [ Full-Text ]
Saira Yousuf, Malik Sikandar Hayat Khiyal, Aihab Khan and Imran Sohail
Remote voting is currently one of the most powerfully debated subjects in information communication technology for free and fair online elections. The main purpose of this research paper is to assure Non Repudiation of casted vote that is necessary in specific voting scenario. It has been designed so the institution holding the election must have proof of pointing out voters who have casted a vote. Non repudiation provides evidence that protect against any attempt by the voter to falsely deny having casted the vote. The proposed solution use digital signatures to ensure the non repudiation of the vote. The voter cast his vote by digitally signing it. The system after receiving the vote verifies authenticity of voter and safe the vote as a proof. The vote is than counted in the final tally. Only registered voter can participate in the internet voting system. The result from the system indicates the execution time and efficiency of the signatures generation using different hash functions. The quantitative analysis and comparison concludes that the signature with hash function MD4 takes least execution time and memory as compare to other signature generation algorithms. The developed system not only provides the proof of the casted vote but can also challenge the authenticity of voter.
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Web Data Refining Using Feedback Mechanism and k-mean Clustering [ Full-Text ]
D. Jatin Das, S. Arun Kumar, B. Ramakantha Reddy and S. Shiva Prakash
Nowadays more web sites are developed by everyone. Among them user cannot get accurate data that user required by searching on web. In basically web mining can be done by some page ranking algorithms are many more. In this paper , user going to refine the web pages by giving feed back or any rating by manually or by automatically. K-mean clustering algorithm is basic algorithm used day to day life. We have proposed genetic algorithm to improve cluster quality and also accurate clusters. By also apply the weblogs to our paper to more refine. Web mining using feedback is eliminating the unwanted sites in web and also it help for improving the user data in developing sites.
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Action Video Games: Its Positive Effect on Cognition [ Full-Text ]
Sushil Chandra, Jupitara Hazarika and Devendra Jha
Playing action video games enhances several cognitive performances; however, the mechanisms underlying this improvement remain unclear. The aim of this paper is to investigate the effect of 10hour action video game play, on cognitive performance based on the variation of beta waves. As frontal lobe is associated with reasoning, planning, emotions and problem solving, and parietal lobe is associated with orientation, recognition and perception of stimuli, EEG signals from these two lobes are recorded for analyzing the effect. The results show that β-waves of first hour and eleventh hour of game play have significant changes (p<0.05) in both the lobes. Moreover, the β-activity is more during eleventh hour than the first hour which indicates increase in cognition due to 10hour game training.
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A Novel Design of Low Power Smart Wireless Gas Sensor [ Full-Text ]
Rajesh Kumar, S. A. Imam and M. T. Beg
This paper represents an enhancement in the performance of wireless monitoring of smart gas sensor. In this paper we are proposing a novel design of a wireless monitoring gas sensor whose response has been drawn using latest available technologies. It consists of an 8 bit micro controller with a 16 bit ADC on chip and a 433MHz transceiver. The sensor is an electrochemical gas sensor with control circuits. Low power micro machined MOSFET Gas Sensor may be used in place of electrochemical gas sensor. This system consists of two modules; one mobile station with the sensor and one base station for the communication with a PC. As the mobile station is battery powered, so ultra-low power consumption is required. Therefore, the low power micro controller and the low power transceiver are used. In this paper we are showing the complete circuits, its response and application. This concept can be expanded for multiple gas sensor placed at different places and accessed by one center point which is far away from the site. Collecting all the data from sensors and providing it on the internet open for all if required.
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Efficiency Analysis In Outsourced Database Using Hash Chains [ Full-Text ]
Pakeeza Batool, Malik Sikander Hayat Khiyal and Aihab Khan
In database outsourcing, organizations outsource their databases to service providers. Service provider hosts clients' databases. When Digital Signatures are used for achieving authentication and Integrity in outsourced database, storage overhead occurs. If query reply contains thousands of tuples then verification of each tuple signature is very expensive for querier. For many of the security applications, one way hash chains are used (sensor networks, mobile devices). One way chains are efficiently used for authentication of one time passwords and have no storage overhead. The Sandwich chain is composed of primary chain, secondary chains and light chain (for authentication of values of secondary chains).Sandwich chain can be incorporated in database outsourcing model to reduce storage overhead caused by using digital signatures. Hashes computed for construction of sandwich chain are used for authentication of tuples returned by service provider.
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A Modified Zero Knowledge Identification Scheme using ECC [ Full-Text ]
Kanika Garg, R. Radhakrishan, Vikas Chaudhary and Ankit Panwar
In this paper we present a Fiat-Shamir-like Zero-Knowledge identification scheme based on the elliptic curve Cryptography. As we know in an open network-computing environment, a workstation cannot be trusted to identify its users correctly to network services. Zero-knowledge (ZK) protocols are designed to address these concerns, by allowing a prover to demonstrate knowledge of a secret while revealing no information to be used by the verifier to convey the demonstration of knowledge to others. The reason that ECC has been chosen is that it provides methodology for obtaining higher speed implementations of authentication protocols and encryption/decryption techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption.
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Survey on Post Mining Methodologies of Association Rules [ Full-Text ]
Kalli Srinivasa Nageswara Prasad and S. Ramakrishna
Association rules present one of the most impressive techniques for the analysis of attribute associations in a given dataset related to applications related to Retail, Bioinformatics, and Sociology. In the area of data mining, the importance of the rule management in Associating rule mining is rapidly growing. Usually, if datasets are large,the induced rules are large in volume. The density of the rule volume leads to the obtained knowledge hard to be understood and analyze. One better way of minimizing the rule set size is eliminating redundant rules from rule base. Many efforts have been made and various competent and excellent algorithms have been proposed. In this literature survey we discuss the recent approaches proposed in Post Association Rule Mining. The criteria of models discussed in this survey are much concern about the impact of input strategies.
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Web Metrics and Measurements [ Full-Text ]
Saadia Shabbir, Bushra Sikandar, Aihab khan and M. Sikandar Hayat Khiyal
Web metrics are used by organizations to bring improvement to their websites to see how a website is used by a visitor and to have an understanding of the number of visitors using a website so by this way a website could perform in a better way and would produce better outcome.The objective of this paper is to show the relationship between the number of web pages visited by a visitor and the number of hits, and visitors details including visitors ip address,server domain name,date which is basically done by using web usability metrics and measuring the number of hits when a visitor visits a website, showing all the details of visitor .The experimental results shows that the total number of hits made by a visitor while using a website is directly proportional to the number of web pages visited and the visitors ip address and server domain name is directly proportional to the total number of hits.
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Cubic Spline Approach to Study Calcium Diffusion in Neuron Cell for Rapid Buffering Approximation [ Full-Text ]
Neeta Bhargava and K. R. Pardasani
Calcium is one of the most important intracellular second messengers and has a wide range of actions. Calcium concentration is coupled to electrical activity of neurons through calcium permeable channels. In response to depolarization, calcium channels open, and calcium flows in. The influx depends on the difference between the membrane potential and the reversal potential and the number of open calcium channels. A numerical model has been developed incorporating the diffusion and reaction of calcium in a neuron cell for rapid buffer. The model has been developed for a one dimensional steady state case. The boundary conditions have been modeled using biophysical condition. Cubic Spline Interpolation has been employed to obtain the solution and perform simulation. The relationships among various parameters have been studied.
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Implementation Of Energy Efficient Proposed Routing Protocol [ Full-Text ]
Gunjan V. Mankar and Sonali T. Bodkhe
WSN consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. As sensor nodes are deployed in sensing field, they can help people to monitor and aggregate data. Researchers also try to find more efficient ways of utilizing limited energy of sensor node in order to give longer life time of WSNs. Network lifetime, scalability, and load balancing are important requirements for many data gathering sensor network applications. Therefore, many protocols are introduced for better performance.. In the available literature, multi-hop routing protocol is well known for power saving in data gathering [5]. Researchers have used such types of the cluster-based (e.g., LEACH, EERP), the chain-based (e.g. PEGASIS) and the tree-based (e.g. TREEPSI) to establish their energy-efficient routing protocols. In this paper, we propose an improved version which uses both cluster and tree based protocols. The proposed protocol improves the power consumption by improving FND.
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Heterogeneous Peers Configuration to Enhance Cooperation in Peer-to-Peer Overlay Networks [ Full-Text ]
Saira Aslam, Irum Kazmi and Muhammad Younus Javed
This research work is based on the enhancement of Quality of Service (QoS) in Peer-to-Peer (P2P) overlay networks. It reduces free riding by enhancement of cooperation among heterogeneous peers for the fair share of resources, as well as elevates the efficiency of information retrieval regarding a particular peer and its resources available and demanded for and from the network respectively. These resources could be peer’s physical attributes such as free storage space, RAM, processor cycles, or it could be any other application based resources, like media files etc. An efficient behavior of the peers in the network is retrieved by introducing cooperating groups (CG) in the network, where cooperating peers are associated to a particular CG. CG-ID is assigned to those peers who share resources on the basis of give and take rule. Through CGs it would be far more efficient to search an idol peer waiting for another peer so that both could share each other’s resources. Heterogeneous Cooperating Group-based Newscast Protocol (HCGNP) has been introduced in the network which generates cooperating peers in the network. Simulations and results show that the probability of cooperation between the peers, who remain part of the network, is very high as compared to other cooperation algorithms. Hence the current research introduces an entirely different and an efficient way of enhancing cooperation between the peers in P2P overlay networks.
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Application of Face Recognition System [ Full-Text ]
Sunita Chand and Aditya Varshney
A face recognition system has been developed by integrating a Neural Network with Fuzzy Logic technique in order to improve the decision making process. Face Recognition is emerging as an active research are spanning several disciplines such as image processing, pattern recognition, computer visions and neural network. The upper and lower parts of the human face features are extracted for the face recognition process. Different weight ages are imposed on the features and in this study the upper-face feature has been given more weight age than the lower face feature by using a fuzzy logic technique. This system has been proven effective in developing a security system with high recognition rate for different human facial expressions.
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Deployment of sensor nodes and Optimization of Energy in Wireless Sensor Network using Voronoi Diagram [ Full-Text ]
Mitali R. Ingle and Sonali Nimbhorkar
Wireless Sensor Network is a group of low-cost, low-power, multifunctional and small size wireless sensor nodes that work together to sense the environment, perform simple data processing and communicate wirelessly over a short distance. Some of these sensor nodes are able to move on their own. With the ability to move independently, these mobile sensors are able to self deploy and self repair, thus adding more to their value. The energy constraint sensor nodes in sensors networks operate on limited batteries, so it is a very important issue to use energy efficiently and reduce power consumption. The aim is to develop a system that deals with the Deployment of sensors nodes efficiently so that energy consumption is minimum with maximum data transfer in minimum hopping using the concept of Voronoi Diagram.
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A Fuzzy Agent-based Architecture for Supplier Selection [ Full-Text ]
Vivek Kumar, S.Srinivasan and Subhra Das
Today supplier selection is a critical and demanding process for the industry, which provides the company with the accurate product/raw material and/or services at the right price at the right time and in the required quantities. Consequently, supplier selection become very important for maintaining planned association. The objective of this paper is to introduce an architecture for supplier selection based on multiagent and fuzzy decision making techniques. The proposed method combines the multi agent technique and fuzzy decision making technique for supplier selection.
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An Algorithm to Improve Performance over Multihop Wireless Mesh Network [ Full-Text ]
Sumedha R. Chokhandre and Urmila Shrawankar
Transmission Control Protocol (TCP) is the dominant reliable transport protocol utilized in the Internet. Improving the performance of TCP associated with the presence of multi-hop is one of the research challenges in wireless mesh networks. Wireless mesh networks have large round trip time variations and these variations are dependent on the number of hops. In wireless mesh network, when congestion loss and wireless loss are co-existed the number of packets dropped increases and will have adverse effects on TCP and its congestion control mechanism which leads to low throughput. Here we have designed a new TCP scheme for multi-hop wireless mesh networks, by modifying the sender side congestion control functionality of TCP NewReno, which is tuned towards improving the performance of TCP. The simulation results show that TCP SAC has higher performance than TCP NewReno, Reno, Sack and Vegas in multi-hop wireless mesh networks.
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Assessment of Non-Parametric and Parametric PSD Estimation Methods for Automated Epileptic Seizure Detection [ Full-Text ]
Girisha Garg, Sonakshi Behl and Vijander Singh
This paper explores the feasibility and accuracy of using several power spectral estimation methods for the analysis of electroencephalogram (EEG) signals to distinguish the EEG of an epileptic person from that of a normal person .The features representing the EEG signals (both normal and epileptic) were extracted from the power spectral density (PSD) obtained from methods namely---Non-Parametric methods(Welch, Periodogram Algorithms) and Parametric methods(Burg, Yule-Walker ,Covariance Algorithms). In addition to this, the Mahalanobis distance based classification (MDBC) technique was employed to classify the two classes of EEG signals on the basis of the extracted features. Some conclusions were drawn concerning the most accurate method for epilepsy detection.
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Lossless Compression and Aggregation Analysis for Numerical and Categorical Data in Data Cubes [ Full-Text ]
K. Bhaskar Naik, M. Supriya, Ch. Prathima and B. Ramakantha Reddy
Logistic regression is an important technique for analyzing and predicting data with categorical attributes and the linear regression models are important techniques for analyzing and predicting data with numerical attributes. We propose a novel scheme to compress the data in such a way that we can construct regression models to answer any OLAP query without accessing the raw data. Through these regression models we develop new compressible measures, for compressing and aggregating the both numerical and categorical type of data effectively. Based on a first-order approximation to the maximum likelihood estimating equations, and Ordinary least squares we develop a compression scheme that compresses each base cell into a small compressed data block with essential information to support the aggregation models. Aggregation formulas for deriving high-level regression models from lower level component cells are given. We prove that the compression is lossless in the sense that the aggregated estimator deviates from the true model by an error that is bounded and approaches to zero when the data size increases. The results show that the proposed compression and aggregation scheme can make feasible OLAP of regression in a data cube. Further, it supports real-time analysis of stream data, which can only be scanned once and cannot be permanently retained.
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Image Enhancement Using Nonlinear Filtering Based Neural Network [ Full-Text ]
Feras N. Hasoon, Jabar H. Yousif, Nebras N.Hasson and Abd Rahman Ramli
The aim of this paper is to propose an enhancement method to solve the problem of Impulsive noise in image processing An optimization technique utilize a nonlinear filter based neural network is presented and design, a novel filter to reduce the impulsive noise has been developed as well as. The implementation of a weight median filter (WMF) and neural network gives efficient impulsive noise suppression and an excellent image detail-preserving capability. The adjustment of the weight coefficients of the WMF have been done using a back-propagation (BP) learning techniques with supervised multi-layer perceptron (MLP) feed-forward networks. A user interface using MATLAB software is designed and implemented.
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