Sir Padampat Singhania University

About: Sir Padampat Singhania University is a education organization based out in Udaipur, India. It is known for research contribution in the topics: Encryption & Diesel fuel. The organization has 124 authors who have published 228 publications receiving 2066 citations. The organization is also known as: SPSU.

A Machine Learning Perspective on Causes of Suicides and identification of Vulnerable Categories using Multiple Algorithms

Abstract: Background Suicides represent a social tragedy with long term impact for the family. Given the growing incidence of suicides, a better understanding of factors causing it and addressing them has emerged as a social imperative. Material and Methods This study analyzed suicide data for three decades (1987-2016) and was carried out in two phases. Machine Learning Models run after pre-processing the suicide data included Neural network, Regression, Random Forest, XG Boost Tree, CHAID, Generalized Linear, Random Trees, Tree-AS and Auto Numeric Model. Results and Conclusion Analysis of findings suggested that the key predictors for suicide are Age, Gender, and Country. In the second phase, data from happiness reports were merged with suicide data to check if Country-specific factors impact the list or order of key predictors. While the key predictors remain the same, Country-specific factors like Generosity, Health and Trust impact the suicide rate in the Country.

Design and Analysis of Spurious Harmonics Suppressed Microstrip Ultrawide Band Filter using Modified Defected Ground Structure Techniques

Abstract: In recent days, the growth of wireless communication systems has greatly influenced the communication sectors. Especially, the technological advancements made in the UWB filters play a significant role in redesigning the UWB signals. In this paper, we have proposed a modified Defected Ground Structure (DGS) for Microstrip Ultra-wideband filter. The aim of the study is to design an efficient and lightweight UWB filter design for efficient communication systems. Thus, a different UWB filter is designed with permissible frequency range which improves the performance of the stopband. In this work, the DGS, interdigital, SIR & Shunt stub are employed. Then, a filter prototype is fabricated and measured. The results show that the modified DGS achieves 104.3% Bandwidth, less than 15 dB Loss of return with a frequency of 6.9 GHz for 0.25 λ0 × 0.16 λ0 size. The proposed design has improved the performance of the stopband in the aspects of return loss and the insertion loss.

A New Approach for Compression on Textual Data

Abstract: Data compression algorithms are used to reduce the redundancy, storage requirement and efficiently reduce communication costs. Data Encryption is used to protect our data from unauthorized users. Due to the unprecedented explosion in the amount of digital data transmitted via the Internet, it has become necessary to develop a compression algorithm that can effectively use available network bandwidth and also taking into account the security aspects of the compressed data transmitting over Internet. This paper presents an encoding technique that offers high compression ratios. An intelligent and reversible transformation technique is applied to source text to improve the capability of algorithms to compress the transmitted data. The results prove that the proposed method performs better than many other popular techniques with respected to compression ratio and the speed of compression and requires some additional processing on the server/nodes.

A Survey on DBN for Intrusion Detection in IoT

Abstract: In computer networks, intrusion detection systems play the major role to disturb the whole networks. Many latest researches have been done on IDS. Imperfection of intrusion detection systems (IDS) has given a chance for data processing to make many vital contributions to the sphere of intrusion detection. In recent years, several researchers are mistreating data processing techniques for building IDS. In this paper, various data processing techniques like deep belief neural network for IDS in IoT for serving to IDS to achieve higher detection rate are discussed. The term Internet of things (IoT), generally called Internet of objects, proposes the engineered interconnection of basic things, which is regularly observed as a self-managing remote procedure of sensors whose reason is to interconnect all things.

Differential cross sections for the electron impact ionization of Ar (3p) atoms for equal energy final state electrons

Abstract: The electron-impact ionization of inert gases for asymmetric final state energy sharing conditions has been studied in detail. However, there have been relatively few studies examining equal energy final state electrons. We report in this communication the results of triple differential cross sections (TDCSs) for electron impact ionization of Ar (3p) for equal energy sharing of the outgoing electrons. We calculate TDCS in the modified distorted wave Born approximation (DWBA) formalism including post collision interaction (PCI) and polarization potential. We compare the results of our calculation with available measurements [Phys. Rev. A 87, 022712 (2013)]. We study the effect of PCI, target polarization on the trends of TDCS for the single ionization of Ar (3p) targets.