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Application of Data Mining In Marketing
One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behavior for investment decisions. The enormous amount of valuable data generated by the stock market has attracted researchers to explore this problem domain using different methodologies. Potential significant benefits of solving these problems motivated extensive research for years. The research in data mining has gained a high attraction due to the importance of its applications and the increasing generation information. This paper provides an overview of application of data mining techniques such as decision tree. Also, this paper reveals progressive applications in addition to existing gap and less considered area and determines the future works for researchers.
Analysis of Errors - A Support System for Teachers to Analyzethe Error Occurring to a Novice Programmer
For a novice programmer, coding is equivalent to a nightmare. A novice programmer tries to replicate steps provided by the faculty and on compilation gets a number of errors which the novice programmer is not able to resolve. This system provides support to the faculty about the coding ability of the students and their ability to solve those errors. Also, the faculty can provide a solution to the errors which are occurring to the students and the solution is displayed accordingly. The emphasis of this paper is on developing this system within JAVA and making use of Online Compilers. Moreover, we focus on a new system which is able to provide online code management and these codes get compiled using an online compiler and these programs can be viewed by the respective faculty for cross verification. This paper takes into account the syntactic errors, runtime and semantic errors.
Broadband Repeat Jamming of Monopulse Receivers inMissile Borne Tracking Radar
Jamming of radar guided missile receivers are extremely difficult as the frequency lock and the servo lock requires no deviations in the repeater waveform of the jammer and its frequency. Broadband repeat jamming of such missile radar receiver is illustrated in this paper for effective deception in the presence of FM CW (Continuous Wave) interference signal. The modulation index of the FM jammer required for breaking the frequency lock of the monopulse receiver is determined and its variation with radar echo signal amplitude is presented. It is shown that modulation index required for jamming the receiver increases with increase in amplitude of the received radar echo. It is also verified that for particular radar echo amplitude, less modulation index is required for jamming the receiver when the modulating voltage in the FM jammer is maintained at large value. It is seen that break-lock in the receiver occurs when the FM modulation index is 8.75x103 or more for typical radar echo amplitude of 1 volt and FM modulating voltage of 5 mV and frequency of 0.2 MHz. The effectiveness of the jamming is estimated through computer simulation using Visual System Simulator.
Review on Fragment Allocation by using ClusteringTechnique in Distributed Database System
Considerable Progress has been made in the last few years in improving the performance of the distributed database systems. The development of Fragment allocation models in Distributed database is becoming difficult due to the complexity of huge number of sites and their communication considerations. Under such conditions, simulation of clustering and data allocation is adequate tools for understanding and evaluating the performance of data allocation in Distributed databases. Clustering sites and fragment allocation are key challenges in Distributed database performance, and are considered to be efficient methods that have a major role in reducing transferred and accessed data during the execution of applications. In this paper a review on Fragment allocation by using Clustering technique is given in Distributed Database System.
Reinforcement Learning Framework for OpportunisticRouting in WSNs
Routing packets opportunistically is an essential part of multihop ad hoc wireless sensor networks. The existing routing techniques are not adaptive opportunistic. In this paper we have proposed an adaptive opportunistic routing scheme that routes packets opportunistically in order to ensure that packet loss is avoided. Learning and routing are combined in the framework that explores the optimal routing possibilities. In this paper we implemented this Reinforced learning framework using a customer simulator. The experimental results revealed that the scheme is able to exploit the opportunistic to optimize routing of packets even though the network structure is unknown.
Eyes Detection by Pulse Coupled Neural Networks
This paper presents a new method fast and robust for eyes detection, using Pulse-Coupled Neural Networks (PCNN). The functionality is not the same as traditional neural network because there are no training steps. Due of this feature, the algorithm response time is around tree millisecond. The approach has two components including: face area detection based on segmentation and eyes detection using edge. The both operations are ensured by PCNN The biggest region which is constituted by pixel value one will be the human face area. The segmented face zone which will be the input of PCNN for edge detection undergoes a vertical gradient operation. The two gravity’s center of close edge near the horizontal line which corresponds to the peak value of horizontal projection of vertical gradient image will be the eyes.
Need of an English Language Laboratory in EngineeringUniversities
This research focuses on the need of a digital language laboratory which will allow the students of a technical university to improve their communication skills not only in work-related situations but also in personal domains. This paper talks about the importance of a language lab in English learning classes at a technical university. It also describes the barriers for teachers using language labs and finally suggests ways how language labs can be useful for students studying sciences.
State of the Art in Semantic Web Search Techniques forArabic Language
Arabic language has many differences from English language in terms of morphology and semantic. These areas of difference make it somehow difficult when it comes to web search in Arabic. Unlike Arabic language, other languages including Latin have substantiated amount of research in the use of semantic technologies in processing text and information retrieval. Despite the complexity in Arabic script, some significantly contribution has been made in the area of retrieval algorithms and semantic web techniques which can be measured in terms of the accuracy. This paper therefore, examines the state of the art in the use of semantic web search techniques for the retrieval of Arabic text.
Sentiment Analysis-Towards Harvesting Opinions from the Net
Sentiment analysis also called as Opinion mining classifies various opinions in text into categories like positive, negative as well as an implicit category of neutral. The data for this classification comes from Web (reviews, blogs, social network, discussion forums etc.). This user generated content is now regarded as a true source for exploring factual and subjective information. Sentiment analysis application involves competitive and marketing analysis as well as detection of unfavorable rumors for risk management, thereby helping companies to improve customer service, enhance their products and check the vulnerability of competitors. Opinions which are classified as positive often mean profits and fame for individuals and customers but, the system unfortunately has a loop hole where fake opinions or reviews are posted to discredit some individuals or products without disclosing their true identity. The accuracy of a sentiment analysis system in principle is to find out how well it agrees with human judgment. This paper presents a survey of various Challenges, Data Store and Levels that appear in the field of sentiment analysis.
Pair Triplet Association Rule Generation in Streams
Many applications involve the generation and analysis of a new kind of data, called stream data, where data flows in and out of an observation platform or window dynamically. Such data streams have the unique features such as huge or possibly infinite volume, dynamically changing, flowing in or out in a fixed order, allowing only one or a small number of scans. An important problem in data stream mining is that of finding frequent items in the stream. This problem finds application across several domains such as financial systems, web traffic monitoring, internet advertising, retail and e-business. This raises new issues that need to be considered when developing association rule mining technique for stream data. The Space-Saving algorithm reports both frequent and top-k elements with tight guarantees on errors. We also develop the notion of association rules in streams of elements. The Streaming-Rules algorithm is integrated with Space-Saving algorithm to report 1-1 association rules with tight guarantees on errors, using minimal space, and limited processing per element and we are using Apriori algorithm for static datasets and generation of association rules and implement Streaming-Rules algorithm for pair, triplet association rules. We compare the top- rules of static datasets with output of stream datasets and find percentage of error.
Machine Learning Techniques for Prediction of Subject Scores: A Comparative Study
In this paper, a novel method is proposed so as to predict the subject wise academic performance of the Engineering students. This study describes the prediction of subject scores in ongoing courses by analyzing subject preludes of previous semester. In this study we try to predict the individual subject scores for ongoing courses while comparing two classification techniques i.e. Naive Bayesian and C4.5 Decision tree classifier. This piece of work adheres to most critical aspect of Quality objectives of Academia i.e. finding students’ academic performances for their ongoing courses well before they face their End semester Examination. Unlike the recent research trends that focused on predicting overall grading of students during their studies, this paper orients itself in identifying students grasping levels subject wise. It was found that from study, that obtained accuracy figure was higher in C4.5 Decision tree classifier than Naïve Bayes.
A Model of Computing Trust in Web Based Social Network Using New Aggregation and Concatenation Operators
Web-based social networks can be considered as a representation of our real social network existing in our society. Web-based social networks led to the foundation for the study of trust. Trust is the measure of belief one person has on another person in relation to some tasks which will give him some good or bad result. The statistical approaches work best where the account of trust is naturally based on evidence which can be used to assess the trust one party places in another. The evidence is converted into trust which is represented by belief, disbelief and uncertainty. The concept of vector is used for representing the trust and for the combination of trust. The vector of 3-dimension can represent the trust with each dimension representing the direction of belief, disbelief and uncertainty respectively. Using the vector analysis rules the trust of an agent will be inferred.
Automated Traffic Surveillance: Evolution and Implementation
The rampant growth in use of four-wheelers has led to an increase in road congestion at all signal points. In the light of time constraints, drivers find an easier way out by breaking signals. Presently, our defense against such practices lies at the mercy of traffic policemen stationed at various signal points in the city and monitoring of surveillance cameras. However, constant manual monitoring is not always feasible because of limited manpower. Also, while the use of CCTV cameras only aids in monitoring, fine deduction is still looked after by individual traffic authorities. This system of automated surveillance is based on wireless RF transmission and circumvents the need of expensive wired fiber optic cables. The three key elements of this system include (a) infrared transmitter and sensor (b) a dual state transmitting system (c) a control room managing the data base. The motion of a vehicle passing the pre-established line near the signal is judged by the infrared arrangement, including the strip of sensors on the lower surface of the vehicle under consideration and the IR transmitter on the surface of the road, precisely on the above mentioned limiting line at the signal. The presence of the vehicle thus detected will be accounted for by a transmitter installed in it, thus changing its regular state of transmission and providing the unique number of the offender’s vehicle to the control room. The transmission stage works on the RF frequency. FSK modulation being a reliable and apt scheme has been used for the purpose of modulation of data. This brings us to the next stage of the project dealing with the data base matching and there after sending a plan of action to the undersigned bank of the user wherein the fine deduction process will be initiated. Thus in this paper, we focus on simplifying surveillance by introducing automated monitoring system.
Performance Evaluation of Routing Protocol for Mobile Ad-Hoc Network
MANET is the compilation of wireless portable nodes which dynamically arranges a short term network without the use of any centralized administration or network infrastructure. Routing protocols used in mobile ad hoc networks must mechanically change to environments that can vary between the extremes of low mobility with high bandwidth, high mobility with low bandwidth. Various secure routing protocols are proposed for mobile ad hoc networks. In this paper, a performance analysis of three MANET routing protocols- AODV, DSR and Sec-AODV are performed. AODV routing protocols was selected on the basis of the intact simulations. Due to the needs of securing the routing in the wireless ad hoc networks, Sec-AODV protocol is proposed and is developed to add security to original AOD. It includes cryptographic operations based on private key cryptography for packet authentication that can have an imperative impact on the routing performance.
A Dynamic Performance-Based Flow Control Method for High-Speed Data Transfer
This paper develops a protocol, Performance Adaptive UDP (henceforth PA-UDP),which aims to dynamically and autonomously maximize performance under different systems. A mathematical model and related algorithms are proposed to describe the theoretical basis behind effective buffer and CPU management. A novel delay-based rate throttling model is also demonstrated to be very accurate under diverse system latencies. Based on these models, we implemented prototype under Linux, and the experimental results demonstrate that PA-UDP outperforms other existing high-speed protocols on commodity hardware in terms of throughput, packet loss, and CPU utilization. PA-UDP is efficient not only for high-speed research networks, but also for reliable high-performance bulk data transfer over dedicated local area networks where congestion and fairness are typically not a concern.
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