Ijcet Iaeme

News archiving becomes a formidable task due to the perpetual generation of news. Archives play a vital role in crafting personalized news programs. Adhering patches of information, crafting the story and shaping up a news script defines the whole process of news generation. Creating refreshed news stories in small time intervals perch in as a challenge. The journalists access news archives to procure details about the past events related to the latest news update. The whopping amount of news articles which pops out on a single query makes extracting the relevant information a tedious task for the newsreporter. Here we present newssummary generation system based on ontology and natural language processing techniques. The system is tested using BLEU method and correlated the metric score with human evaluation.

In today’s digital world, image edge detection is widely used in all over the globe. Digital image edge detection is used to detect the sharp changes in brightness of the images and the edge of a digital image. There are many classical techniques used to detect image edge detection like Canny, Sobel, Prewitt and Robert edge detector method. The proposed research work mainly focuses on the study of different edge detection methods which were previously derived and to propose an efficient method of digital image edge detection technique using Discrete Wavelet Transform (DWT). The results were compared with one of the best edge detector method: Canny Edge Detector. In the proposed image edge detection method, the first analytical result showed that an input image after applying the thresholding technique represents a segmentation of image edges and the second analytical results showed the 8- connected components of pixel connectivity in two dimensional images related to their neighbor pixels producing the enhanced edges. To evaluate the performance of the proposed algorithm with the existing algorithms, the two thresholding values were applied as T_low and T_high using hysteresis thresholding method. PSNR and width σ were also computed to detect the efficiency of the proposed algorithm.

Service-oriented architectures are widely considered to be the determining trend in software engineering. Vendors of software products want to benefit by migrating to cloud environments. However, when transforming an existing software system from the Software as a Product model to the Software as a Service model the software engineering process changes. While the process in general has been researched suf iciently, very low effort has been put into understanding the impact on requirements elicitation. This paper investigates the necessary changes in the requirements engineering process and provides a systematic approach for a successful transformation. Furthermore, it discusses the new benefits in requirements elicitation that are inherent in a cloud environment. The paper then discusses the identified problems and developed solutions with regards to deduced guidelines and best practices. We conclude that the requirements engineering process profits from a systematic transformation when migrating a traditional software product to the Software as a Service model.

A new kind of comfort and confidence has been created by location based services in the mind of mobile and internet users by providing automotive help in many areas like tracking, navigation, gaming and information fetching about a specific concern. With the increasing usage of said services, this is irrelevant to say much about the critical role of LBS in various fields. After closely analyzing the present situation related with exploitation of LBS conclusion can be made that anything can be tracked dynamically, rapidly and correctly by the technological background provided by LBS and associated services. With increasing utilization of location related services the duties of service providers has been occurring on its peak with respect to customer satisfaction. Number of approaches and methods are being adopted for providing best services to customers. This paper is providing a modeling approach for vehicle tracking process by using LBS in logistics sector through Unified Modeling Language (UML). By using UML, various sessions and operation of tracking have been modeled. With consideration of running Vehicle Tracking System (J-Track) various reports are analyzed for setting some objectives about future research. An Object Oriented Data Modeling technique is being used to process the data and it is represented with the help of UML- Use-Case diagram, Class Diagram, Sequence diagram, Activity diagram and State diagram.

At present, cloud computing extremely popular subject, which allows a service provider to provide seamless service/information over internet. Therefore, it eliminates the necessity for maintaining expensive computing resources. Testing cloud applications possesses its own challenges that demands for novel testing strategies and tools. Instead, cloud application also allows and provides options for the development of more beneficial and scalable software testing techniques. Because of this, an appropriate standard that really helps user to utilize application without any downtime is the need of the hour. Therefore, to ensure Geo-Red applications high quality, a number of test cases for geo redundancy are being proposed. Thus, this work is an extension of work already proposed as an effective testing framework (TF2Grace) that fulfills these types of needs. This paper provides the test environment setup and also describes the structural design and application experiment with proposed framework. It further provides an appropriate report and recommendation for the application under test.

In this system we propose a novel privacy-preserving mechanism that supports public auditing on shared data stored in the cloud. In particular, we exploit ring signatures to compute verification metadata needed to audit the correctness of shared data. With our mechanism, the identity of the signer on each block in shared data is kept private from public verifiers, who are able to efficiently verify shared data integrity without retrieving the entire file. In addition, our mechanism is able to perform multiple auditing tasks simultaneously instead of verifying them one by one. Our experimental results demonstrate the effectiveness and efficiency of our mechanism when auditing shared data integrity. This Project Mainly Focus To Realize The Authentication For The Data Accesson a Demand Mode. New Security And The Privacy Concerns Can Be Performed. AIDA Algorithm Is Used For The Multiparty Oriented Cloud Services. SAPA Protocol for Address the Privacy Issue.

Computing is changing frequently to serve the user’s needs for security and reducing a dependency which leads researcher to develop newer technologies. Cloud computing is one of those technologies which successfully delivers the service oriented architecture to reduce the burdensome of managing the devices. But in some situation instead of providing controls to the end user it operates as a reverse effect. Data destruction is the one of that transformation in which the deletion of data is required by the user from the storage locations. But the existing destruction mechanism will leaves certain type of metadata residues from which either the data or users information can be regenerated which gives an attack prone zone for outsiders. This work proposes a novel IT-DHSD mechanism based on effective active storage object transition with privacy enabled operation to give more control to the user. In this each object contains the data and the destruction or deletion time which works as an...

This paper addresses the problem of partitioning a graph and particular the use of the genetic algorithms for graph partitioning. It is a NP hard problem. The solution of a graph (circuit) partitioning problem is global optimum. In this practical paper solution is easy and we can easily apply genetic operator in this type of problem. One of the application of Graph partitioning in chip designing. The target of our approach is to design modular chip which can be realized with self standard IC chip if VLSI circuit can be converted into a graph and obviously we have taken into account minimum power consumption. Our approach to partition the Graph into sub Graphs and minimization of the number of cuts is our main objective. Our approach with Genetic algorithm calculates the fitness (number of cuts) and discard the solution with low fitness value. Multi way partitioning can be easily implemented if we increase number of crossover point. Fitness value achievement depends on crossover and mutation probability. We can change crossover boundary when fitness value is low in previous generation and continue until optimum result is found.

In this paper, a new adaptive weight algorithm is developed for the removal of salt and pepper noise particularly in satellite images. Satellite images are corrupted when acquired by a defective sensor or when transmitted through a faulty channel. Salt and pepper noise can be commonly found in the sensor or transmission channel during acquisition and transmission of digital satellite images. This algorithm can be worked in two phases. During the first phase, detecting the noise pixel according to the correlations among image pixels and in second phase adaptive weight algorithm is used to remove the noise. Simulation results based on Matlab show that this method can eliminate the salt and pepper noise in satellite images efficiently and preserves edges and details information of the image. Also this method can remove noise for highly contaminated image with noise level as large as 90%, it still can get the better performance

In today’s age the major problem is related to the predicting user’s web page request. In the past few years the markov model is used for this problem. The effective web mining techniques like Clustering, Association rule mining and markov model having many drawbacks. We are proposing an approach for overcome that drawbacks which help us to improving search engine and helping user to find interesting web pages.

This article describes in detail how to detect the effects of climate change through hybrid technology and give the solutions. In today's environment, climate change [1] is emerging as the biggest problem threatening the world. This study describes in detail the study of the detection and characteristics of various types of natural disasters caused by climate change such as heavy rains, floods, storms, and wildfires. This research is the combination of IOT, wireless sensor network, Big data analytics, Cloud computing and artificial Intelligence. The proposed system consists of wireless sensor which detect Environmental factor such as rain, flood, storm and wildfire. The sensor data are stored and it will be analyzed into already existing environment data. When there is a discrepancy between the information taken by the sensor and the existing information, the actuator in this system will start working automatically. For example, sensors that sense rain during heavy rains send information to a Database. If there is a discrepancy between the existing information and the information available, actuator will start working immediately. Immediately the information goes to the Central Control Room and from there the information goes to the Disaster Management Centre. So main aim of this project is to detect the climate change in environment, and it gives the solution to the problem.

In this paper, a similarity measure for images based on values from their respective Fourier Transforms is proposed for image registration. The approach uses image content to generate signatures and is not based on image annotation and therefore does not require human assistance. It uses both, the real and complex components of the FFT to compute the final rank for measuring similarity. Any robust approach must accurately represent all objects in an image and depending on the size of the image data set, diverse techniques may need to be followed. This paper discusses implementation of a similarity rating scheme through the Open CV library and introduces a metric for comparison, carried out by considering Intersection bounds of a covariance matrix of two compared images with normalized values of the Magnitude and Phase spectrum. Sample results on a test collection are given along with data using existing methods of image histogram comparison. Results have shown that this method is particularly advantageous in images with varying degrees of lighting.

As mobile devices grow in popularity and presents in everyday life, it’s often involved in digital crimes and investigation as well. But rapid evolution of new form of online communication known as social networking has become a medium for real time activities which involve instant messaging and conversation or chatting, status, comment and share of information and ideals. A brief forensics analysis was done on some of the popular social media platform like Hi5 and Tagged. Activities on this platform were examined and how it’s potential for forensics investigation. This paper briefly discussed how relevant data would be gathering from the various activities/features used by the platform for crime investigation of suspects.

With the substantial growth in volume and complexity of data used in the digital world large organizations need to handle a variety of unstructured data. Traditionally relational database systems have been used to store, process and retrieve data although other types of databases such as hierarchical, network, graph have existed before 1970, yet their commercial goals were not achieved until recent years. These databases (called NoSQL or Non-relational databases) are complements to relational databases and are used by world's largest organizations such as Google, Amazon and Facebook. This research compares the performance of relational and non-relational databases namely Oracle, and MongoDB by executing complex queries on a large set of data that is available in document-based mode and is converted to Oracle tables. The results show that data retrieval is significantly faster in MongoDB however some mathematical queries such as aggregation functions(sum, count, AVG) are better suited to Oracle RDBMS.

In information field we have huge amount of data available that need to be turned into useful information. So we used Data reduction and its techniques. A process in which amount of data is minimized and that minimized data are stored in a data storage environment is known as data reduction. By this process of reducing data various advantages have been achieved in computer networks such as increasing storage efficiency and reduced computational costs. In this paper we have applied data reduction algorithms on NSL-KDD dataset. The output of each data reduction algorithm is given as an input to two classification algorithms i.e. J48 and Naive Bayes. Our main is to find out which data reduction technique proves to be useful in enhancing the performance of the classification algorithm. Results are compared on the bases of accuracy, specificity and sensitivity.

Nowadays, analytics is playing a key role in any field. Analytics is used in our day to day life. People don’t want to purchase even without analytics. Before few months IPL (Indian Premier League for Cricket) auction was taking placed. Even franchises are interested to pick a cricket player based on their past performances. For all this, they need accurate data and analytics with the comparative study to pick a particular player for their team. Here, we are comparing the last 10 years cricket sports data of IPL with interesting facts. We can perform much analytics but here we are focusing on the comparison between popular players, team, and fielders. Performance of top-10 players in each category like batting, bowling and fielding. Valuable player for the specific team.

Cloud computing is a concept of modern and smart computing world. People buy high configuration computer system for their use but a little amount of the total capacity is used by them. So, computing power and money both becomes waste. The solution of this problem is cloud computing. In cloud computing environment the client’s whole data is on cloud server which is offered by cloud service provider (CSP). Cloud service provider offers facility of processing power, storage space, software etc. The whole data of user is on cloud server and accessed by user through login credentials. Cloud computing reduces the on-demand hardware and processing power requirement of these days. While the need of cloud computing increases the security challenges also increases. This paper first describes the need of cloud computing and some security challenges and some proposed security solutions to it.

With the substantial growth in volume and complexity of data used in the digital world large organizations need to handle a variety of unstructured data. Traditionally relational database systems have been used to store, process and retrieve data although other types of databases such as hierarchical, network, graph have existed before 1970, yet their commercial goals were not achieved until recent years. These databases (called NoSQL or Non-relational databases) are complements to relational databases and are used by world's largest organizations such as Google, Amazon and Facebook. This research compares the performance of relational and non-relational databases namely Oracle, and MongoDB by executing complex queries on a large set of data that is available in document-based mode and is converted to Oracle tables. The results show that data retrieval is significantly faster in MongoDB however some mathematical queries such as aggregation functions(sum, count, AVG) are better suited to Oracle RDBMS.

There are millions of websites in the world now but it has been observed since very long time that Web Security has been one of most important areas of research whether be it either analysis or detection and later developing to mitigation plans. Web security threats are very much present now days and they have undergone much sophistication comparing to their initial phase. Now they are becoming more & more evolved each day. The evolution of threat on websites might be in terms of new ways of attack or bringing in resistance to using simulated Operating Systems or VM ware environments. Also, there has been considerable shift in the target of attacks in recent years. Earlier, clients were ignored while choosing targets. But, in recent years client user has become the main target for attacks as the adversary believe that the end user is the weakest link in the security chain. This paper is presented here to study the issues related to web security in cyber world

With the continues development of the computer network, information has been exchange in different format like text, image, audio and videos. In today’s scenarios security is playing a vital role in networking. Securing all these types of information is most important. There are different types of cryptographic encryption methods are used to send the information through network with security. But still there are some open issues. Each encryption method has its own strength and weakness. The combination of various encryption techniques i.e. hybrid encryption techniques provides the better security. This survey analysis the different hybrid encryption techniques and working principle of those hybrid techniques

With the substantial growth in volume and complexity of data used in the digital world large organizations need to handle a variety of unstructured data. Traditionally relational database systems have been used to store, process and retrieve data although other types of databases such as hierarchical, network, graph have existed before 1970, yet their commercial goals were not achieved until recent years. These databases (called NoSQL or Non-relational databases) are complements to relational databases and are used by world's largest organizations such as Google, Amazon and Facebook. This research compares the performance of relational and non-relational databases namely Oracle, and MongoDB by executing complex queries on a large set of data that is available in document-based mode and is converted to Oracle tables. The results show that data retrieval is significantly faster in MongoDB however some mathematical queries such as aggregation functions(sum, count, AVG) are better s...

The study investigates the current impact of Electronic Data Interchange (EDI) adoption in shipping, logistics sea freight forwarding industry and in customs. It is found that the level of adoption of EDI applications in shipping logistics industry is considerably comprehensive. The observed perceived usefulness and perceived ease of use of EDI applications are high across the industry, particularly for web-based EDI applications. Merchants are increasingly using computers to facilitate international transactions, and many observers believe that full-fledged electronic commerce is nearing reality. At present, the business community uses electronic data interchange. The most significant perceived benefits brought by EDI implementation are found to be faster information response and access, improvement of efficiency and streamlining of logistics processes. Since EDI being both quick and efficient, the shipping industry is expected to benefit greatly from its adoption, particularly in the areas of bills of lading. Unfortunately, numerous technical and legal obstacles have slowed the introduction of EDI, with the chief impediment being the law’s insistence on paper-based documentation. Recently however, several significant steps have been taken to promote the use of EDI and it is revealed that more Research &Development efforts focusing on the provision of real-time information are warmly anticipated by the industry.

At present, tags are extensively used to describe the images, so that utilizing these tags for image retrieval system is today’s need. So, our system incorporates image similarity graph with image-tag bipartite graph using visual features of image like color, shape & texture .For color feature extraction HSV model, for shape feature extraction Sobel with mean and median filter, for texture feature extraction Framelet methods are used. Initially we extract features by these three methods and all features are combined for matching between images in the database and query image. Combination of the features of the three methods along with CBIR and TBIR are used to balance the influence between image content tags. The system is able to retrieve the images related to the query as well as annotating the query image.

With the continues development of the computer network, information has been exchange in dif erent format like text, image, audio and videos. In today’s scenarios security is playing a vital role in networking. Securing all these types of information is most important. There are dif erent types of cryptographic encryption methods are used to send the information through network with security. But still there are some open issues. Each encryption method has its own strength and weakness. The combination of various encryption techniques i.e. hybrid encryption techniques provides the better security. This survey analysis the dif erent hybrid encryption techniques and working principle of those hybrid techniques.

Rootkit is one of the primary concerns of network communication systems, which is related to the security and privacy of Internet users. The worldliness of malicious software (malware) used to breakdown the computer security has increased exponentially in the recent years. Therefore, early detection of rootkits is on top priority to avoid the unrestrained operation of malware. Most of existing techniques only allow late rootkit detection after the malware has already been hidden by a rootkit. In this paper, we put forward a dynamic framework to detect kernel rootkits and guarantee the runtime security of guest VMs. The method is explicit to a guest Virtual Machine (VM), since it does not require any specific system information. The initial strategy is a virtual machine screen based resource arrangement component, which can limit the resource usage with given execution ensure. The end results reveal that the component that is put forth can allocate resources for a rootkit distinguishing proof on request.

Diabetes mellitus is a common disease caused by a set of metabolic ailments where the sugar stages over drawn-out period is very high. It touches diverse organs of the human body which therefore harm a huge number of the body's system, in precise the blood strains and nerves. Early prediction in such disease can be exact and save human life. To achieve the goal, this research work mainly discovers numerous factors associated to this disease using machine learning techniques. Machine learning methods provide effectual outcome to extract knowledge by building predicting models from diagnostic medical datasets together from the diabetic patients. Quarrying knowledge from such data can be valuable to predict diabetic patients. In this research, six popular used machine learning techniques, namely Random Forest (RF), Logistic Regression (LR), Naive Bayes (NB), C4.5 Decision Tree (DT), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM) are compared in order to get outstanding machine learning techniques to forecast diabetic mellitus. Our new outcome shows that Support Vector Machine (SVM) achieved higher accuracy compared to other machine learning techniques.

Biometric Systems Now a Days are playing a vital role in the whole word. Biometric Identification is been carried out in all the industrics, Institutions and in all the concerns wherr we are in need of the security and heavy monitoring. There are various traints considered for identifying and Authenticating the individual persons, they may include the behaviourial and also the physiological traits. Eye tracking is the process of measuring either the point of gaze (where one islooking) or the motion of an eye relative to the head. An eye tracker is a device for measuring eye positions and eye movement. Eye trackers are used in research on the visual system. This paper focuses on the identification with low frequency Eye Tracker. he most widely used current designs are video-based eye trackers. A camera focuses on one or both eyes and records their movement as the viewer looks at some kind of stimulus. Most modern eye-trackers use the center of the pupil and infrared / near-infrared non-collimated light to create cornealreflections(CR). The vector between the pupil center and the cornealreflections can be used to compute the point of regard on surface or the gaze direction. A simple calibration procedure of the individual is usually needed before using the eye tracker. This paper presents a review of the related works in the field as well as a general classification of dif erent identification types. We stated a formal description of a saccade and an analyzed fragment of the gaze trajectory containing a saccade, which is based on the finite dif erences method, and revealed features of the eye movements that can be used for the identification purpose. Two classifiers are proposed and compared based on the experimental results obtained for them and we examined whether the delivery of an attentional bias modification (ABM) procedure in the presleep period could produce transient benefits for sleep-disturbed individuals by reducing presleep cognitive arousal and improving ease of sleep onset. In a counterbalanced repeated A-B design, participants alternated completing an These results suggest that delivery of ABM can attenuate cognitive arousal and sleep onset latency and highlights the possibility that targeted delivery of ABM could deliver real- world benefits for sleep-disturbed individuals.

Agriculture is the backbone of Indian economy. About 50% of Indian population depending on agriculture sector to meet their day-to-day expenses. The current irrigation system practiced in India is sprinkler water irrigation, tank water irrigation, inundation irrigation, etc. these methods are less efficient as they do not scatter to the requirement of the moisture level of the soil and do not make efficient use of water resources. In the future, as population increases, demand for food crops increases, which eventually results in depending on water resource on a large scale. The electricity distribution in India is poorly organized and very unsettled. Currently, India requires technological up gradation to meet the demand for irrigation purpose. The IOT based Modern Farming enables efficient utilization of water as the soil is constantly monitored with the help of moisture sensor and based on the readings the crop is irrigated with the help of a motor. The power is supplied through the DC Adapter/battery12V. All this can be achieved using IOT technology. The main ideology behind this project is to reduce human intervention and efficiently make use of water and electricity. This is made possible by sending received data to the android device using Bluetooth Module. The entire system is controlled and executed by the Arduino UNO Board microcontroller.

The Cyber risk landscape is developing rapidly in multitude areas. Report to cyber attacks dominates the headlines. It is seemingly becoming more frequent and more sophisticated than ever. Businesses across the wide spectrum of industries are exposing to potentially enormous losses as result of cyber attacks and data breaches. Banks, manufacturing companies, universities, the government even the US military have been attacked. In 2013 more than 600 organizations publically disclosed data breaches revealing that nearly 92 million records have been expose. Security researchers found the fact that technical security solutions alone will not result in robust cyberspace. So, some researchers proposed cyber insurance as an acceptable risk management technique to financially protect the cyber space after Cyber Attack. In this regard we theoretically investigate the following important questions (1) What are the Cyber Risks (2) How to prevent cyber attack (3) why we need cyber insurance when we have advanced technical solutions to protect out network and data, To address these questions we examine how cyber insurance plays an important role for making a robust cyberspace.

Big Data has become a research hotspot in academia and industry, and it is affecting people's daily life, work habits and ways of thinking. However, at present, big data faces many security risks in the process of collection, storage and use. The leakage of privacy caused by big data poses serious problems for the users, also the incorrect or false big data will lead to wrong or invalid analysis of results. This paper analyzes the technical challenges of implementing big data security and privacy protection, and describes some key solutions to address the issues related with big data security and privacy. It is pointed out that big data is an effective means to solve information security problems while introducing security issues. It brings new opportunities for the development of information security.

OLTP applications, in the current times, require support for ACID transactions and concurrency. But these properties each come with their trade-off. NewSQL systems have emerged as the solution to this conundrum, by overhauling the traditional architecture of RDBMSs. Concurrency control scheme selected has a major impact on the architectural performance. In this paper we firstly discuss the older concurrency control schemes used in the conventional SQL systems like two phase locking protocol and later discuss the modern concurrency control schemes used mainly in the modern NewSQL based systems such as multi version concurrency control, basic timestamp concurrency control, optimistic concurrency control, Timestamp ordering with partition level locking. Later, we have discussed the contemporary NewSQL systems with emphasis on underlying architecture and schemes used for controlling concurrency.

Computational Musicology is new and emerging field of Data Mining. Raga is the most aspect of Indian Classical Music. It consists of unique set of notes (swara) and Pakad that correspond to a specific pitch. North Indian Classical Music has its root in Vedic ritual chants and has remained relatively untouched. Here, we depict a system that takes audio input file, convert it into sequence of notes and then find its most matching pattern. This pattern resembles with pakad of a raga and there by identifies the raga.

With the substantial growth in volume and complexity of data used in the digital world large organizations need to handle a variety of unstructured data. Traditionally relational database systems have been used to store, process and retrieve data although other types of databases such as hierarchical, network, graph have existed before 1970, yet their commercial goals were not achieved until recent years. These databases (called NoSQL or Non-relational databases) are complements to relational databases and are used by world's largest organizations such as Google, Amazon and Facebook. This research compares the performance of relational and non-relational databases namely Oracle, and MongoDB by executing complex queries on a large set of data that is available in document-based mode and is converted to Oracle tables. The results show that data retrieval is significantly faster in MongoDB however some mathematical queries such as aggregation functions(sum, count, AVG) are better s...

RFID is only one of numerous technologies grouped under the term Automatic Identification (Auto ID), such as bar code, magnetic inks, optical character recognition, voice recognition, touch memory, smart cards, biometrics etc. Auto ID technologies are a new way of controlling information and material flow, especially suitable for large productions [1][17] This paper gives a review of the current state of the art in the radio frequency identification (RFID) technology. This is short prologue to the standards of the engineering; a survey is given on real classes of RFID labels and readers. The introduction of RFID systems in industrial manufacturing has already been taken up more than ten years ago. RFID is a smart and promising technology in various applications like asset tracking, animal tracking, in wall mart and in inventory management. This paper is a roadmap for new learners in RFID technology

Semantic Textual Similarity (STS) calculates the degree of semantic equivalence between two textual snippets, even though they do not share common words. The textual snippets are words, phrases, sentences, paragraphs or documents. In this work, the textual snippets are sentences. The similarity between the sentences can be measured with the aid of lexical, syntactic and semantic features entrenched in the sentences. In SemEval workshop, the STS task is to measure the semantic similarity between the sentence pairs. The dataset contains the sentence pairs and the human annotated real values from 0-5. In this paper, the experimental analysis of various lexical, syntactic and semantic features on STS 2016 dataset is carried out. This analysis is useful while building the models with machine learning algorithms with the aid of these features. The impact of the individual features on semantic textual equivalence is assessed between the feature generated values and human annotated values using Pearson Correlation Coefficient.

Vehicular ad hoc network (IEEE 802.11e) is dynamic network where independent identity node helps each other to forward the message. But some time node may not be interested in forwarding the message. Thus it is essential to give node some incentive to participate in message forwarding game on the basis of credit based system. Our approach based on credit based system as well as coalitional game theory proposes an hybrid approach to solve this issue. Existing message forwarding technique like proportional, receipt counting and Frame have not addressed load balancing issue. We have further extended our system by applying load balancing on credits since we don’t want credit to be concentrated on limited number of nodes. Our proposed approach outperforms all above existing approaches by increasing delivery ratio with 16 to 20% and reducing Virtual Currency Center (Vcc) credit time computation by 46 to 48%.

Eclipse Modeling Framework (EMF) designed especially for models. Eclipse is a platform for building integrated development environments (IDEs) for Java and C programming, websites and other applications. EMF may use for reducing misunderstanding between the customer and development team. Models provide a higher level of abstraction than source code and decrease complexity. The business experts can collaborate directly on the model with developers, rather than communicating through requirements documentation. Model increases the development speed and even more importantly, it increases the implementation quality. The technological stability is an important cornerstone of the project and has attracted many tools and frameworks developers to adopt the Eclipse Modeling Technology. The Eclipse platform is Java-based, but not restricted to Java. C/C++ and Cobol IDEs are being developed. The Eclipse is to provide an IDE that can constantly evolve and adapt. It has some built-in technology, but relies on plug-in tools from software suppliers to address different tasks. It supports repository-based team development, and makes use of open, widely accepted technologies such as Unified Modeling Language, Apache Ant, GTK toolkit for GUIs, Tomcat etc. The Eclipse Integrated Development Environment (IDE) is essential for creating your Android apps.

Smart city is a prominent concept and it is being used in entire world with various contexts. Smart cities provide technological services, cost effective services and optimized services for the stakeholders. Smart solutions can solve the problems of increasing population in cities. In this paper we present the review of few latest IEEE research articles which may help in developing future smart solutions.

It is the ability to examine/write information among specific executions of an utility and between requests. A way to make sure facts persistency for an utility is to apply database software to save records. Large websites and applications that want to do quite a few facts operations rely upon the overall gadget to preserve working even underneath excessive load. One bottleneck for the application is the database overhead incurred while putting and retrieving information. This is described as server-side latency. While on the other hand database development effort and time that might lead you to choose a database that is less complicated to expand code for. RDBMS are currently very popular To examine, which RBMS sever high-quality perfect for required performance depending at the mission. In this paper we will compare the three relational database Oracle, My-SQL and Microsoft Access to evaluate the time taken to do Selection, Projection and be a part of operation at the database and the way lengthy it takes to do such operations on the databases. To do the assessment between the databases, a laptop application turned into developed. The software we use is .Net framework as a laptop consumer. The C#.NET based utility implements methods to insert and retrieve statistics from the relational databases and to evaluate the overall performance of the Select, Project and Join Operations in Oracle, My-SQL and Microsoft Access.

In this paper we discuss about a brief overview of TCP SYN Flood attack which is a type of denial of services attack. Most of the research papers discuss only about theoretical aspect. Main idea of this paper is to use attacker tools for giving the examples of TCP SYN flood attack.

Computer programming is the worldwide language of our earth and a basic literacy in the digital age. There is no doubt that knowledge computer programming at a youthful age is helpful for all students at least in their daily life. The reimbursement of learning programming help adolescent students to gain advantages in thinking, processing and communication. These benefits can support acquiring, mounting and improving the current century skills among youth. One of the main challenges of scientists and enlightening practitioners in the field is how to make computer programming attractive and interesting for the students in primary , secondary schools and educational institutions. The use of various enlightening software could have positive impact on this issue. There are many successful examples of enlightening software used in schools. This paper emphasizes the usefulness education software tools in teaching and learning computer programming fundamentals. Some of the most significant skin tone of such tools, including immediate criticism, visually, and object- oriented programming are explained in details. The author presents several the educational software tools mentioned above can improve teaching , learning computer programming and industry expected from education sector.

Cloud Computing allows users to modify number of resources in real time thus focusing on computing as a utility that can be access over the Internet. We saw various phases starting from Centralized Bulky systems to Distributed Networks and now the emergence of Cloud Computing which is based on Centralized Systems with Internet as the access. Here the vendor i.e. the owner of Cloud is authenticated to provide services to user as per his demand. These Clouds are location-independent and have a flexible pricing model for the user. But for efficient use of these services, these should be properly managed using Capacity Management as a tool. Cloud Computing is only advantageous if Cloud Services are efficiently used

Wireless Sensor Networks have been growing in many areas like healthcare, surveillance, disaster sensing, agriculture, defence, weather forecasting, smart home and manufacturing. A sensor network is a sensor node that is connected spatially to form a network automatically for receiving data transmission among them. The limited resources for wireless sensor networks are real-time transmission with high demands and its processing. In the distributed computing environment, the cloud computing has its own popularity with data processing needs and storage for its cloud environments. Cloud computing can be referred to an era of providing applications, infrastructure and platforms with accessing of shared computing resources over the network. Therefore in the present days, Sensor-Cloud integration provides a high scalable, flexible and open reconfiguration platform for controlling and monitoring the applications.

In information field we have huge amount of data available that need to be turned into useful information. So we used Data reduction and its techniques. A process in which amount of data is minimized and that minimized data are stored in a data storage environment is known as data reduction. By this process of reducing data various advantages have been achieved in computer networks such as increasing storage efficiency and reduced computational costs. In this paper we have applied data reduction algorithms on NSL-KDD dataset. The output of each data reduction algorithm is given as an input to two classification algorithms i.e. J48 and Naïve Bayes. Our main is to find out which data reduction technique proves to be useful in enhancing the performance of the classification algorithm. Results are compared on the bases of accuracy, specificity and sensitivity.

Image enhancement has been an area of active research for decades. Most of the studies are aimed at improving the quality of image for better visualization. Contrast Limited Adaptive Histogram Equalization (CLAHE) is a technique to enhance the visibility of local details of an image by increasing the contrast of local regions. The algorithm is extensively used by various researches for applications in medical imagery. The drawback of CLAHE algorithm is the fact that it is not automatic and needs two input parameters viz., N size of the sub window and CL the clip limit for the method to work. Unfortunately none of the researchers have done the automatic selection of N and CL to make the algorithm suitable for any autonomous system. This paper proposes a novel extension of the conventional CLAHE algorithm, where N and CL are calculated automatically from the given image data itself thereby making the algorithm fully adaptive. Our proposed algorithm is used to study the enhancement of aerial, medical and underwater images. To demonstrate the effectiveness of our algorithm, a set of quality metric parameters are used. In the conventional CLAHE algorithm, we vary the value of N and CL and use the quality metric parameters to obtain the best output for a given combination of N and CL. It is observed that for a given set input images, the best results obtained using conventional CLAHE algorithm exactly matches with the results obtained using our algorithm, where N and CL are calculated automatically.

Electronic Commerce (E-commerce) is the conduct of business activities using electronic data transmission technologies such as those used in the Internet and World Wide Web (WWW). There are different aspects of doing Ecommerce such as Business-to-Customer (B-C), Business-to-Business (B-B), Business –to-Government (B-G) and Customer-to-Customer (C-C). Now a days more and more people participate in E-commerce transactions. The main advantage of E-commerce is that people can save money and time. The financial volume of E-commerce transactions increased to billions of dollars today. People are more concerned about the security of transacting online. Since E-commerce transactions became very common, and the volume of transactions rose high, we need to strengthen the current security facilities. More or less, trust between the trading partners is also very important. Without trust, most people prefer to do traditional methods of doing business. Brands have got a major impact on any kind of business. Emotional brands tries to promote products/services based on emotional appeals of customers rather than specific service offered. Business usually creates an effective web presence to attract visitors and reflect positive images about the organizations among the potential customers.

Water management has become one of the major concerns in many countries. Researchers have proposed different criteria and methodologies for identification of suitable dam sites. Based on our literature review, we have identified three major methodologies for selection of suitable dam site location: Geographic Information System and Remote Sensing (GIS/RS), Hydrological Modelling with GIS/RS and Multi-criteria Analysis (MCA) integrated with HM and GIS/RS. Advantages and disadvantages of each of the methodologies are also mentioned. These methods consider different criteria ranging from those based on only biophysical characteristics to more integrated criteria including socio-economic criteria. Most common criteria used for the selection of suitable dam site were slope, rainfall, land cover, soil type and distance to settlement/road/stream. When more relevant criteria were considered, the suitability site selection tended to be more reliable and accurate. Hence MCA plays an important role.

Engineering Industries (EI), Product Lifecycle Management (PLM) and Engineering Change Management project with the objective of reengineering several business processes and enabling the processes within PLM 4,5,6,8,11,13,16,19,22,24,27,30,35 applications and DMS 21,28,34,36 applications. The Project covers Engineering Industries (EI) such as Energy Devices 21, 28, 34, 36, Telecom devices, automotive global design centers and manufacturing facilities. The design approach will be covering the Engineering industry’s single PLM 4,5,6,8,11,13,16,19,22,24,27,30,35 system platform for entire Organization for design change. Fundamental project management discipline and tools will be used to control, execute, and monitor the EI 4,5,6,8,11,13,16,19,22,24,27,30,35 implementation. All Scope Change Requests will require cost justification and approval of the EI Steering Committee. A monthly Risk Management Report will summarize the risks, identify the mitigating measures necessary and identify respective responsibilities for implementing them. EI’s key objectives for this Project are: • Enable business process and engineering management efficiency through a single integrated global process model. • Achieve the value for Business Value Assessment through below process: • Business Process Management (BPM) • Process transformation and integration • Standardization of business processes • Strong data governance • Increased automation of processes • Expanded process and business system capability • Implement a Common Enterprise platform across EIs design centers in the Americas leading to accurate and timely Business information • Leverage out-of-the-box functionality and minimize system customization.

Anonymous credential systems provide a mechanism for the users to authenticate themselves anonymously. Since the transactions are inherently anonymous, some users try to misbehave by taking advantage of their anonymity. So there is a necessity to formulate some method to stop such users from misbehaving. Also in order to increase the security at the users end we include an additional entity, the trustee that the user trusts.

The incumbent trend in process industry is to use ICT enabled wired process control systems. Distributed control system, Supervisory control and data acquisition systems with wireless open loop control systems are commonly used to facilitate the same. However, wireless closed loop control systems have not yet been introduced in the process industry. In this work, the authors attempt to analyze the enablers of implementing ICT enabled process control system in the process industry and their correlations are established effectively by interpretive structural modelling. This paper attempts to unfold ISM using structural self-interaction matrix, Initial reach ability matrix, and final reach ability matrix. A diagraph is prepared and converted to ISM as the second phase of this research. The paper is concluded with an action plan for enhancing high driving power elements and with managerial implications.