iosr-JCE   Volume-24 ~ Issue-1 ~ Jan. - Feb. 2022

Abstract: Data security is very crucial in today's digital world, protecting a digital data from unwanted action of unauthorized users like cyber-attack. Using some advanced technologies we can try to protect over data in a variety of ways. In this research work we proposed technique of partially transmitted sequences along with the fast Fourier transform for physical layer security. The performance of the proposed technology is based on the complementary cumulative distribution function of low crest which enhance the level of security.

Key Word: Crest Factor, Fast Fourier Transform, Partially Transmitted Sequences

[1]. Zhiyi Wang ,Jun Cao ,Rui Deng ,Yi Liu,Jing " Time-frequency domain encryption with SLM scheme for physical-layer security in an USER DATA system", IEEE 2018
[2]. Amber Sultan ,Xuelin Yang , Adnan A. E. Hajomer ,Weisheng Hu," Chaotic Constellation Mapping for Physical-Layer Data Encryption in USER DATA", IEEE 2018
[3]. Adnan A. E. Hajomer , Xuelin Yang ,Weisheng Hu, "Chaotic Walsh–Hadamard Transform for Physical Layer Security in USER DATA", IEEE 2017
[4]. HM Furqan, JM Hamamreh , "Enhancing physical layer security of OFDM systems using channel shortening", IEEE 2017
[5]. W Liu, M Li, G Ti, X Tian, Q Liu "Transmit filter and artificial noise aided physical layer security for OFDM systems",IEEE 2016

Abstract:In this modern era, where technology has influenced the automotive industry deep, almost all four wheels now come with embedded features of mobile communications, wireless communication services, attractive digital displays, etc. This offers user comfort and offers a great user experience, but on the other hand, proves to be the cause of the driver's serious disturbance. Add to this, driver drowsiness causes a high number of road accidents. One of the causes of vehicle accidents is drowsiness of the driver. Many researchers have used many technologies to overcome this problem in recent years
So there are different techniques to detect.....

Key Word: Vehicle-based Measurements, Behavioural Measures, Bio-Signal based Measures, hybrid Measures.

[1]. Murry W Johns, All Rights Reserved | The Epworth Sleepiness Scale
[2]. www. Stanford Sleepiness Scale (SSS).com
[3]. Deradjad Pranowo Non-intrusive vehicle-based measurement system for drowsiness detection
[4]. Online Detection of Driver Fatigue Using Steering Wheel Angles for Real Driving Conditions
[5]. Sensitivity of Lane Position and Steering Angle Measurements to Driver Fatigue

Abstract: This paper analyzes the major energy sources in India and significance of renewable energy sources in climate mitigation. The aim of this paper is to provide renewable energy sources with the future of the energy industry, and it is through supportive and extensive legislation covering all possible aspects of the energy sector that these revolutions should be regulated. In this paper, the existing renewable energy legislation and regulations mechanism in India is analyzed and the barriers and challenges to the renewable energy industry are examined. Policies were developed to support the growth of specific technologies in the field of renewable energy. India is undergoing.....

Key Word: Renewable Energy, Climate, Energy Sources.

[1]. Arya, SB, Singh, B, Niwas, R, Chandra, A & Al-Haddad, K 2016, 'Power Quality Enhancement Using DSTATCOM in Distributed Power Generation System', IEEE Transactions on Industry Applications, vol. 52, no. 6, pp. 5203-5212.
[2]. Adebare Alfred, "India: Assessment of Renewable Power Purchase Obligations in India", Lex Counsel Law Offices, 23 November 2016.
[3]. Beck Fred, Martinot Eric, "Renewable Energy Policies and Barriers, Encyclopedia of Energy", Academic Press/Elsevier Science, 2004.
[4]. Böttinger, W., Maiwald, M., and Hasse, H. Online NMR spectroscopic study of species distribution in MEA–H2O–CO2 and DEA–H2O–CO2. Fluid Phase Equilibria, 263(2):131-143, 2008
[5]. Cherni Judith A. and Kentish Joanna, "Renewable energy policy and electricity market reforms in China", Energy Policy, 2007

Abstract: In recent years, almost every member of the society has been using Internet for their daily life. This is because it has become an integral part of our life. But, as the technology is continually advancing, the cyber security threats such as spamming and malwares, are swarming cyberspace exploiting vulnerabilities, making it harder for computer users to keep their data safe. To be able to keep people and files safe, an antivirus programs were created to aid in malware detection and prevention. While the performance of antivirus is commendable, they suffer from two major drawbacks, their inability to detect new malwares whose signatures are not available in the virus definition at the time........

Key Word: Ensemble, Machine learning, Malware detection, Recursive Feature Elimination (RFE)

[1]. Ö. A. Aslan and R. Samet, "A Comprehensive Review on Malware Detection Approaches," in IEEE Access, vol. 8, pp. 6249-6271, 2020, doi: 10.1109/ACCESS.2019.2963724.
[2]. "What is Malware?," Forcepoint, Aug. 12, 2018. https://www.forcepoint.com/cyber-edu/malware#:~:text=Malware%20is%20the%20collective%20name,unauthorized%20access%20to%20a%20network. (accessed Jan. 02, 2022).
[3]. "Machine Learning and Images for Malware Detection and Classification Project: MaLiC Konstantinos Kosmidis," 2016. Accessed: Jan. 02, 2022. [Online]. Available: https://repository.ihu.edu.gr/xmlui/bitstream/handle/11544/15225/Machine%20Learning%20and%20Images%20for%20Malware%20Detection%20and%20Classification-MaLiC.pdf?sequence=1.
[4]. P. Lipman, "Machine Learning's Vital Role in Malware Detection," AiThority, Dec. 17, 2019. https://aithority.com/guest-authors/machine-learnings-vital-role-in-malware-detection/ (accessed Jan. 02, 2022).
[5]. Kamalakanta S., Rahul K., Lingaraj S., Padmalochan B. and Prashanta K. P (2019) A Novel Machine Learning Based Malware Detection and Classification Framework,

Abstract: In this paper, we present a novel method for detecting environmental pollution of waste-water in industrial zones. Firstly, the quality of waste-water data is filtered by an adaptive filter. After that, the false nearest neighbor and average mutual information algorithms are applied to find embedding dimension space and time delay of waste-water quality time series to form training and testing set for the model. Finally, the Support Vector Regression and Fuzzy logic is implemented to build model for prediction quality of waste-water in industrial zones. Four main parameters at the waste-water processing station of Nittoku paper factory in the Kim Bang district, Ha Nam province, Vietnam have been used to test proposed method. The experimental results show that the proposed model is high accuracy and short training time, to helps waste-water processing station operators take early action and avoid environmental pollution.

Key Word: Support Vector Regression, Fuzzy logic, pollution, waste water, time delay, embedding dimension space.

[1]. According to Circular 24 of the Vietnamese Ministry of Natural Resources and Environment: 24/2017/TT-BTNMT, 1st September 2017, Ha Noi, Vietnam, 2017
[2]. Abarbanel, H.D., Brown, R., Sidorowich, J.J., Tsimring, L.S., (1993). The analysis of observed chaotic data in physical systems. Reviews of modern physics. 1993 Oct 1;65(4):1331.
[3]. Božić, J., Vukotić, S., Babić, D., (2011). Prediction of the RSD exchange rate by using wavelets and neural networks. In 2011 19th Telecommunications Forum (TELFOR) Proceedings of Papers 2011 Nov 22 (pp. 703-706). IEEE.
[4]. Castillo, O., Melin, P. (2002). Hybrid intelligent system for time series prediction using neural networks, fuzzy logic, and fractal theory. IEEE transactions on neural network Vol.13, No.6, November 2002, https://doi.org/10.1109/TNN.2002.804316.
[5]. Frank, R.J., Davey, N., Hunt, S.P., (2001). Time series prediction and neural networks. Journal of intelligent and robotic systems. 2001 May 1;31(1-3):91-103.