iosr-JCE   Volume-23 ~ Issue-1 ~Jan. - Feb. 2021

Abstract: This study aims to present a comprehensive survey of the methods and techniques that are applied in the different stages of processing the brain activities, whether the functional or cognitive activities. In the first part, the common methodologies in each phase were listed in detail. They are signals acquisition, signals preprocessing, features extraction and signals classification. While in the second part a review of previous studies regarding the methods and techniques used, where the focus was only limited to the EEG technology. And the third part presents an initial idea of how to use the nanotechnology in the process of effective recording of the brain wavesy.

Key Word: BCI; Electroencephalogram; Signals-Acquisition; Signals Preprocessing; Features Extraction; Signals Classification; Nanotechnology

[1]. M. R. Lakshmi, D. T. Prasad, and D. V. C. Prakash, "Survey on EEG signal processing methods," International Journal of Advanced Research in Computer Science and Software Engineering, vol. 4, no. 1, 2014.
[2]. Angrisani L. Instrumentation and measurements for non-invasive EEG-based brain computer interface. Paper presented at: 2017 IEEE International Workshop on Measurement and Networking (M&N); 2017. Sep 27-29; Naples, Italy.
[3]. Ramoser, H. "Optimal spatial filtering of single trial EEG during imagined hand movement." Rehabilitation Engineering, IEEE Transactions on [see also IEEE Trans.on Neural Systems and Rehabilitation], Vol. 8, Iss. 2, pp. 441-446. (2000).
[4]. A. Moungou, J.-L.Thonnard, and A. Mouraux, ``Using EEG (SS-EPS) to characterize the brain activity in response to textured stimuli in passive touch,'' in Proc. IEEE World Haptics Conf. (WHC). Evanston, IL, USA: IEEE, Jun. 2015, pp. 113_118. Accessed: Apr. 7, 2019.[Online]. Available: http://ieeexplore.ieee.org/document/7177700/
[5]. A. Moungou, E. Vezzoli, C. Lombart, B. Lemaire-Semail, J.-L.Thonnard, and A. Mouraux, ``A novel method using EEG to characterize the cortical processes involved in active and passive touch,'' in Proc. IEEE HapticsSymp. (HAPTICS). Philadelphia, PA, USA: IEEE, Apr. 2016, pp. 205_210. Accessed: Apr. 7, 2019. Available: http://ieeexplore.ieee.org/document/7463178/

Abstract: The task to get helpful systems (electronic home appliances) to alter our lives, is one in every of the most functions of intelligent systems. Intelligent appliances with transmission capability are rising into our lifestyle. because of the quick advance of computing technology. sensible house is one in every of the foremost outstanding areas of intelligent appliances. room is one in every of the places wherever such intelligent appliances are used. At an equivalent time, it's been a apply for all people to use the junk foods, or too previous vegetables and fruits in our lifestyle thanks to the busy regular life that we tend to lead. Or some prospects wherever we tend to don't bear in mind the vegetables/fruits we've not been feeding for a protracted time. This successively results in lack of nutrition or, some unsafe infections or may disturb the immunity power in every people. Why do not we tend to encounter a shot to own a tool to point what we've (food/vegetables/fruits) and the way previous is it.

Index Terms- Image acquisition, Morphological process, Edge detection, OpenCV

[1]. Satyendra K. Vishwakarma 'Energy Efficient Smart Home Automation System' 29 July 2019 https://ieeexplore.ieee.org/document/8777607#:~:text=In%20this%20paper%2C%20smart%20energy%20efficient%20home%20automation,system%20which%20can%20be%20accessed%20through%20the%20Internet
[2]. Prapulla S B 'Smart Refrigerator Using Internet of Things' July 2015 http://ijlera.com/papers/v2-i3/part-II/31.201703127.pdf#:~:text=INTERNET%20refrigerator%20also%20known%20as%20Smart%20refrigerator%20is,when%20a%20food%20item%20needs%20to%20be%20replenished
[3]. Rajesh K R, C A Bindyashree 'Multiple Appliances Controlling and Monitoring System based on Wireless Embedded Home Gateway' 4 April 2015
[4]. https://www.rroij.com/open-access/multiple-appliances-controlling-andmonitoring-system-based-on-wirelessembedded-home-gateway.pdf
[5]. B. Murali Krishna 'Bluetooth Based Wireless Home Automation System Using FPGA' 31st July 2015 -http://www.jatit.org/volumes/Vol77No3/12Vol77No3.pdf#:~:text=FPGA%20board%20is%20used%20to%20control%20the%20home,through%20RS-232%20for%20the%20control%20of%20home%20appliances

Abstract: In the remote sensing techniques reflectance spectroscopy is one of most important technique is used for soil properties assessment, this article attempts to provide a review on fundamental concepts of reflectance spectroscopic techniques. In the spectroscopy technique, spectral signatures are more complicated to process. When proper methods are used in soil properties assessment it gives most accurate results. In this paper various process and methods are explained which are required for data collection and data processing of spectral data like sampling, preprocessing, analysis and classification. Their applications as well as exploring the role of Near-infrared reflectance spectroscopy that would be used for monitoring, mapping soil characteristics and analysis of soil properties. Spectroscopy techniques gives the fast and accurate results as compare to traditional methods because minimum soil sample preparation, no chemical analysis are required, minimum time require to process the acquired data. Moreover, this article explores the potentiality of predicting soil properties based on spectroscopic measurements.

Index Terms- Spectroscopy, Soil, PLSR, PCA, LDA

[1]. Zejian Lei, Mingyin Yao, Muhua Liu, Qiulian Li and Hanping Mao. Comparison between Fertilization N, P, K and No Fertilization N, P, K in Paddy Soil by Laser Induced Breakdown Spectroscopy. IEEE Intelligent Computation Technology and Automation. 2011. 1; 363-366.
[2]. E.S. Mohamed, A.M. Saleh, A.B. Belal, Abd_Allah Gad , "Application of near-infrared reflectance for quantitative assessment of soil properties", The Egyptian Journal of Remote Sensing and Space Sciences, 21, 2018 pg. 1–14
[3]. Vipin Y. Borole, Sonali B. Kulkarni, Pratibha R. Bhise, "Effect of fertilizers on soil properties for different crops in pre-monsoon season using spectroradiometer for raver tehsil of jalgaon district", International Journal of Scientific and Technology Research, Volume 9, Issue 2, February 2020, Pg. 844-849
[4]. Ramdas D. Gore, Sunil S. Nimbhore, Bharti W.Gawali, "Understanding Soil Spectral Signature Though RS and GIS Techniques", International Journal of Engineering Research and General Science Volume 3, Issue 6, pp. 866-872, November-December, 2015
[5]. Bhise Pratibha.R, Kulkarni Sonali.B "Remote Sensing and Data Mining Techniques Applied on Soil Characteristics Data Classification", IOSR Journal of Computer Engineering (IOSR-JCE), pp. 83-91

Abstract: Machine translation is a big domain in research area. In machine translation we translate source language to target language. That time their occur divergence. Divergence is the big problem for machine translation. In this paper, we review on translation divergences between two Languages pair. In Machine translation various types of divergence are present. Lexical divergence, symentatic divergence, structural divergence, thematic divergence etc. We study all the previous work done in language divergence and examine the types of divergence. Our goal is identify the different types of divergence problem from Marathi to English and the vice-versa. This paper hopes to open up new avenues for future research in the area of translation divergence between two language pair not yet been studied in close details.

Index Terms- Machine Translatio; Lingustic divergence; Artificial Neweral Network.

[1]. Jisha P Jayan, Elizabeth Sherly," A Study on Divergence in Malayalam and Tamil Language in Machine Translation Perceptive".
[2]. Vimal Mishra, R.B.Mishra," Divergence patterns between English and Sanskrit Machine Translation",2014
[3]. Niladri Sekhar Dash," Linguistic Divergences in English to Bengali Translation", International Journal of English Linguistics, Vol. 3, No. 1; E-ISSN 1923-8703,2013.
[4]. Sreelekha S.," Statistical Vs Rule Based Machine Translation; A Case Study on Indian Language Perspective".
[5]. Sharmin Muzaffar, Pitambar Behera & Girish Nath Jha," Classification and Resolution of Linguistic Divergences in English-Urdu Machine Translation",2016

Abstract: This research proposes a framework for effective utilization of ICT for professional development of teachers in Bangladesh. The research will also cover the development of strategic planning process and the essential conditions of successful technology integration for learning environment. It will also recognize essential techniques in the teacher education program for managing the process of change as technology becomes a catalyst for the transformation of the teaching-learning process. This proposal is presented based on understanding of the ground reality in the educational eco-system currently prevailing in Bangladesh.

Index Terms- ICT, Professional Development, Teachers, Students, Integration

[1]. Carlson, S.et al,(2002). Teacher professional development in the use of technology: Washington, D.C ,United States of America.
[2]. Andoh, C. B. (2012). Factors influencing teachers' adoption and integration of information and communication technology into teaching: A review of the literature. International Journal of Education and Development using Information and Communication Technology, 8(1), 136-155.
[3]. Organisation for Economic Co-operation and Development (OECD). The Future of Education and Skills: Education 2030; OECD: Paris, France, 2018.
[4]. Unwin, T. Towards a framework for the use of ICT in teacher training in Africa. Open Learn. 2005, 20, 113–129.

Abstract: The development of e-commerce has brought great changes to people's life, and people's consumption patterns have also changed a lot. Consumers have become accustomed to buying the products they need in online stores. However, scholars at home and abroad have little research on the impact of shopping website characteristics on consumer behavior. Therefore, this paper takes Taobao as the research object and discusses the website characteristics and brand through research The results show that only ease of use, reliability, care and compensation of the six dimensions of website characteristics can have a positive impact on brand loyalty. Finally, this paper also puts forward relevant suggestions on Taobao website operation

Key Word: Website characteristics; brand loyalty; Taobao

[1]. The 43rd statistical report on the development of China's Internet [R]. CNNIC, 2019
[2]. Zhong Xiaona. The influence of website characteristics and consumers' individual characteristics on online shopping acceptance [D]. Zhejiang University, 2006
[3]. Kemener. User experience of e-commerce in B2C shopping mall [EB / OL] (2013-04-10) [2013-4-15] http://www.commernet.cn/newsny.asp?ID=441
[4]. Baumeister, R. Yielding to Temptation: Self‐Control Failure, Impulsive Purchasing, and Consumer Behavior [J].Journal of Consumer Research,2002(28):670-676.
[5]. Mummalanent, V. An empirical investigation of Web site characteristics, consumer emotional states and on-line shopping behaviors [J]. 2005,58(4)：526-532..

Abstract: This paper proposes an approach to perform error concealment based on a Video Quality Measurement Tool (VQMT) correlated with the Human Visual System (HVS). The VQMT is expected to replace human judgment when rating video quality in subjective experiments. To the best of our knowledge, this is the first time that results are reported on image quality improvement algorithms, which have been dynamically controlled by a neural network based machine learning process, after having been carefully trained on video and image databases with associated subjective quality ratings (MOS). The underlying study consists of selecting fundamental quality metrics based on Human Visual System models and using artificial intelligence solutions as well as statistical analysis......

Keywords: Error Concealment; Video Quality; Artificial Neural Network; Peak Signal to Noise Ratio; Blur Metric; Visual Artifacts.

[1] B. Ekobo Akoa, E. Simeu et F. Lebowsky, «Using statistical analysis and artificial intelligence tools for automatic assessment of video sequences,» chez Proc. SPIE 9015, Color Imaging XIX: Displaying, Processing, Hardcopy, and Applications, San Francisco, 2014.
[2] L. Lupka, E. Simeu, H. Stratigopoulos, L. Ruffer, S. Mir et O. Tumova, «Signature analysis for MEMS pseudorandom testing using neural networks,» chez 12th IMEKO Joint Symposium on Man Science and Measurement, Annecy, 2008.
[3] H. Stratigopoulos et Y. Makris, «Error moderation in low-cost machine-learning-based analog/RF testing,» IEEE Trans. on Computer-Aided Design of Integrated Circuits and Systems, pp. 339-351, 2008.
[4] B. Ekobo Akoa, E. Simeu et F. Lebowsky, «Using Artificial Neural Network for Automatic Assessment of Video Sequences,» chez 27th IEEE International Conference on Advanced Information Networking and Applications Workshops (WAINA'13), Barcelona, 2013.
[5] F. De Simone, M. Naccari, M. Tagliasacchi, F. Dufaux, S. Tubaro et T. Ebrahimi, «Subjective assessment of H.264/AVC video sequences transmitted over a noisy channel,» chez Proc. Int. Conf. QoMEX 2009, 2009..

Abstract: EDM is emerging field for exploring educational dataset. Student's performance, Enrollment capabilities and development of EDM application is highly used today while analyzing the student data. EMD id specialized with the capabilities of Visualization, Recommendation, Performance probability, Enrollment outcomes etc. Basic five data mining algorithm is compared – Decision Tree, Naïve Bayes, K Nearest neighbor, Neural network and Support Vector Machine (SVM). The accuracy of various authors work has been compare. The paper tried to combine a comparative study with respect to EDM functioning and its development with the help of core Data Mining Techniques.

[1]. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (AdultTreatment Panel III) Third report of the national cholesterol education.
[2]. U. bin Mat, N. Buniyamin, P. M. Arsad, R. Kassim, An overview of using academic analytics to predict and improve students' achievement: A proposed proactive intelligent intervention, in: Engineering Education (ICEED), 2013 IEEE 5th Conference on, IEEE, 2013, pp. 126–130.
[3]. Amirah Mohamed Shahiria, Wahidah Husaina , Nur'aini Abdul Rashida , A Review on Predicting Student's Performance using Data Mining Techniques , The Third Information Systems International Conference , Procedia Computer Science 72 ( 2015 ) 414 – 422
[4]. S. S. Meit, N. J. Borges, B. A. Cubic, H. R. Seibel, Personality differences in incoming male and female medical students., Online Submission.
[5]. M. Mayilvaganan, D. Kalpanadevi, Comparison of classification techniques for predicting the performance of students academic environment, in: Communication and Network Technologies (ICCNT), 2014 International Conference on, IEEE, 2014, pp. 113–118.

Abstract: A different approach to understanding Artificial Intelligence is to examine to solve the problem. At a high level Artificial Intelligence generally considered a subfield of computer science. In mathematics and computer science, an algorithm is a sequence of instructions, typically to solve a class of problems or perform a computation. Algorithms are unambiguous specifications for performing calculations, data processing, automated reasoning, and other tasks. The idea of VBA editor is a very powerful tool to solve this millennium problem by a macro recording in computer science.

Keywords: Millennium Problem, Nyaysangat Foundation, Artificial Intelligence, AI, VBA, Boolean algebra, Computer Theory. P v NP

[1]. Thesis "A PROPOSED SOLUTION FOR P V NP PROBLEM" SUBMITTED IN MATHEMATICAL SOCIETY OF LONDON".
[2]. IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 21, Issue 5, Ser. III (Sep - Oct 2019), PP 07-18 www.iosrjournals.org The P vs. NP problem, Author - Ekta Singh, Director Nyaysangat Foundation.
[3]. IOSR Journal of Applied Chemistry (IOSR-JAC) e-ISSN: 2278-5736.Volume 12, Issue 11 Ser. I (November. 2019), PP 31-39 www.iosrjournals.org DOI: 10.9790/5736-1211013139 www.iosrjournals.org 31 |Page God Is Logically Exist Ekta Singh Director, Nyaysangat Foundation Corresponding Author: Ekta Singh
[4]. IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 21, Issue 6, Ser. I (Nov - Dec 2019), PP 33-45 www.iosrjournals.org DOI: 10.9790/0661-2106013345 www.iosrjournals.org 33 | Page e=mc2Pr (a) = Time Machine A Light And Music In A New Life Can Be Protected By Meditation And Prayer To Reach The Star For Pride In King‟s Kingdom Corresponding Author: Ekta Singh, Director Nyaysangat Foundation
[5]. IOSR Journal of Mathematics (IOSR-JM) e-ISSN: 2278-5728, p-ISSN: 2319-765X. Volume 15, Issue 6 Ser. VI (Nov – Dec 2019), PP 09-35 www.iosrjournals.org DOI: 10.9790/5728-1506060935 www.iosrjournals.org 9 | Page Pr (a) "Elementary Proof Of The Yang Mills Theory Exists On R4 And Has A Mass Gap Delta > 0" Ekta Singh, Director, Nyaysangat Foundation.

Abstract: In today's data-driven world, organizations are swimming in a sea of information. Customer transactions, social media interactions, sensor data – the volume, variety, and velocity of data can be overwhelming. But within this vast ocean lies a treasure trove of insights waiting to be discovered. This is where data mining comes in. Data mining is a powerful tool that organizations can leverage to make more informed decisions, optimize operations, and gain a competitive edge. As the volume and complexity of data continue to grow, data mining techniques......

Keywords: Data, Mining, Organization, Decision

[1]. Attwal, K. P. S. and Dhiman, A. S. (2020). Exploring Data Mining Tool-Weka And Using Weka To Build And Evaluate Predictive Models. Advances and Applications in Mathematical Sciences, 6(19), 451-469.
[2]. Durugbo, C. M. (2020). After-sales services and aftermarket support: a systematic review, theory and future research directions. International Journal of Production Research, 58(6), 1857-1892
[3]. Gimpel, H., Hosseini, S., Huber, R. X. R., Probst, L., Röglinger, M. and Faisst, U. (2018). Structuring Digital Transformation: A Framework of Action Fields and its Application at ZEISS. Journal of Information Technology, Theory and Application, 1(19), p. 3.
[4]. Ray, S. (2019, February). A quick review of machine learning algorithms. In 2019 International conference on machine learning, big data, cloud and parallel computing (COMITCon) (pp. 35-39). IEEE.
[5]. Rudnick, M., Riezebos, J., Powell, D. J. and Hauptvogel, A. (2020). Effective after-sales services through the lean servitization canvas. International Journal of Lean Six Sigma, 5(11), 943-956..