FROM CREATION OF THE DEPARTMENT TILL CURRENT TIME

In the current time, the use of technologies has become propensity more than necessity. Nobody has gotten away from them nor left youth or old. It's totally relying upon us How to utilize it? One such live innovation is a Smartphone. At only one touch we approach any data about the entire world. It is very easy to carry in our pocket so everyone can use it anytime whenever. Smartphone has some constructive as well as some cynical aspects too. Nomophobia is a negative face of the smartphone. Nomophobia is the irrational dread of being without cell phones or being not able to utilize phones (situational phobia) for some reason such as some signal or battery issues. Theprimary point of the current research is to find out the proportion of Nomophobia among understudies with regardof gender and age in Agra city. For this purpose, a total number of 300 students were selected by randomization (150 males and 150 females) from the age scope of 15-20 years. The data was taken by using a self-administered questionnaire NMP-Q developed by Yilidirim and Correia. The obtained data were analyzed using descriptive statistics, Mean and Chi-square. Results revealed that there is a significant difference between male and female score on nomophobia. The other result indicates that early adolescents positively related to Nomophobia as compare to late adolescents. In India, one person can use multiple cell phones. There is no minimum age to use mobile phones. It is adding fuel to the pre-existing problem of Nomophobia. Telecom Administrative Authority of India (TRAI) should assume a functioning job by making an arrangement/law that "setting based methodology" on cell phone limitations among individuals ought to be followed. A demonstration will be detailed, under this demonstration. There ought to choose the least age for portable use. It will assist a great deal with curbing the circumstance.

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Utilizing Blockchain Technology in Social Media Bot Identification

10.36227/techrxiv.12049374 ◽

2020 ◽

Author(s):

Shreya Reddy ◽

Lisa Ewen ◽

Pankti Patel ◽

Prerak Patel ◽

Ankit Kundal ◽

...

Keyword(s):

Machine Learning ◽

Social Media ◽

Gold Standard ◽

The Internet ◽

Learning Models ◽

Current Time ◽

Machine Learning Methods ◽

Blockchain Technology ◽

Modern Age ◽

Machine Learning Models

<p>As bots become more prevalent and smarter in the modern age of the internet, it becomes ever more important that they be identified and removed. Recent research has dictated that machine learning methods are accurate and the gold standard of bot identification on social media. Unfortunately, machine learning models do not come without their negative aspects such as lengthy training times, difficult feature selection, and overwhelming pre-processing tasks. To overcome these difficulties, we are proposing a blockchain framework for bot identification. At the current time, it is unknown how this method will perform, but it serves to prove the existence of an overwhelming gap of research under this area.<i></i></p>

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Regeneration Mechanism Studied by Potential-Time Response to Sinusoidal Current-Time Function

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19971511 ◽

1997 ◽

Vol 62 (10) ◽

pp. 1511-1526

Author(s):

María-Luisa Alcaraz ◽

Ángela Molina

Keyword(s):

Kinetic Parameters ◽

Rate Constant ◽

Theoretical Study ◽

Time Function ◽

Time Response ◽

Current Time ◽

Regeneration Mechanism ◽

Sinusoidal Current ◽

Regeneration Processes

A theoretical study of the potential-time response to sinusoidal current applied to static and dynamic electrodes for regeneration processes is presented. Methods for determination of the regeneration fraction, rate constant of the chemical reaction and heterogeneous kinetic parameters are proposed.

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Multi-Objective Optimization of Resistance Welding Process of GF/PP Composites

Polymers ◽

10.3390/polym13152560 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2560

Author(s):

Guowei Zhang ◽

Ting Lin ◽

Ling Luo ◽

Boming Zhang ◽

Yuao Qu ◽

...

Keyword(s):

Signal To Noise Ratio ◽

Welding Process ◽

Welding Current ◽

Resistance Welding ◽

Thermoplastic Composites ◽

Current Time ◽

Process Factor ◽

Welding Equipment ◽

Lap Shear ◽

Adhesive Connections

Thermoplastic composites (TPCs) are promising materials for aerospace, transportation, shipbuilding, and civil use owing to their lightweight, rapid prototyping, reprocessing, and environmental recycling advantages. The connection assemblies of TPCs components are crucial to their application; compared with traditional mechanical joints and adhesive connections, fusion connections are more promising, particularly resistance welding. This study aims to investigate the effects of process control parameters, including welding current, time, and pressure, for optimization of resistance welding based on glass fiber-reinforced polypropylene (GF/PP) TPCs and a stainless-steel mesh heating element. A self-designed resistance-welding equipment suitable for the resistance welding process of GF/PP TPCs was manufactured. GF/PP laminates are fabricated using a hot press, and their mechanical properties were evaluated. The resistance distribution of the heating elements was assessed to conform with a normal distribution. Tensile shear experiments were designed and conducted using the Taguchi method to evaluate and predict process factor effects on the lap shear strength (LSS) of GF/PP based on signal-to-noise ratio (S/N) and analysis of variance. The results show that current is the main factor affecting resistance welding quality. The optimal process parameters are a current of 12.5 A, pressure of 2.5 MPa, and time of 540 s. The experimental LSS under the optimized parameters is 12.186 MPa, which has a 6.76% error compared with the result predicted based on the S/N.

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Analysing Nexus between Economic Growth, GHG Emissions, and Energy Consumption for India

Journal of Resources Energy and Development ◽

10.3233/red-170101 ◽

2021 ◽

Vol 17 (1) ◽

pp. 1-16

Author(s):

Asim Hasan ◽

Rahil Akhtar Usmani

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Carbon Emissions ◽

Series Data ◽

Gas Emissions ◽

Current Time ◽

Causal Influence ◽

Integration Test

Rising greenhouse gas emissions is an important issue of the current time. India’s massive greenhouse gas emissions is ranked third globally. The escalating energy demand in the country has opened the gateway for further increase in emissions. Recent studies suggest strong nexus between energy consumption, economic growth, and carbon emissions. This study has the objective to empirically test the aforementioned interdependencies. The co-integration test and multivariate vector error correction model (VECM) are used for the analysis and the Granger Causality test is used to establish the direction of causality. The time-series data for the period of 1971–2011 is used for the analysis. The results of the study confirm strong co-integration between variables. The causality results show that economic growth exerts a causal influence on carbon emissions, energy consumption exerts a causal influence on economic growth, and carbon emissions exert a causal influence on economic growth. Based on the results, the study suggests a policy that focuses on energy conservation and gradual replacement of fossil fuels with renewable energy sources, which would be beneficial for the environment and the society.

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Study and Analysis of Interference Signals of the LTE System of the GNSS Receiver

Sensors ◽

10.3390/s21144901 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4901

Author(s):

Lucjan Setlak ◽

Rafał Kowalik

Keyword(s):

End User ◽

Current Time ◽

Gnss Receiver ◽

System A ◽

Telecommunication Systems ◽

Depth Analysis ◽

Gnss Receivers ◽

Interference Signals ◽

The Subject ◽

Made In

Sometimes, it is impossible to conduct tests with the use of the GNSS system, or the obtained results of the measurements made differ significantly from the predicted accuracy. The most common cause of the problems (external factors, faulty results) are interference disturbances from other radio telecommunication systems. The subject of this paper is to conduct research, the essence of which is an in-depth analysis in the field of elimination of LTE interference signals of the GNSS receiver, that is based on the developed effective methods on counteracting the phenomenon of interference signals coming from this system and transmitted on the same frequency. Interference signals are signals transmitted in the GNSS operating band, and unwanted signals may cause incorrect processing of the information provided to the end-user about his position, speed, and current time. This article presents methods of identifying and detecting interference signals, with particular emphasis on methods based on spatial processing of signals transmitted by the LTE system. A comparative analysis of the methods of detecting an unwanted signal was made in terms of their effectiveness and complexity of their implementation. Moreover, the concept of a new comprehensive anti-interference solution was proposed. It includes, among others, information on the various stages of GNSS signal processing in the proposed system, in relation to the algorithms used in traditional GNSS receivers. The final part of the article presents the obtained research results and the resulting significant observations and practical conclusions.

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Adaptive Chaotic Image Encryption Algorithm Based on RNA and Pixel Depth

Electronics ◽

10.3390/electronics10151770 ◽

2021 ◽

Vol 10 (15) ◽

pp. 1770

Author(s):

Xiaoqiang Zhang ◽

Xuangang Yan

Keyword(s):

Image Encryption ◽

Three Dimensional ◽

Encryption Algorithm ◽

Current Time ◽

Plain Image ◽

Scope Of Application ◽

Selective Diffusion ◽

Chaotic Image Encryption ◽

And Diffusion ◽

Image Encryption Algorithm

To prevent the leakage of image content, image encryption technology has received increasing attention. Most current algorithms are only suitable for the images of certain types and cannot update keys in a timely manner. To tackle such problems, we propose an adaptive chaotic image encryption algorithm based on RNA and pixel depth. Firstly, a novel chaotic system, two-dimensional improved Logistic-adjusted-Sine map is designed. Then, we propose a three-dimensional adaptive Arnold transform for scrambling. Secondly, keys are generated by the hash values of the plain image and current time to achieve one-image, one-key, and one-time pad simultaneously. Thirdly, we build a pre-permuted RNA cube for 3D adaptive scrambling by pixel depth, chaotic sequences, and adaptive RNA coding. Finally, selective diffusion combined with pixel depth and RNA operations is performed, in which the RNA operators are determined by the chemical structure and properties of amino acids. Pixel depth is integrated into the whole procedure of parameter generation, scrambling, and diffusion. Experiments and algorithm analyses show that our algorithm has strong security, desirable performance, and a broader scope of application.

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Community Detection Based on Graph Representation Learning in Evolutionary Networks

Applied Sciences ◽

10.3390/app11104497 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4497

Author(s):

Dongming Chen ◽

Mingshuo Nie ◽

Jie Wang ◽

Yun Kong ◽

Dongqi Wang ◽

...

Keyword(s):

Community Detection ◽

Network Structure ◽

Clustering Algorithm ◽

Laplacian Matrix ◽

Representation Learning ◽

Detection Algorithm ◽

Graph Representation ◽

Time Slice ◽

Current Time ◽

Evolutionary Networks

Aiming at analyzing the temporal structures in evolutionary networks, we propose a community detection algorithm based on graph representation learning. The proposed algorithm employs a Laplacian matrix to obtain the node relationship information of the directly connected edges of the network structure at the previous time slice, the deep sparse autoencoder learns to represent the network structure under the current time slice, and the K-means clustering algorithm is used to partition the low-dimensional feature matrix of the network structure under the current time slice into communities. Experiments on three real datasets show that the proposed algorithm outperformed the baselines regarding effectiveness and feasibility.

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An MEWMA-based segmental multivariate hidden Markov model for degradation assessment and prediction

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability ◽

10.1177/1748006x21990527 ◽

2021 ◽

pp. 1748006X2199052

Author(s):

Yaping Li ◽

Enrico Zio ◽

Ershun Pan

Keyword(s):

Markov Models ◽

Hidden Markov ◽

Average Run Length ◽

Moving Average ◽

Model Parameters ◽

Current Time ◽

Multivariate Processes ◽

Industrial Systems ◽

Hidden States ◽

Multivariate Signals

Degradation is an unavoidable phenomenon in industrial systems. Hidden Markov models (HMMs) have been used for degradation modeling. In particular, segmental HMMs have been developed to model the explicit relationship between degradation signals and hidden states. However, existing segmental HMMs deal only with univariate cases, whereas in real systems, signals from various sensors are collected simultaneously, which makes it necessary to adapt the segmental HMMs to deal with multivariate processes. Also, to make full use of the information from the sensors, it is important to differentiate stable signals from deteriorating ones, but there is no good way for this, especially in multivariate processes. In this paper, the multivariate exponentially weighted moving average (MEWMA) control chart is employed to identify deteriorating multivariate signals. Specifically, the MEWMA statistic is used as a comprehensive indicator for differentiating multivariate observations. Likelihood Maximization is used to estimate the model parameters. To avoid underflow, the forward and backward probabilities are normalized. In order to assess degradation, joint probabilities are defined and derived. Further, the occurrence probability of each degradation state at the current time, as well as in the future, is derived. The Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dataset of NASA is employed for comparative analysis. In terms of degradation assessment and prediction, the proposed model performs very well in general. By sensitivity analysis, we show that in order to improve further the performance of the method, the weight of the chart should be set relatively small, whereas the method is not sensitive to the change of the in-control average run length (ARL).

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