Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Modified Binary Multiplier Circuit Based on Vedic Mathematics

Abstract: This paper presents a modified binary multiplier using Vedic mathematics. The paper proposes a modification in the previously published Vedic multiplier circuit. The suggested modified Vedic multiplication technique is more efficient in terms of delay and area. The proposed circuit is implemented in VHDL. The Mentor Graphics ModelSim tool is used for HDL simulation, and the Xilinx ISE Design Suite 14.1 is used for circuit synthesis. The simulation is done for 4-bit, 8-bit, and 16-bit multiplication operations. In this paper, the simulation waveforms are shown only for 4-bit multiplication operation based on the modified Vedic multiplication technique. The proposed method can be extended for a larger bit size. The performance evaluation in terms of speed and device utilization is compared with the previously reported Vedic multiplier architectures. The proposed design exhibits a speed improvement compared to the multiplier architectures available in literature.

Reflection and refraction at the interface between distinct generally anisotropic half spaces for three-dimensional plane quasi-P waves

Abstract: In this paper, reflection and refraction phenomena are studied for a three-dimensional plane quasi-P wave incident at the interface between distinct triclinic half spaces. A method has been developed to find the analytical expressions of all the phase velocities of reflected and transmitted quasi-P (qP), quasi-SV (qSV), and quasi-SH (qSH) waves. Closed form expressions for the amplitude ratios of reflection and transmission coefficients of qP, qSV, and qSH waves are also obtained. These expressions are computed numerically for a given set of data and the velocity distributions and variation of reflection and transmission coefficients with polar and azimuthal angle of incidence are shown graphically using two-dimensional single and double axes graphs. Surface plots of velocity variations of different reflected and transmitted waves are drawn to analyze the combined effect of incident polar and azimuthal angle on velocity distribution. Numerical results presented indicate that anisotropy effects on the refl...

An empirical approach to ECRM-increasing consumer trustworthiness using online product communities

Abstract: Online business communities are fast emerging as new organizational tools for customer relationship management, marketing, brand management and for a multitude of other purposes such as building strong online trust and reciprocity. This study has been conducted to do an analysis of the online community of Apple in detail by using Netnography, which is a new qualitative, interpretive research methodology that uses Internet-optimized ethnographic research techniques to study an online community. As a marketing research technique, ‘Netnography’ uses the information publicly available in online forums to identify and understand the needs and decision influences of relevant online consumer groups. The identification of parameters that aids participant trustworthiness can aid long-term strategic decision making. It is deduced that increased consumer participation in a community results in increased reciprocity, and more accurate peer-to-peer responses translate into greater peer acceptance, which is indicative of greater trustworthiness of a participant. This implies that trustworthiness and popularity of a forum member is a direct function of his ability to give correct answers (level of Consumer Product knowledge) to participants and their level of participation. Peer-to-peer consumer interaction is useful, and relevant incentives to consumer evangelists will be in the long-term organizational interest. Concepts of business online communities – coupled with commerce, content and communication – are widely discussed as the essential components of a successful organizational web presence. In a marketing context, the significance of a community can be viewed as an extension of the relationship marketing paradigm. The interest in the online communities from a marketing perspective is driven by the belief that the complex network of personal relationships and increasing identification with the group as a community provide a foundation for a very attractive business model. Customers and other stakeholders are only likely to be interested in communities that offer them value.

Empathy and Mindfulness: Potential Antecedents to Authentic Leadership

Abstract: As the upsurge of information continues due to globalization of economies in the wake of fierce competition, the role of information technology becomes more important than ever. The dynamics of business arena requires leaders in the IT industry who are well versed with new technologies as well as at the same time exhibit essential leadership skills that builds trust to ensure success. This paper discusses an empirical research aimed at identifying the antecedents for authentic leadership style for the professional in the IT sector by examining empathy and mindfulness as potential antecedents to authentic leadership. The questionnaire was completed by 250 respondents from the Indian IT sector. Findings reveal that empathy of a leader is significantly related to the development of authentic leadership. However, mindfulness is not related to authentic leadership. The paper identifies empathy as a potential antecedent of authentic leadership that is intended to foster positive organizational outcomes. Intense literature review reflects that only few studies have been conducted focusing on the antecedents of authentic leadership. The study attempts to fill this void.

Distributed anomaly detection using concept drift detection based hybrid ensemble techniques in streamed network data

Abstract: Ever since the internet became part of the everyday lives of humans providing network security has been considered of utmost importance. Over the years lot of time and energy has been devoted by people in the research community and industry to provide better, improved and secure mechanisms to ensure secure communications on the internet. Amongst the many fields of study, the most prominent and ever evolving one has been the study of network traffic for attack detection and mitigation. The advent of new technologies has led to an increase in the pace of network based attacks and therefore novel modified approaches are needed to be able to cope with these latest trends. Distributed machine learning with the development of new tools and frameworks like RDD structure in Apache Spark provides an immense scope of growth in this direction. Moreover, the dynamic nature of present day network traffic called concept drift has also necessitated studying solutions from a different angle. We, therefore, in this paper have worked on distributed machine learning based ensemble techniques to detect the presence of concept drift in network traffic and detect network based attacks. The work has been done in three parts. Firstly, two classifiers, namely, Random Forest and Logistic Regression have been used as level ‘0′ learners and Support Vector Machine has been used as level ‘1′ learner. Secondly, to handle the process of concept drift we have used a sliding window based K-means clustering. And thirdly ensemble based techniques for detection of attacks in the traffic. The experiments have been performed on three datasets, namely, the NSL-KDD dataset, the CIDDS-2017 dataset and generated Testbed dataset. These tests have been conducted on different machines by varying the number of executor cores to study time latency in a distributed environment. An accuracy of 93% on NSL-KDD, 98% on CIDDS-2017 and 97% on Testbed datasets for SVM based blending model have been achieved.