Oriental Journal of Computer Science and Technology An International research journal of Computer Science and Technology

Research in agriculture is increasing quality and quantity, but pest reduces it. To prevent the effect of these pests, insecticides are used. But excessive use of pesticides is very harmful to production and environment. So initially pest detection is necessary. We work on nocturnal pests because that can be easily attracting using night trapping tools. The purpose of this review article is to analyse the popular techniques and find the right technique for the initial diagnosis and early detection of major nocturnal flying pests like Pink Bollworm, White Grub, Helicoverpa and Spodoptera. The importance of early detection can be in identifying and classifying the pests in a digital view. We have concluded our results with the various methods and the prospects of future research.

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Segmentation algorithms play an important role in image processing and analysis. The identification of objects and process monitoring strongly depends on the accuracy of the segmentation algorithms. Waste water treatment plants are used to treat wastewater from municipal and industrial plants. Activated sludge process is used in wastewater treatment plants to biodegrade the organic constituents present in waste water. This biodegradation is done with the help of microorganisms and bacteria. There are two important types of microscopic organisms present in the activated sludge plants, named as flocs as filaments, which are visible under microscope. In this paper we study the microscopic images of wastewater using phase contrast microscopy. The images are acquired from wastewater sample using a microscope. The samples of wastewater are collected from domestic wastewater treatment plant aeration tank. Our main aim is to segment threadlike organisms knows as filaments. Several segmentation algorithms (such as edge based algorithm, k-means algorithm, texture based algorithm, and watershed algorithm) will be explored and their performance will be compared using gold approximations of the images. The performance of the algorithms are evaluated using different performance metrics, such as Rand Index, specificity, variation of information, and accuracy. We have found that edge based segmentation works well for phase contrast microscopic images of activated sludge wastewater.

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In this paper different classification methods are compared using base and meta(Combination of Multiple Classifier for training) level classifiers, for the fruitful diagnosis of Lower Back Pain. The Lower Back Pain becomes chronic with age, so needs to be correctly diagnose with symptoms in the early age. Five independent classifiers were implemented at base level and meta level. At meta level, five combinations of different classifiers were implemented, using voting technique. According to the scores, the overall classification using Naïve Bayes and Multilayer Perceptron got the maximum efficiency 83.87%. The purpose of this paper is to diagnose healthy individuals efficiently. To carry out study the Lower Back Pain Symptoms Dataset is used from very famous platform for predictive modeling, Kaggle. The experiments were carried out in WEKA (Waikato Environment for Knowledge Analysis), suite of machine learning software¹.

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Distributed structure of programming and computing has evolved in all facets of development and spawned a new era of distributed computing. In these structures, the isolated processing nodes have been networked to form a powerful processing and communication device. Now, they need an integrated infrastructure for communication that is capable of providing and developing strong and secure mobility features. The mobile agent technology is becoming a promising solution for widely distributed systems like the Internet. Mobile agent based infrastructure is capable of forming migratory environment efficiently using the network resources. The mobile agent is software code capable of moving closer to the required resource in contrast to systems that incorporate the mobility of non-executable code only. It is also required for various agent-oriented languages to support architectural heterogeneity and less or no dependency on the previous system once an agent is transmitted to another system in the network. This paper reviews the architectural components that exist and required for agent-based systems. It also reviews various software components of universal mobile agent system and explores some aspects of migration and intercommunication of agent-oriented approaches.

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With the continuous advancement in technology, web technologies have reached to a new height. Enterprise applications are meant to be the basic need of today’s world which aims to produce results that are highly reliable, portable and adaptable. With these enormous features, they needed the storage mechanism which could handle and store the data effectively. The storage system thus required was a database management system but again technical knowledge was required to make things work appropriately.  However, this approach was the traditional one which requires data to be stored in tabular format whereas Object oriented architecture has taken the programming language to a whole new technical phase for which the traditional RDBMS will not efficiently accomplish the expected job. To fulfill this gap in the literature, Object Relational Mapping is emerged as a solution to provide which provide comparative technical features effortlessly. These characteristics simplify and make the mapping of objects in object-oriented programming languages more flexible, efficient and easy to use.Therefore, we propose in this paper that Object relational Modeling (ORM) relates each object of object oriented languages to corresponding rows in the table.

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The rapid and revolutionary advancement in technology has increased the demand for advanced ubiquitous mobile applications in our daily lives. Home automation system uses collective smart technology to elevate sphere of security and human living standards. Wireless Smart home systems have been prototyped by researchers to realize different applications in vast contexts. In this paper we propose a keyless smart home security system which uses Bluetooth as a communication protocol to automate door locks based on a security code and predefined user credentials. The system combines Android phone as a signal sender to dispatch the input signal from an end users side, Bluetooth communication module as signal receiver, ARDUINO microcontroller as CPU and servo motor and light emitting diodes as an output. The system integrates two modules: one of which is Arduino microcontroller which is responsible for authentication and verification of security code and allows servo motor to process the output according to the received input. The second is android Application which provides an interface to the user to set credentials and security code which is then transmitted to the Arduino microcontroller via Bluetooth technology. Since Arduino and Android are open source, hence implementation rate of the proposed system is inexpensive and feasible.

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The Shipboard Training in the selected Maritime Institution uses a distributed documentation partially manual process in monitoring the performance of the cadets that most likely causes the delay and inconsistency of reports. Their Department uses any Social Media Website in assessing/validating the reports on the performance of the cadets. The Department of Shipboard Training receives a summary of the report through  Social Media Website.

Technology nowadays is overwhelming that resulted to change faster from a stand-alone system to a web based technology which is capable of supporting almost all of the computerized transactions using an open source mobile applet and Content Management Systems. Most of the organizations have embraced technology and have developed exceptional online programs that provide easy access and massive communication. These maritime schools entirely take after the IMO model courses as proclaimed by the 1978 tradition on Standards of Training, Certification and Watch keeping for seafarers (STCW), as altered in 1995, and are the main ones permitted by our legislature to lead and regulate baccalaureate courses with 3-year scholastics in addition to 1 year managed shipboard apprenticeship for deck and engine cadets.

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Capacitated Vehicle Routing Problem (CVRP) is anoptimization task where customers are assigned to vehicles aiming that combined travel distances of all the vehicles as minimum as possible while serving customers. A popular way among various methods of CVRP is solving it in two phases: grouping or clustering customers into feasible routes of individual vehicles and then finding their optimal routes. Sweep is well studied clustering algorithm for grouping customers and different traveling salesman problem (TSP) solving methods are commonly used to generate optimal routes of individual vehicles. This study investigates effective CVRP solving method based on recently developed adaptive Sweep and prominent Swarm Intelligence (SI) based TSP optimization methods. The adaptive Sweep cluster is a heuristic based adaptive method to select appropriate cluster formation starting angle of Sweep. Three prominent SI based TSP optimization methods are investigated which are Ant Colony Optimization, Producer-Scrounger Method and Velocity Tentative Particle Swarm Optimization (VTPSO). Genetic Algorithm is also considered since it is the pioneer and well-known population based method. The experimental results on two suites of benchmark CVRPs identified the effectiveness of adaptive Sweep plus SI methods in solving CVRP. Finally, adaptive Sweep plus the VTPSO is found better than other tested methods in this study as well as several other prominent existing methods.

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Matching mug shot photos to forensic sketches drawn according to verbal descriptions of eyewitnesses is a decisive point for criminal investigations. However, the incapability of a witness to precisely describe the appearance of a suspect and his/her reliance on a subjective aspect of the description often lead to imprecise and inadequate sketches. This necessitates the development of robust automated matching methods such that least dependency exists on the quality of original sketches. The focus of the paper is on enhancing the preprocessing phase, before the matching phase is applied, by generating a population of sketches out of each initial sketch via applying geometrical changes in facial areas. The population is then optimized using Genetic Algorithms (GA) by adopting the Structural SIMilarity (SSIM) index as the fitness function. The matching is finally applied to the best sketch produced by GA by employing the Local Feature-based Discriminant Analysis (LFDA) framework. The efficiency of the proposed hybrid approach in achieving correct matchings is evaluated against 88 sketch/photo pairs provided by the Michigan State Police Department and Forensic Art Essentials, and 100 sketch/black-and-white photo pairs from FERET database. The experimental results indicate that our proposed approach obtains fairly better results relative to the LFDA framework. Furthermore, we notice a significant improvement in the retrieval rate if sketch/photo pairs are first cropped to central facial areas before a matching technique is applied.

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This study examines the advantages and possibilities for the use of electronic transactions for their market. It focuses on developing and transition countries that have not fully implemented the use of e-commerce in their economic, commercial and productive processes. An important aim of this research is to create awareness on the likely effects for enforcing the use of digital signatures to carry out e-commerce transactions on the economies of developing and transition countries. The study also proposes key issues to be considered for policy-makers in countries in order to consider in fostering the development of e-commerce.

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In 21^st century, the world is largely dependent on information technology where accuracy, speed and reliability have a huge impact. Manual pen and paper work is going to be replaced by computerized systems for more efficient functioning. In the present scenario, it is difficult to keep track the admission status of a candidate on the day of admission, as the number of candidates applied for higher education institutes is gradually increasing. The aim of the research work is to develop a web based application for University Admission Management System (UAMS) where we can computerize a part of University Admission process to make the admission process easy, efficient and user-friendly.

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Cognitive radio (CR) is a novel technology to resolve the issue of under-utilization of wireless spectrum. Quality of service (QoS) provisioning in CR networks to large number of traffic as per their need is not an easy task since no wireless spectrum is available on permanent basis for its operation. In this paper, few critical QoS parameters namely dynamic-availability-of-idle-channels (avail-idle-channel), expected-holding-time-of-idle-channel (HT-idle-channel) and user-mobility are chosen to analyze their impact over quality of service of the communicating cognitive users using rule-based fuzzy decision-making system. The results indicate the relationship of chosen parameters over the QoS of the communicating cognitive users.

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Bio metric technology is now used for employees time management attendance system because it has ability to recognize peoples unique physiological characteristics. Because of multiple benefits of Bio metric attendance system it has gained high popularity in the market. Bio metrics attendance system is extremely useful in helping business community feel secure by eliminating employees time theft, as it relies on ones personal characteristics that vary between individuals.  Since bio metrics characteristics cannot be duplicate, it prevents punching on behalf of a co-worker working in the same company. The manual practice of attendance system is time consuming and needs full time personal monitoring whereas bio metric attendance saves employee time, decreases staffing overhead and provides accurate labor data to payroll system to effectively manage business operations and thereby increase productivity. Moreover the bio metric attendance system has brought transparency and enhanced the work culture in the system. We will explore various advantages and disadvantages of implementation of the bio metric attendance system to a big organization, or small entrepreneur or unit and the necessary measures for its efficient implementation.

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Mobile agents are a very novice field with wider scope of research in the stream of a integrated coherent networks, parallel programming, automated learning, remote execution and artificial intelligence. A mobile agent is a representative that is often treated as moving object developed using any object oriented programming language. Using a WFMS is an emerging current trend in modeling, research methodologies and implementing the information/data flow and various related business processes within an organization. Work is often credited as a task, information, a document, data, announcements or a job that passes through different nodes within an organization. The integration of WFMS involves the automation of various processes such as tasks, documents, processed data, and information or rules to accomplish a task. This automation within the technology can be achieved by integration of agent based technology that makes use of Mobile Agent Paradigm. This paper briefs about various features, benefits and role mobile agents in Workflow management system. This also highlights how the implementation of MAWFMS can smoothen and simplifies the workflow managements in multifarious event based environments.

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Cognitive radio (CR) is a novel technology to resolve the issue of under-utilization of wireless spectrum. There exists number of challenges and issues in designing and implementation of the cognitive radio. Extending quality-of-service (QoS) enabled applications to CR network is even more difficult task due to non-availability of the dedicated allocation of idle spectrum. CR imposes peculiar and unique challenges to guarantee quality of service of diverse flows in contrast to other wireless networks. This paper identifies the issues and challenges of QoS provisioning in cognitive radio networks.

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Various channels have high traffic density during peak hours the problems are further exacerbated by the traffic overloading in downtown areas at peak hours. The reliable and efficient communication demands unnoticed handoff to the user without deteriorating the signal strength. Current cellular system exhibits a varying traffic conditions depending upon the corresponding variations in population which is low in rural areas and high in downtown areas. The traffic density becomes even higher at peak hours and low at night hours. The acceptable service quality demands optimum use of frequency spectrum for obtaining maximum traffic throughput. The efficient allocation of channels on need basis can be one of the solutions for efficient traffic management during peak hours.

In Flexible Channel Allocation scheme (FlCA), the available channels are divided in fixed and flexible set channels. Fixed set channels are normally assigned to all the cells and the number of channels is decided by the approximate calculated load of particular cell that typically suffices the traffic load of cell. The flexible channels are assigned to those cells whose channels are inadequate under increased traffic load conditions. These channels are assigned in accordance with demand of increased traffic loads. Fuzzy logic approach being flexible is explored for assigning these flexible channels for enhanced QoS.

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This research implements Image processing to reduce the size of image without losing the important information This paper aims to determine the best wavelet to compress the still image at a particular decomposition level using wavelet packet transforms.

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The proponents of this study proposed the idea of making a LAN-Based Vehicle Information System to improve the conventional method of record administration for Engine Vehicle Enlistment Office. The illustrative strategy for inquire about was connected to the investigation. Research and meetings were led to fortify the assumption of issues and hidden issues on various zones of the ebb and flow data framework were found in light of the respondent's answers. The LAN-Based Vehicle Data framework won't just evaluate yet will likewise lighten the issue and tedious procedure of the old framework. Also, the proposed framework would yield ongoing procedures and more advantageous. The goal of this examination is to have a data framework that is more proficient and bother free in record administration. The investigation presents advancement of data frameworks from the conventional to the top of the line innovation. Uncovering the mechanics of the said framework and displaying information upheld points of interest that can be picked up utilizing LAN-Based Data Framework. Sorted out interface and usefulness gives speed and productivity, end of problem and lessen of time.

The MVRO (Motor Vehicle Registration Office) is a department that is in charge of regulating the transportation in Subic Bay Freeport Zone. It systematizes the transportation inside the SBFZ and has 275 registered taxis aside to 500 registered shuttle buses, public utility vehicles and company vehicles. According to the Officer-In-Charge of MVRO,  Mrs. Marietta Fe S. Dumlao, their database only reside to excel and not organized to the various categories of the registered vehicles

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Nowadays, most of paper based exams are converted to computer based exams. Such conversion requires a significant robust security issues.  The security issues are not limited to the authentication of the exam invigilators, and provided identification card. Improving the computer based exams is a challenging task, where focusing on user authentication ways is the main core to have a robust secure exams. This paper introduces a new methodology of authentication based on biometric iris recognition system for Qiyas exams in Saudi Arabia.

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The purpose of the present research is to propose a detailed analysis of a fragment of a passive memristor memory crossbar. For computer simulations a previously proposed by the authors in another paper nonlinear dopant drift memristor model with a modified window function is now applied. The results obtained by the simulation are compared with experimentally recorded current-voltage relationships and with these derived by the use of several basic memristor models as well. A relatively good coincidence between the results is established. The fragment of a memristor memory crossbar is simulated for the procedures of writing, reading and erasing information in the memristor cells. The effect of the basic memristor parameters, as the ionic drift mobility, the ON and OFF resistances and the physical length of the element on its switching speed is discussed. After a number of simulations, it was established that due to the self-rectifying effect the parasitic sneak paths do not strongly influence the normal operation of the memristor memory crossbar. It is confirmed that the model with a modified Biolek window function proposed in our previous research could be used for simulations of complex memristive electronic circuits for hard-switching.

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While the current IT plethora is replicating enormous data and it need to have tremendous
processing power by the servers to maintain this valuable data and storages. Therefore in order
to provide ease to data storage Erasure coding exhibits much success in the area of data mining
as it can reduce the space and bandwidth overheads of redundancy in fault-tolerance delivery
systems, so the exploration of erasure coding in concurrency with the metadata will be appreciable;
Research also on the other side of the coin shows as few have analyzed the understanding of
consistent hashing too will proved productive for certain related issues and also the neural
networks can be used for maintaining and exploring new data sciences in order to provide
encouraging frameworks in managing infinite volumes of data we have at our disposal. In this
work, we prove the visualization of simulated annealing in order to render solution at global
maxima and provide provision of improvements to the specified framework or model. We also
analyzed and state the disconfirmation about the fact that write-back caches and neural networks
are never incompatible

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It is widely recognized that the threat to enterprises from insider activities is increasing and
that significant costs are being incurred. The multi-faceted dimensions of insider threat and
compromising actions have resulted in a diverse experience and understanding of what insider
threats are and how to detect or prevent them. The purpose of this research is to investigate the
potential for near real-time detection of insider threat activities within a large enterprise environment
using monitoring tools centred on the information infrastructure. As inside threat activities are not
confined solely to cyber-based threats, the research will explore the potential for harnessing a
variety of threat indicators buried in a different enterprise operations connected or interfacing with
the information infrastructure, while enabling human analysts to make informed decisions efficiently
and effectively.

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This article recounts research-in-progress which attempts to account for a paradigm
shift in Indian design education. The research also explores features that need to be rooted and
nurtured in the foundation year of design education to be suitable for the realities of life in 21st century
India. This foundation year has had diverse titles including “Design Fundamentals” or “Basic Design”.
The foundation year began at the Bauhaus and evolved after 1945 at the Hochschule für Gestaltung,
Ulm and the Academy of Art and Design Basel (HGK Basel). In its emergent period design was
concentrated on discrete products including industrial goods, textiles, ceramics, architecture and
graphic design. Today, however, to be pertinent to concurrent society, designers need to work on
convoluted issues that are interdisciplinary and much comprehensive in scope. 21st century design
education needs to be able to apply design and develop strategies to solve actual issues and not
just look at “good form”. There is also a visible shift from client-driven projects towards a more
reflective “issue-based” design education that strives for more socially inclusive, locally/glocally/
globally relevant solutions: a move from “human-centric design” to “life-centric design”. The research
to date incorporate an overview of the history of design education in India from its European origins
and a literature scrutiny of both formal (books, papers, and reports) and informal sources (blogs and
emails) to justify and reinforce the argument for change. Identification of central issues to contemporary
design education is based in-depth interviews and emphasize group discussions. The interviews
and discussions were with design educators and professional designers who interact with design
students as mentors or share a common con-cern for design education. Deliberations on design
and insights into future directions were congregated from confer-ence and seminar recordings. The
complications of the Indian people, both nationally and locally, within the mesh of cultural diversity
with eco-nomic discrepancy-ncluding health, transportation, housing, agricultural support, safe
water provision, to mention some of the many sectors—are areas which offer potential for the
designer to make a contribution in finding panacea to the wide range of problems facing India. It is
important for designers to comprehend the complexity of issues at stake as well as being aware of
“intangibles” like values, social responsibilities, empa-thy, humility, and local/global relevance. When
design education includes political, social, economic and eco-logical discourses in a collaborative,
inter/multidisciplinary way perhaps then design can participate actively in nation building.

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In this paper, the Eighteenth Order Convergent Method (EOCM) developed by Vatti et.al is considered and this method is further studied without the presence of second derivative. It is shown that this method has same efficiency index as that of EOCM. Several numerical examples are given to illustrate the efficiency and performance of the new method.

AMS Subject Classification: 41A25, 65K05, 65H05.

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An injective function g:V(G)→{F₀,F₁,F₂,...,F_n+1},where F_jis the jth Fibonacci number(j=0,1,...,n+1), is said to be Fibonacci cordial labeling if the induced functiong∗: E(G) →{0,1}defined by g ∗(xy)=(f(x)+f(y)) (mod2) satisfies the condition |e_g(1)−e_g(0)|≤1. A graph having Fibonacci cordial labeling is called Fibonacci cordialgraph. In this paper, i inspect the existence of Fibonacci Cordial Labeling of DS(Pn),DS(DFn),EdgeduplicationinK_{1, n},Jointsum ofGl(n),DFn⊕K_1,nand ring sum of star graph with cycle with one chord and cycle with two chords respectively.

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Today internet has become a trusted factotum of everyone. Almost all payments like tax, insurance, bank transaction, healthcare payment, payment in e-commerce are done digitally through debit or credit card or through e-wallet. People share their personal information through social media like Facebook. Twitter, WhatsApp etc. The government of every developing country is going to embrace e-Governance system to interact with people more promptly. The information shares through these applications are the burning target to intruders. This paper utilized the imperceptibility as well as the robustness of steganography techniques which are increased by embedding multiple bits in a particular region selected either based on some image attributes or by Human Visual Perception.

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Day by day, data is growing rapidly. Analysis of the data is necessity. As per recent survey data generated in last 2 years is more than the data created in entire previous history of human. Data created in different form and in diversified manner. It can be structured, it can be semi-structured, or it can be unstructured. To analyze diversified by agricultural data we can use the tools of Big Data like Pig. Using Pig, we can analyze varieties of data. Pig is a platform for analysis of data. Biggest advantage of Pig is it can process any diversified data very quickly and allows us to use user defined functions. Use Case of Pig is ETL. It is used to extract the data from sources then after applying transformation we can load it into the data warehouse. We will do analysis of state wise proportion circulation of Numeral of operative properties for all societal collections in 2005-06 and 2010-11 using Pig.

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For last two decades, the demand for wireless spectrum has been increasing rapidly with tremendous developments in the telecom industry. There also has been huge growth in flow of multimedia traffic over the last decade. Thus, the demand for additional bandwidth is increasing exponentially despite the fact that the electromagnetic spectrum is a finite resource. On the other hand, spectrum occupancy is found to be quiet low in most of the allocated bands. Thus, the under-utilization of the precious spectrum is unaffordable if persistent growth of new and existing wireless services are to be sustained. Cognitive radio (CR) is a future technology initiated by many research organizations and academic institutions to increase the spectrum utilization of underutilized spectrum channels to ameliorate scarcity problem of valuable electromagnetic spectrum. There exists number of issues and challenges in designing and implementation of the cognitive radio. These issues need to be rigorously resolved before a cognitive radio is realised.

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To measure testability before the actual development starts will play a crucial role to the developer, designers and end users as well. Early measurement of testability, especially in early requirement stage to assist the developer for the further development process, and will also assures us to produce and deliver the high quality requirement that can surely reduce the overall cost and improves the quality of development process. Taking view of this fact, this paper identifies testability estimation factors namely understandability and modifiability and establishes the correlation among testability, understandability and modifiability. Further, a model is developed to quantify software testability in requirement phase and named as Requirement Testability Model of Object Oriented Software-RTM^OOS. Furthermore, the correlation of Testability with these factors has been tested and justified with the help of statistical measures.

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Data mining has become one of the emerging fields in research because of its vast contents. Data mining is used for finding hidden patterns in the database or any other information repository. This information is necessary to generate knowledge from the patterns. The main task is to extract knowledge out of the information. In this paper we use a data mining technique called classification to determine the playing condition based on the current temperature values. Classification technique is a powerful way to classify the attributes of the dataset into different classes. In our approach we use classification algorithms like Decision Tree (J48), REP Tree and Random Tree. Then we compare the efficiencies of these classification algorithms. The tool we use for this approach is WEKA (Waikato Environment for Knowledge Analysis) a collection of open source machine learning algorithms.

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Cognitive radio is a future technology coined for increasing the utilization of otherwise under-utilized spectrum channels. Providing quality of service (QoS) to diverse flows as per their requirements is a very difficult job as there is no dedicated allocation of wireless channels in cognitive radio (CR) network. The paper selects few critical QoS parameters such as signal-strength, bandwidth and user-mobility that assess the influence on quality of communication between users using rule-based fuzzy inference system. The analytical results show the influence of those QoS parameters on the quality of communicating channels and open new issues in designing protocol structure for CR.

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Presence of missing values in the dataset leads to difficult for data analysis in data mining task. In this research work, student dataset is taken contains marks of four different subjects in engineering college. Mean, Mode, Median Imputation were used to deal with challenges of incomplete data. By using MSE and RMSE on dataset using with proposed Method and imputation methods like Mean, Mode, and Median Imputation on the dataset and found out to be values of Mean Squared Error and Root Mean Squared Error for the dataset. Accuracy also found out to be using Proposed Method with Imputation Technique. Experimental observation it was found that, MSE and RMSE gradually decreases when size of the databases is gradually increases by using proposed Method. Also MSE and RMSE gradually increase when size of the databases is gradually increases by using simple imputation technique. Accuracy is also increases with increases size of the databases.

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Cognitive radio (CR) is a promising solution to improve the spectrum utilization by enabling unlicensed users to exploit the spectrum in an opportunistic manner. Spectrum handoff is a different type of handoff in CR necessitated by the reappearance of primary user (PU) in the licensed band presently occupied by the secondary users (SUs). Spectrum handoff procedures aim to help the SUs to vacate the occupied licensed spectrum and find suitable target channel to resume the unfinished transmission. The purpose of spectrum mobility management in cognitive radio networks is to make sure that the transitions are made smoothly and rapidly such that the applications running on a cognitive user perceive minimum performance degradation during a spectrum handoff. In this paper, we will survey the literature on spectrum handoff in cognitive radio networks.

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Now a day’s usage of android applications has become a part of our life. By using these applications our work becomes simple and easier in our day to day activities. This paper suggests an android application which is generally useful for the students and parents. It contains various features like notifying the student about the renewal date of library books, alerting students and their parents about the percentage of attendance and reminds them about number of classes they should present to maintain the specified attendance threshold. This application also alerts the students and parents about various events like examinations, workshops to be held, student activities to be conducted etc. This application is user friendly and can be installed in any android smart phone

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Practical effort estimation is very basic and most essential aspect of very organisation to sustain better project management. Accuracy in efforts makes the organisation to surge its business and build motivation among its customers effectively. It was observed that continuous improvement is required for software effort assessment after regular eras.The fundamental point of this examination work is to assess the execution of Re-UCP strategy for estimation of efforts for web application projects. This research work compares the existing effort estimation model results with the Re-UCP effort estimation methods results for web application development projects.

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Data Warehouse design requires a radical rebuilding of tremendous measures of information, frequently of questionable or conflicting quality, drawn from various heterogeneous sources. Data Warehouse configuration assimilates business learning and innovation know-how. The outline of theData Warehouse requires a profound comprehension of the business forms in detail. The principle point of this exploration paper is to contemplate and investigate the transformation model to change over the E-R outlines to Star Schema for developing Data Warehouses. The Dimensional modelling is a logical design technique used for data warehouses. This research paper addresses various potential differences between the two techniques and highlights the advantages of using dimensional modelling along with disadvantages as well. Dimensional Modelling is one of the popular techniques for databases that are designed keeping in mind the queries from end-user in a data warehouse. In this paper the focus has been on Star Schema, which basically comprises of Fact table and Dimension tables. Each fact table further comprises of foreign keys of various dimensions and measures and degenerate dimensions if any. We also discuss the possibilities of deployment and acceptance of Conversion Model (CM) to provide the details of fact table and dimension tables according to the local needs. It will also highlight to why dimensional modelling is preferred over E-R modelling when creating data warehouse.

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The review and comparative analysis of the methods of compression and recognition of speech signals is carried out. The result of the carried out analysis of the existing recognition methods indicates, that all of them are based on the use of “inflexible” algorithms, which are badly adapted to the characteristic features of speech signals, thus degrading the efficiency of the operation of the whole recognition system. The necessity of the use of algorithms for determination of recognition features along with the use of the wavelet packet analysis as one of the advanced directions of the creation of the effective methods and principles of the development of the speech signals recognition systems is substantiated.

Analysis of the compression methods with the use of the orthogonal transformations at the complete exception of minimal decomposition factors is conducted; a maximal possible compression degree is defined. In this compression method the orthogonal transformation of the signal segment with the subsequent exception of the set of the smallest modulo decomposition factors, irrespective of the order of their distribution, is conducted. Therefore the additional transfer of the information on the factors distribution is required.

As a result, two information streams appear, the first one corresponds to the information stream on the decomposition factors, and the second stream transfers information on the distribution of these factors.

Method of the determination of the speech signals recognition features and the algorithm for nonlinear time normalization is proposed and proved.

Wavelet-packet transformation is adaptive, i.e. it allows adapting to the signal features more accurately by means of the choice of the proper tree of the optimal decomposition form, which provides the minimal number of wavelet factors at the prescribed accuracy of signal reconstruction, thus eliminating the information-surplus and unnecessary details of the signals.

Estimation of the informativeness of the set of wavelet factors is accomplished by the entropy. In order to obtain the recognition factors, the spectral analysis operation is used. In order to carry out the temporary normalization, the deforming function is found, the use of which minimizes the discrepancy between the standard and new words realization.

Dedicated to the determination of admissible compression factors on the basis of the orthogonal transformations use at the incomplete elimination of the set of minimal decomposition factors, to the creation of the block diagram of the method of the recognition features formation, to the practical testing of the software- methods. In order to elevate the compression factor, the adaptive uniform quantization is used, where the adaptation is conducted for all the decomposition factors. The program testing of the recognition methods is carried out by means of determination of the classification error probability using Mahalanobis (Gonzales) distance.

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Extending the Internet to connect any physical device with smart technology can be called as the Internet of Things (IoT).It is a proposed development of the Internet in which everything can be connected to the internet enabling them to send and receive data. Selection of energy efficient routing protocols has become an essential step in designing any IoT network. Moreover, the protocol should also be selected to enhance the lifetime of the network. In this article, we evaluate the performance analysis of DEEC (Distributed Energy Efficient Clustering), DDEEC (Developed DEEC), EDEEC (Enhanced DEEC) and TDEEC (Threshold DEEC) for the application in IoT. From MATLAB simulation, it was observed that TDEEC outperforms other routing protocols and is well suited for IoT application.

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The main thrust of the study is to develop a cloud-based application performance monitoring system of the cadets while on board ship training for the Philippine Merchant Marine Academy in San Narciso, Zambales which intended to serve as an alternative system that can be used by the target school in monitoring the performance of the cadets while on ship board and determine its effectiveness.

The researcher has used the descriptive research method wherein the study is focused on the present situations. It involves the recording, description and the presentation of the present system, composition and phenomena.

The Statement of the problem focused in obtaining the effectiveness of the proposed cloud based application in performance monitoring system of the cadets for the Philippine Merchant Marine Academy, San Narciso, Zambales.

Findings showed that the Department of Shipboard Training needs a real time system that can monitor the cadets while on board ship training. Based on the conclusion of this study, the researcher recommends the development of the cloud based application which will monitor the performance of the cadets while on board ship training and lastly, the developed system was tested during the implementation and met no errors.

Based on the findings, the number of respondents as group per course is in parallel to the ratio of the students currently enrolled at PMMA. Majority of the respondents for both the groups came from the existing Group whose ages range from 19-21 years old.As revealed, the majority of the respondents for both the groups are males from the Proposed Group.

In the proposed system out of one hundred percent respondents, thirty or 93.5% cadets; while the officials are nine or 6.5% of the one hundred, from the total of thirty-nine respondents.

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A new framework recognition system for identifying the missed pilgrims in Hajj and Umrah is presented in this paper. The framework recognition system is based on the Wavelet Probabilistic Neural Network (WPNN) classifier. The entire framework recognition system is capable of identifying the missed pilgrims. The framework recognition systems is developed as an application for mobile phones The proposed framework recognition system is applied to a huge database for pilgrims in the Ministry of Hajj Computer server for matching and identifying the missed pilgrim. The results are superior comparing to the existing systems

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The authors show that in a Built-In Self-Test (BIST) technique, based on linear-feedback shift registers, when the feedback connections in pseudo-random test-sequence generator and signature analyzer are images of each other and corresponds to primitive characteristic polynomial then behaviors of faults masking remains identical. The simulation results of single stuck-at faults show how the use of such feedback connections in pseudo-random test-sequence generator and signature analyzer yields to mask the same faults.

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In a recent era of modern technology, there are many problems for storage, retrieval and transmission of data. Data compression is necessary due to rapid growth of digital media and the subsequent need for reduce storage size and transmit the data in an effective and efficient manner over the networks. It reduces the transmission traffic on internet also. Data compression try to reduce the number of bits required to store digitally. The various data and image compression algorithms are widely use to reduce the original data bits into lesser number of bits. Lossless data and image compression is a special class of data compression. This algorithm involves in reducing numbers of bits by identifying and eliminating statistical data redundancy in input data. It is very simple and effective method. It provides good lossless compression of input data. This is useful on data that contains many consecutive runs of the same values. This paper presents the implementation of Run Length Encoding for data compression.

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One of the most common methods of communication involves the use of e-mail for personal messages or for business purposes. One of the major concerns of using the emails is the problem of e-mail spam. The worst part of the spam emails is that, these are invading the users without their consent and bombarding of these spam mails fills up the whole email space of the user along with that, the issue of the wasting the network capacity and time consumption in checking and deleting the spam mails makes it even more concerning issue.  With the increasing demand of removing the e-mail spams the area has become magnetic to the researchers. This paper intends to present the performance comparison analysis of various pre-existing classification technique. This paper discusses about spam mails in section (I), In section (II) various feature selection methods are discussed , In section (III) classification techniques concept in spam filtering has been elaborated, In section (IV) existing algorithms for classification are discussed and are compared. In section (V) concludes the paper giving brief summary of the work.

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Agriculture is a gigantic sector of the Indian economy as its share to gross domestic product (GDP) is almost 17 per cent. Over 60 per cent of the population adopts agriculture as main occupation. In spite of a large of Indian economy, agriculture is lagging behind many aspects and characterised by poor connectivity and disintegration of market, unreliable and delayed information to the farmers, small land holdings, non adoption or less adoption of improved technology and so on. It has become indispensable to explore various ways to keep our farmers updated about modern technologies and relevant information. The development and timely dissemination of better personalized technologies specific to different agro-climatic conditions, size of land holding, soil type, type of crops and related pests/diseases is the real issue to brazen out ahead for the agricultural scientists/experts. The timely availability of right information and its proper utilisation is indispensable for agriculture. ICT based initiatives can be taken for propagation of information, transfer of technology, procurement of inputs and selling of outputs in a way so that farmers can be benefitted. The timely information and practical solutions of the agricultural problems helps the farmers to adopt good agricultural practices, make better choices of inputs and to plan the cultivation properly.

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Maturity checking has become mandatory for the food industries as well as for the farmers so as to ensure that the fruits and vegetables are not diseased and are ripe. However, manual inspection leads to human error, unripe fruits and vegetables may decrease the production [3]. Thus, this study proposes a Tomato Classification system for determining maturity stages of tomato through Machine Learning which involves training of different algorithms like Decision Tree, Logistic Regression, Gradient Boosting, Random Forest, Support Vector Machine, K-NN and XG Boost. This system consists of image collection, feature extraction and training the classifiers on 80% of the total data. Rest 20% of the total data is used for the testing purpose. It is concluded from the results that the performance of the classifier depends on the size and kind of features extracted from the data set. The results are obtained in the form of Learning Curve, Confusion Matrix and Accuracy Score. It is observed that out of seven classifiers, Random Forest is successful with 92.49% accuracy due to its high capability of handling large set of data. Support Vector Machine has shown the least accuracy due to its inability to train large data set.

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The present research effort analyses various application areas of risk oriented testing and indentifies the gaps from the past .We need risk oriented testing not only for identifying risks in the projects but also for the maximum optimization of resources .Our research stresses on risk oriented testing in pervasive and evolutionary computational areas as due to dynamicity of such computing environment ,the project imbibes risk in great measure and needs to be taken care in early stages of the project .  Risk oriented testing requires concentration in both of these application areas as extremely little work has been done in this regard.

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