MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Computer Engineering & Technology

Using routing technique, wireless sensor network WSN can route sensor data quickly. As there is only one next hop, transmissions can be fast. However, routed data only traverses its end-to-end path. So routing data to every node is difficult. Additionally, verifying transmission to each destination can be prohibitively expensive. Broadcast technique can scalably reach every node in a sensor network. Current sensor network routing protocols running on the mica2 hardware platform can route across approximately ten hops in a second after considering retransmissions, media access and contention [12], [14], [20]. The trickle broadcast protocol transmits at most once a second to minimize packet losses due to collisions [2]. This study presents a way to combine routing and broadcasting techniques to achieve reliable propagation of data packets. It brings out clearly, the reliability with which the control packets are propagated to all the nodes deployed in the network, as compared to pure broadcast based dissemination. Reliably disseminating a piece of data to every node is a basic requirement for WSNs.

World University root node

Engineering and Technology

IASTED International Symposium on Distributed Sensor Networks, DSN 2008

Routing strategy based firecracker protocol for data dissemination in wireless sensor networks

Due to the increasing demand in secured applications, biometrics systems are becoming very important for many real world applications. A biometric system is essentially a pattern-recognition system that identifies a person based on feature vector derived from a specific physiological or behavioural characteristic that the person possesses. Over the years, biometric technologies based on face, fingerprint, DNA samples, speech, keystroke and other personal features have advanced to a great extent leading to sophisticated authentication systems. Though there is evidence of interest in the use of biometrics in selected areas such as crime detection and border security, studies indicate that the development of such biometric technologies has not been utilised to its full capacity in business and social communities due to socio-technical concerns. While much research focuses on the implementation enhancements relating to acquiring samples, feature extraction, digitizing and storage, pattern matching algorithms and fault tolerance, there is a paucity of research that focuses on the impact assessment of biometric systems on communities. This paper identifies the motivating factors as well as major challenges that biometric systems face from the perspective of the impact of technology, cost, privacy and social issues on communities. It analyses such impact on communities through various scenarios in societies, businesses and government. Based on the study, we believe that a suitable knowledge-shared ICT implementation framework is required to successfully harness the benefits of biometrics systems in communities. Hence, in this paper, we propose a knowledge-based adaptive framework that overcomes these challenges through a selectively shared knowledge management approach among various organisations, government bodies, societies and other communities. We believe this would be a step towards achieving highly secured communities that make use of biometric systems effectively. Copyright © 2008 COSI.

Harnessing Knowledge Management to Build Communities - Proceedings of the 11th Annual Australian Conference on Knowledge Management and Intelligent Decision Support, ACKMIDS 08

The impact of biometric systems on communities: Perceptive and challenges

Proc. International Conference on Cognition and Recognition

Isolated Marathi Numeral Recognition using Density and Central Moment Feature

In traditional machine learning approaches to classification, one uses only a labelled set to train the classifier. Labelled instances however are often difficult, expensive, or time consuming to obtain, as they require the efforts of experienced human annotators. Meanwhile unlabeled data may be relatively easy to collect, but there has been few ways to use them. Semi-supervised learning addresses this problem by using large amount of unlabeled data, together with the labelled data, to build better classifiers. Because semi-supervised learning requires less human effort and gives higher accuracy, it is of great interest both in theory and in practice. The paper discusses various important approaches to semi-supervised learning such as self-training, co-training(CO), expectation maximization (EM), -EM, Then how graphbased methods are useful is explained. All semisupervised learning methods are classified into generative and discriminative methods. But experimental results show that the hybrid algorithm gives better classification accuracy. © 2008 IEEE.

Proceedings - 2008 International Conference on Computational Intelligence and Security, CIS 2008

A survey of semi-supervised learning methods

This paper discusses the performance analysis of multi-antennas systems with receive antenna selection over quasistatic fading channels. In performing the analysis with antenna selection, the selection criterion adopted is based on selecting best Nr antennas out of the available NR3 receive antennas such that the instantaneous signal-to-noise ratio (SNR) at the receiver is maximized. It is assumed that the total number of transmit antennas, NT =2, are equal to or greater than the total number of receive antennas. From the analysis it is shown that the resulting diversity order with antenna selection is maintained as that of full complexity system, however the coding gain deteriorates in proportion with reduced number of receive antennas. The results obtained with antenna selection with NR =2 and N R3 =3 multi-antenna systems are compared. © 2008 IEEE.

Proceedings of the 4th International Conference on Wireless Communication and Sensor Networks, WCSN 2008

Performance analysis of space-time trellis codes with receive antenna selection

A system for re-ordering the search results to provide to the user results of more relevance to him with the help of his profile. This concept is called Personalization. These profiles can be created by collecting data explicitly (which may be input directly by the user in the form of recommendation, comment or vote) as well as implicitly (based on the user's browsing patterns). This data can be monitored locally (at the client side) or at the server level or some hybrid approach can be adopted. The open recommendation system facilitates the degree to which personalization of results is needed by the user. The system design also includes measures to maintain the privacy and security of the users by encrypting their profile information to counter the threats to the same. The system has been designed as an open ended one and has a window for more ideas/designs to be incorporated some of which have been mentioned in the future works. © 2008 IEEE.

2008 First International Conference on Emerging Trends in Engineering and Technology

Personalization of Web search results based on user profiling

In this paper, orthogonal space-time block codes (OSTBC) are considered for investigating impact of receive antenna selection on the capacity and error probability analysis of multiple-input multiple-output (MIMO) systems. The results are compared with and without antenna selection of 2X2 and 2X4 MIMO systems. Achieved capacity with receive antenna selection for Nr ≥ NT has been found close to the capacity of full complexity system, whereas upper capacity bound is tight for Nr ≤ NT.

Journal of Scientific and Industrial Research

A reduced complexity MIMO system with antenna selection for high data rate wireless communications

This paper presents short-term forecasting model for crude oil prices based on three layer feedforward neural network. Careful attention was paid on finding the optimal network structure. Moreover, a number of features were tested as an inputs such as crude oil futures prices, dollar index, gold spot price, heating oil spot price and S&P 500 index. The results show that with adequate network design and appropriate selection of the training inputs, feedforward networks are capable of forecasting noisy time series with high accuracy. © 2008 IEEE.

ISSNIP 2008 - Proceedings of the 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing

Forecasting model for crude oil prices based on artificial neural networks

Multi-Antenna systems allow for high data rates and improved quality of service but the cost paid for deriving these benefits is hardware complexity due to multiple antennas and the number of RF chains. Antenna selection techniques are proposed in recent time to reduce the hardware complexity to considerable extent, retaining the diversity benefits of Multiple-Input Multiple-Output (MIMO) systems. Space-Time coding schemes are the practical signal design techniques to realize the information theoretic capacity limits of MIMO systems. In this paper, orthogonal space-time block codes (OSTBC) are considered for the capacity and error probability analysis of MIMO systems with receive antenna selection. The numerical and simulation results obtained using MATLAB are presented for the channel capacity and bit-error probability in Rayleigh fading channels. The results are compared with and without antenna selection of space-time block coded MIMO system.

IET Seminar Digest

Capacity and performance analysis of space-time block coded MIMO systems with receive antenna selection in rayleigh fading channels

The on-line image retrieval process consists of a query example image, given by the user as an input, from which low-level image features are extracted. These image features are used to find images in the database which are most similar to the query image. A drawback, however, is that these low level image features are often too restricted to describe images on a conceptual or semantic level. The gap between the high level query from the user and low level features extracted by a computer is known as the semantic gap. Translating or converting the question posed by a human to the low level features seen by the computer illustrates the problem in bridging the semantic gap. This paper proposes a novel fuzzy approach for mapping the fuzzy database while extracting the colour features from image and assigning the weights to this fuzzy content when calculating the similarity between the query image and the images in database. Number of experiments was conducted on a small colour image database and promising results were obtained. © 2007 IEEE.

Proceedings - 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007; 1st IEEE/ACIS International Workshop on e-Activity, IWEA 2007