Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Requirement & Performance Factors of Business Intelligence Through Web Mining

: The world wide web is a popular and interactive medium to distribute information in the era. The web is huge , diverse and ever changing information service center. Web deals with e-commerce, e-governance, e-finance, e-learning, e-banking etc for fulfilling the customer’s requirement. To deal with e terms there is need of intelligent strategies in order to maintain the direct contact with the customers. Web mining is the field of the data mining which answers about different materialized issues of business intelligence which include marketing expertise as domain knowledge and are specifically designed for e commerce purpose. This paper provides an introduction to the field of web mining and examines existing as well as potential web mining application that are applicable for business intelligence functions, like marketing, human resources, fiscal administration. We are using the visualization to visualize the business intelligence functions that are affected by web mining techniques in the form of 2-D graphs. In this we are analyzing the output obtained from the tools to prove the existence of business intelligence in every kind of the website and provide some suggestion in order to move in this very direction
Fuzzy Set Theoretic Approach To Collocation Extraction

Fuzzy approach deals with the linguistic properties of elements such as beauty, coldness, hotness etc. Collocations are linguistically motivated. Decision of word combination for being collocation is a linguistic term as merely co occurrence of word combinations does not signify the presence of collocation. Thus collocation extraction can be made possible by looking its linguistic aspect. In the present paper, an attempt has been made to make two different fuzzy sets of word combinations to be considered for collocations. Mutual information and t-test have been taken as basis for the construction of fuzzy sets. Two fuzzy set theoretical models have been proposed to identify collocations. It has been shown that fuzzy set theoretical approach works very well for collocation extraction. The working data has been based on a corpus of about one million words contained in different novels constituting project Gutenberg available on www.gutenberg. org.
ADOPTION OF CYTOCHROME B AS A MEANS TO IDENTIFY THE SOURCE OF DNA USING POLYMERASE CHAIN REACTION

The present study was aimed to determine the type of biological material of unknown origin through the cytochrome b gene besides PCR, and this is important for samples for forensic medicine lawsuits involved in the investigation Criminal, as the forensic task to resolve the issues in routine casework, sometimes it is necessary to identify the exact species of the biological material. Samples, which included several isolates of Pseudomonas aeruginosa and blood of different animal sources included (rabbits, chickens, sheep), human blood and corpses tissue. It was detected amplification of the gene coding for the types of product covered by the study, where P.aeruginosa gave the package, which appeared the size of 460 base pairs. As was detected amplification of the gene coding for the following kind of product (Sheep, chickens, rabbits), where the given package size 331, 227, 740 base pairs respectively. The product amplification of the gene coding for the type of human gave specialist pack size of 580 base pairs for each of the blood and corpses tissue samples.
Enhancement of Biometric Template Security in Multibiometric Systems

Security is a very important aspect in the biometric systems. Biometric characteristics are unique to an individual hence the compromise of the biometric template is permanent. Attackers mostly attack on template and database of biometric system so securing them is a very crucial issue these days. Moreover the multibiometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. In this research paper our focus is on template security in biometrics system and we develop a system to encrypt and decrypt the biometric images. In this work, multi-modal biometric template security for palm print and fingerprint is proposed. At first, the preprocessing steps are applied and subsequently, the features are extracted and combined to simultaneously protect multiple templates. Then different cryptographic techniques are used to encrypt it to make it secure so that even if someone gains access to the encrypted image stored in the database he will not able to reproduce the
JPEG Image Transmission over Rayleigh Fading Channel with Unequal Error Protection

In this paper an image transmission system has been proposed where Joint Photographic Experts Group (JPEG) algorithm is used as an image coder and Rate Compatible Punctured Convolution (RCPC) channel coder is used for transmission of coded image over wireless channels (AWGN and Rayleigh fading). JPEG bit stream is partitioned into DC and AC bit streams. AC bit stream further classified using edge density property of block. Priorities based Unequal error Protection (UEP) applied to bit stream. Distortion analysis (MSE) is given for proposed image transmission scheme. The simulation results shows reduction in distortion compared to conventional Equal Error Protection (EEP). This proposed algorithm can be applied for low frequency as well as high frequency images. General Terms Image Coding and transmission through wireless channel
Empowerment‐based education for established type 2 diabetes in rural England

People with newly‐diagnosed type 2 diabetes are offered structured education, but there are few programmes for those with established diabetes. The empowerment‐based education approach from the United States has been advocated as one approach that supports self‐management, but is not used in England. The aim of this study was to assess the acceptability of empowerment‐based diabetes education for patients with established type 2 diabetes.
Analytical Modeling of Social Network Growth Using Multilayer Network Projection

In this study, we present a new network model to address the question of how social networks such as groups in social websites, networks of social events, online video game groups evolve in time. A common feature of all these networks is that first, new users attach to an existing group (clique), and second, the decision of new network users is greatly influenced by already-joined users. In our model, new user joins the underlying network from a parallel network layer as the consequence of influence of underlying network users on the ones from other networks. This influence could be any type of relationship exterior to the underlying network layer such as friendship. For the new network model design, we utilize the concepts behind: 1. Growing network model presented by Barabási–Albert (BA), 2. Social influence-driven contagion model and 3. Multiplex network model. The way we treat this challenging phenomena is by multilayer projection, i.e. friends of each actual user that exist in other social network layers are projected as virtual users onto the underlying network layer. At each time step, each virtual user might become actual user based on a proposed Social influence-driven contagion method.
Improving Distance Based Unsupervised Outlier Detection using Anti-hubs

As the dimensionality of the data increases due to this all point becomes good outlier the distance based outlier detection methods fails. Reason of these issues is irrelevant and redundant features; nearest neighbor of the point P is K points whose distance to point P is less than all other points. Reverse nearest neighbors (RNN) of Point P is the points for which P is in their k nearest neighbor list. Some points are frequently comes in k-nearest neighbor list of another points referred as hubs and some points are infrequently comes in k nearest neighbor list of different points are called as Anti-hubs. Recent research proposes anti-hub based unsupervised outlier detection methods but these propose are suffered from computation cost of finding anti-hubs. In the case of data which has outstanding dimensionality, computation cost and time requirement to find anti-hubs is high. There is need to remove the redundant features if high dimensional data contains redundant attributes. Reduce the computation cost and time requirement by removal of redundant features to find anti-hubs for outlier detection. For extending anti-hub based outlier detection method for high dimensional data apply feature selection.
Enhancing Security in Biometric System Using Blind Authentication Protocol

Biometric authentication system are used prevalently for its template security, retract ability and privacy. The Authentication process is reinforced by biometric cryptosystem. We propose a demonstrable secure and blind biometric authentication protocol which discloses only identity and not any other information to both client and server. To reduce the computational cost and enhance security we have used ElGamal. It is based on asymmetric encryption in which biometric authentication and security of public key cryptography is enhanced. Authentication protocol works on public network and provides template protection, ability to retract template protection and assuage the concern on privacy. In our approach the authentication in the encrypted domain does not affect the accuracy, while the encryption key bolsters security.
Incentives for Online Communities

—Online communities promote wide access to a vast range of skills and knowledge from a heterogeneous group of users. Yet implementations of various online communities lack consistent participation by the most qualified users. Encouraging such expert participation is crucial to the social welfare and widespread adoption of online community systems. Thus, this research proposes techniques for rewarding the most valuable contributors to several classes of online communities, including question and answer (QA) forums and other content-oriented social networks. Overall, novel quantitative incentives can be used to encourage their participation. Using a game theory approach, this research designs and tests an incentive mechanism for QA systems. Based on survey data gathered from online community users, the proposed mechanism relies on systemic rewards , or rewards that have tangible value within the framework of the online community. This research shows that human users have a strong preference for reciprocal systemic rewards over traditional rewards. Furthermore, this research shows that it is possible to motivate participation from the most valuable contributors to an online community.
Investigating Relationship between Job Burnout and Organizational Commitment among Extension Workers in Kurdistan Province, Iran

In developing countries agricultural extension workers face many constraints such as poor working conditions and unfavorable government policy support for agriculture. This study aimed to identify the level of job burnout among extension workers and its relationship with organizational commitment. Using random sampling technique 55 extension workers were selected as sample, which represented 51.40% of the population. The research method was descriptive-corelational. In this research, Allen and Meyer’s organizational commitment scale and Maslach’s burnout inventory were used for data collection. The study found that extension workers experience moderate levels of emotional exhaustion, depersonalization and personal accomplishment in their work. Moreover, the results of Pearson's correlation coefficient test revealed that affective commitment and normative commitment was inversely correlated with emotional exhaustion and depersonalization and positively correlated with personal accomplishment. In addition, continuance commitment was positively correlated with emotional exhaustion and depersonalization. No significant relationship was observed between continuance commitment and personal accomplishment.
Performance Evaluation of Routing Protocol for Mobile Ad-Hoc Network

MANET is the compilation of wireless portable nodes which dynamically arranges a short term network without the use of any centralized administration or network infrastructure. Routing protocols used in mobile ad hoc networks must mechanically change to environments that can vary between the extremes of low mobility with high bandwidth, high mobility with low bandwidth. Various secure routing protocols are proposed for mobile ad hoc networks. In this paper, a performance analysis of three MANET routing protocolsAODV, DSR and Sec-AODV are performed. AODV routing protocols was selected on the basis of the intact simulations. Due to the needs of securing the routing in the wireless ad hoc networks, Sec-AODV protocol is proposed and is developed to add security to original AOD. It includes cryptographic operations based on private key cryptography for packet authentication that can have an imperative impact on the routing performance.
Handling Handling Handling Handling UncertaintyUncertaintyUncertaintyUncertainty Information through Extended Information through Extended Information through Extended Information through Extended ClassifiersClassifiersClassifiersClassifiers

The data whose values are precise is known as certain data whereas uncertain data is the data whose values are not precise. It does mean that value of a data item is represented by multiple values. The traditional data mining algorithms, especially classifiers work on certain data. They can’t handle uncertain data. This paper extends traditional decision tree classifiers to handle such data. We understood that the simple mean and median of uncertain values can’t give accurate results. For this reason this paper considers Probability Distribution Function (PDF) to improve the accuracy of decision tree classifier. It also proposes pruning techniques to improve the performance of the classifier. Empirical results show that, when compared to algorithms that use averages of uncertain values our algorithm is more accurate. However, it is computationally more expensive as it has to compute PDFs. Our pruning techniques help in reducing the computational cost.
Randomized Algorithms: Methods and Techniques

Randomized Algorithms are now gaining the attention of researchers. The reason is that some of the randomized algorithms have been successfully implemented in important applications reducing the time complexity and other computing resources. This paper reviews the different methods and techniques available in randomized algorithms. Paper also gives the gaps in the existing research and the future scope of research in this area.
A Comparative Analysis and Evaluation of Different Agile Software Development Methodologies

Numbers of Information System development methods or agile software development methodologies are in practice. When any organization is going for IS development they will be looking for the IS development methods that are most complete and/or significant and also to fulfill their requirements and give them a complete solution. Agile software development methods have made their way into the software mainstream and have got the attention of software engineers and researchers due to their rapid growth. The purpose of this paper is to compare and investigate the three most practiced methods, that is Extreme Programming, Rational Unified Process and Dynamic System Development Method by using the Multi Criterion Decision Making tool. In addition, we analyze them on the basis of different aspects in order to find out which one is the most complete and significant technique for the development of Information System.
Throughput Optimal Power Allocation in Multi -Relay MIMO-CN in MANET

-Cooperative communication has derived an interest for wireless network. Most existing works on cooperative communications are focused on link-level physical layer issues such as topology control, routing and network capacity are largely ignored Although there have been extensive studies on applying cooperative networking in multi-hop ad hoc networks, most works are limited to the basic three-node relay scheme and single-antenna systems. These two limitations are interconnected and both are due to a limited theoretical understanding of the optimal power allocation structure in MIMO cooperative networks (MIMO-CN) In Proposed system we use Cooperative diversity. It is a cooperative multiple antenna technique for improving or maximizing total network channel capacities for any given set of bandwidths which exploits user diversity by decoding the combined signal of the relayed signal and the direct signal in wireless multi hop networks. Also we show that physical layer cooperative communications have significant impacts on the network capacity, and proposed topology control scheme can substantially improve the network capacity in MANETs with cooperative communications.
A Comparative Study of Active-Learning Techniques for Classification of Remote Sensing Images

— The success of remote sensing image classification techniques is based on defining an efficient training set. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. Active learning is an active research area within the machine learning community, and is now being extensively used for remote sensing applications. To make remote sensing image classification effective the training set should be as small as possible and must include highly informative pixels. Active learning heuristics provide capability to select “most informative” unlabeled data and to obtain the respective labels, fulfilling both goals. The investigated techniques exploit different query functions, which are based on the evaluation of two criteria: uncertainty and diversity. The combination of the two criteria results in the selection of the potentially most informative set of samples at each iteration of the AL process. This paper investigates different active learning (AL) techniques for the classification of remote sensing (RS) images with support vector machines.
OPTIMIZATION OF CULTURE CONDITIONS FOR POLY Â- HYDROXYBUTYRATE PRODUCTION FROM ISOLATED BACILLUS SPECIES

The capacity for poly β-hydroxy bytyrate (PHB), a biodegradable polymer, synthesis was tested for strain isolated from root nodules of Cicer arietinum plant. Out of 30 different strains, one strain was selected for further screening for PHB production in different conditions like media, temperature, pH, and agitation speed. The MTCC culture of Azotobacter beijerinckii (MTCC-2641) was used as a control for PHB production. When growth conditions were optimized in different media, the highest growth of isolate was observed in PHB glucose medium followed by yeast extract mannitol (YEM) agar. Other observed optimum growth conditions in PHB medium like temperature, pH, shaking were 30-37 0C, 6.5, 200 rpm respectively while in YEM medium all optimized conditions are same as in PHB glucose medium except agitation speed that was 150 rpm. After optimization of different culture conditions, isolated strain was characterized biochemically. Based upon biochemical studies, isolated strain was identified as Bacillus species. The present study provided the useful data about the optimized conditions for PHB production that can be utilized in industrial production of PHB, a fast emerging alternative of nonbiodegradable plastic.
Opto-Electronics Packaging And Failure Analysis Methodology

The demand for opto-electronics is increasing as we are nearing the future due to the need for high data rate, high bandwidth, lossless transmission and low electromagnetic interference sensitivity. The paper describes the present research carried on the mature laser technology i.e. GaAs, in order to improve its efficiency. The packaging principle used for receivers can be applied for the packaging of the laser driver circuit and the laser source in a single module. The concept of FRACAS (Failure Reporting, Analysis and Corrective Action System) has been described and failure analysis technique for Electrical overstress (EOS) is described. An industrial approach to calculating the reliability of a system with some known data facts has been described. Some challenges with respect to packaging have been discussed in detail and some methods to overcome challenges such as lattice mismatch have been described.
Land Mapping Based On Hyperspectral Image Feature Extraction Using Guided Filter

: In the area of Remote Sensing as well as Geosciences, whenever a particular scene is captured, it becomes very difficult to identify each and every object in the image. Here comes the advantage of using hyperspectral imaging and feature extraction method. Hyperspectral images are taken using satellites. To classify such images feature extraction is an effective method . The problem of the “curse of dimensionality” emerges when a statistic based classification method is applied to the hyperspectral data. A simpler and an effective way of processing with hyperspectral data is to reduce the dimensionality. This can be done by feature extraction that a small number of features are extracted from the hyperspectral image when confronted with a limited set of training samples. This paper mainly focuses on guided filtering. Guided filtering with SVM classifier will yield a better accuracy.
Low Power Digital FIR Filter Design Using Optimized Adder and Multiplier

: This paper proposes a design of low power and low delay digital finite-impulse response (FIR) filter. Nowadays, there are many portable applications requiring low power and high throughput than ever before. Thus, low power system design has become a significant performance goal. The Finite Impulse Response (FIR) Filter is the important component for designing an efficient digital signal processing system. The adders and multipliers play an important role in FIR filter while considering the power. The proposed FIR filter is designed by using Hybrid adder and Vedic multiplier from the analysis of various adders and multipliers. The Hybrid adder uses the concept of ripple carry adder and carry select adder and selects particular adder cell to perform addition operation which depends upon the carry input. The Vedic multiplier performs multiplication process in a hierarchical manner. Thus, the proposed method can minimize the dynamic power consumption and delay of the FIR filter. The experimental results show that the low pass FIR filter using proposed method achieves 10% and 1% of delay and power consumption reduction compared to conventional method. The proposed FIR Filter is simulated and synthesized using Modelsim simulator and Xilinx and power consumption results are shown by using XPower estimator tool.
Impact of Globalisation on Formal, Motivational and Strategic HRM Practices: An Empirical Evidence from India

New economic development, which is a result of globalisation and internationalisation, has exerted tremendous pressure on the Indian human resource functions how to evolve itself and add the value to the outcome of the firm. The present paper precisely discusses the globalisation and its impact on the HRM practices of Indian firm in the light of new economic reforms. This study aims to examine the far-reaching changes in the pattern of HR practices owing to ever-increasing globalisation in India. The data were collected through the selfdeveloped questionnaire from 282 senior HR managers of Indian firms. The principal component analysis with varimax rotation generated three components from fifteen HR practices, namely Formal, Motivational and Strategic HR practices. Structural Equation Modelling (SEM) technique has been applied to understand the relationship between globalisation and three bundles of HR practices by using the SPSS Amos 22 software. The study findings suggest that the role of globalisation cannot be neglected. Indeed, The HR policies and practices of Indian firms are strongly influenced by the pace of globalisation of the Indian economy.