There are many different algorithms for matrix multiplication. Commonly used matrix multiplications are conventional matrix multiplication and matrix multiplication using divide and conquer method including Strassen's matrix multiplication. In this paper I optimize the divide and conquer method for matrix multiplication by avoiding recomputation of the matrix elements. This new method is useful when multiplicands biggest and nearest digits.

Keywords: Algorithm, Matrix multiplication optimization, divide and conquer

[1]. Alfred, V, Aho., John, E, Hopcroft., Jeffrey, D, Ullman., Design & Analysis of Computer Algorithms,Pearson
[2]. Khaled, Thabet., King, Abdulaziz. Matrix Multiplication Algorithms., International Journal of Computer Science and Network Security, VOL.12 No.2, February 2012
[3]. Pawan, Rathod., Ankit, Vartak., Neha, Kunte., Optimizing the Complexity of Matrix Multiplication Algorithm., 2017 International Conference on Intelligent Computing and Control (I2C2'17)

Noise is unwanted sound and Noise due to traffic is increasing due to increasing vehicular movement on the roads. The increased noise levels lead to several adverse impacts on health. Vijayawada the second most important city in the State of Andhra Pradesh, India is considered as a commercial capital of the State and is very close to the existing capital of the State. This made the increasing of the traffic manifold in the city besides the associated noise pollution. Traffic noise is studied at four locations representing Residential, Commercial, Industrial and Silent zones. Traffic flow is determined at these locations and simultaneously noise levels are determined for three days varying the distance from the sampling point to the center of the road. The data is collected, compared with the permissible limits and analyzed. It is noted that the equivalent sound levels (Leq) at all the four locations are beyond permissible limits for that zone......

Keywords: Traffic noise, Noise Pollution, Equivalent sound level, Modeling, Multiple Regression, Artificial Neural Networks.

[1]. Al-Mutairi N. and Al-Rukaibi F. 2012. "Neural Network Models for Traffic Noise Quality Prediction: A Comparative Study", Journal of Civil and Environmental Engineering, 2 (1).
[2]. Alpesh K. Sankhat, C. B. Mishra, and A.N. Roghelia. 2017. "Developing Noise Pollution Linear Regression Model of Una Town", International Journal for Research in Applied Science & Engineering, Technology, 5 (V), 1656-1663.
[3]. Ambika N. Joshi, Nitesh C. Joshi, Payal P. Rane, 2015. "Noise Mapping in Mumbai City, India". International Journal of Innovative Science, Engineering & Technology, 2 (3), 380-385, March 2015.
[4]. Arora J.K. and P. V. Mosahari. 2012. "Artificial Neural Network Modelling of Traffic Noise in Agra-Firozabad Highway", International Journal of Computer Applications, 56 (2), 6-10.
[5]. Babu B.V., Ramakrishna V. and K. Kalyan Chakravarthy. 2003. "Artificial Neural Networks for Modeling of Adsorption", Second International Conference on Computational Intelligence, Robotics, and Autonomous Systems (CIRAS-2003), Singapore, December 15-18.

The goal of our group's project is to design and build an firefighting quadcopter. This means going through the process of bluiding a quadcopter in a need size.After deciding the size we wanted our quadcopter to be done.

[1]. https://flytnow.com/drone-fire-fighttps:/
[2]. https://www.quadrocopter.com/public-safety/
[3]. https://www.droneomega.com/what-is-a-quadcopter/
[4]. https://oscarliang.com/quadcopter-hardware-overview/
[5]. http://dronehitech.com/en/sg-acro-quadcopter-frame/

The paper presents an innovative method of preparing the germinating bed on small fields as surface from the small peasant farms. Preparing the germinating bed for sowing or planting is a complex process of digging, harrowing, pruning and leveling the soil. All these operations can be performed simultaneously with a simple technique equipment of small mechanization characterized by low energy consumption, high efficiency and superior quality of the work according to agro technical requirements. The idea of this equipment went from a hand-operated tool to work the soil that the Russian gardeners successfully use, being adapted to a mechanized working process.

Keywords: Germinating bed, tiller, technical equipment, mechanized working process

[1]. Buzatu, I., Herea, V., (1984). Unelte și utilaje de mică mecanizare, București, Editura Ceres, România
[2]. Popescu, A., 2013, Considerations on utilized agricultural land and farm structure in the European Union,Scientific Papers Series Management, Economic Engineering in Agriculture and Rural Development, Vol.13(4): 221 –225.
[3]. Sulea, I., Trandafir, S.,(1966). Unelte si utilaje agricole de mica mecanizare, Editura agro-silvica, Bucuresti, România
[4]. ***Agro România(2010), Pregătirea patului germinativ în agricultura ecologică,http://agroromania.manager.ro/articole/stiri/pregatirea-patului-germinativ-in-agricultura- ecologica-9991.html
[5]. ***Cazma-sapăminune(2018), Furca pentru săpat terenul in grădină, https://www.olx.ro/oferta/cazma- sapa-minune-furca-pentru-sapat-maruntit-terenul-in-gradina-ID5l1hk.html

Alzheimer Disease (AD) is a type of Dementia which is a neurodegenerative progressive disorder. No treatment can stop or prevent the growth of this disease. Magnetic Resonance Imaging (MRI) is the best tool for the early detection of AD. This paper presents the review of feature extraction and classification techniques used for the early detection of AD which are used earlier. Proposed algorithm for the early detection of AD is also stated in the paper.

Keywords: Alzheimer Disease, Mild Cognitive Impairment, Magnetic Resonance Imaging, ALFF.

[1]. Chuanchuan Zheng et al., " Automated Identification of Dementia Using Medical Imaging: A Survey from Pattern Classification Perspective", Brain informatics(2016), 3:17-27 DOI 10.1007/s 40708-05-0027 Springer.
[2]. American Psychiatric Association and American Psychiatric Association (1994) Task Force on DSM-IV; Diagnostic and statistical manual of mental disorders: DSMIV 4th edition. American Psychiatric Association Washington DC.
[3]. Suhuai Luo et al . ,"Automatic Alzheimer Disease Recognition MRI Data Using Deep Learning Method" , journal of applied mathematics and physics 2017,5, 1892-1898 ISSN Print: 2327-4352.
[4]. S.R.Bhagyashree et al. , " An Initial Investigation in the Diagnosis of Alzeimer's Disease using Various Classification Techniques". 978-1-4799-3975-6/14 2014 IEEE.
[5]. Viswanathan.A. et al. , " Vascular Risk Factors And Dementia: How to Move Forward ?" Neurology 72: Pp 368-74,2009.

In the MINT-Wigris Tool bag are 11 models available for the quantum range. Figure 1 is for fusion, figure 4 for weak bosons decays and figure 8 has eight more tools. One more figure wheel is not shown, it presents the spaces Euler angle for generating as transformation matrices the three quaternionic symmetries for xyz-space rotational axes. More can be constructed where the energy exchange between systems uses different quasiparticles P from a list of about 32. Bases of a 4-dimensional real Hilbert space H4 are used for them and a GF measuring apparatus for P reduces in a Boolean subspace block 24 of H4 one base vector for projective geometrical use. Some GF triples are listed in figure 10. A proof in [1] demonstrates that in figure 9 for hypergraphs of blocks a rgb-graviton in nucleon exists as an additional GF for a 3-cycle of blocks belonging......

[1]. Kalmbach, G. (1983): Orthomodular Lattices. – London New York: Academic Press 390p.
[2]. G. Kalmbach H.E. (2017), MINT-WIGRIS, MINT Verlag, Bad Woerishofen.
[3]. G. Kalmbach H.E. (Chef-Hrsg), MINT (Mathematik, Informatik, Naturwissenschaften, Technik), MINT Verlag, Bad Woerishofen 1997-2020, vol. 1-65.
[4]. Internet video under YouTube: Moebius Transformations Revealed 2014.
[5]. G. Kalmbach, U. Eberspaecher, MINT-Wigris Tool Bag, Bad Woerishofen 2019

In agriculture research, automatic leaf disease detection is essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect symptoms of disease as soon as they appear on plant leaves.To detect disease there are various steps- need to acquire image and preprocess image. Then image segmentation, feature extraction is done in order to go for statistical analysis. The proposed work includes image filtering and convert RGB image to CIE LAB color component. K-mediod technique is used for image segmentation. Lastly by using the neural networks disease is identified and classified.

Keywords: Leaf disease, Image processing, CIELAB color model, SGDM Matrix, Color Co- occurrence Method, k- medoids, Neural Network.

[1] Jayamala K. Patil, Raj Kumar, ―Advances In Image Processing For Detection of Plant Diseases ‖, JABAR, 2011, 2(2), 135-141.
[2] P.Revathi, M.Hemalatha, ― Classification of Cotton Leaf Spot Diseases Using Image Processing Edge Detection Techniques‖, ISBN, 2012, 169-173, IEEE.
[3] H. Al-Hiary, S. Bani-Ahmad, M. Reyalat, M. Braik and Z. ALRahamneh, ― Fast and Accurate Detection and Classification of Plant Diseases‖, IJCA, 2011, 17(1), 31-38, IEEE-2010.
[4] Piyush Chaudhary, Anand K. Chaudhari, Dr. A. N. Cheeran and Sharda Godara, ― Color Transform Based Approach for Disease Spot Detection on Plant Leaf‖, IJCST, 2012, 3(6), 65 -70.

The research work states that there are some existing characteristics of M-commerce. The present work identifies broadcasting capacity as the outstanding characteristics on M-commerce background. The work notifies the role of broadcasting capacity and its respective transactions on M-commerce background. Broadcasting and Its Receiving Agent Based M-commerce Model and Some other are base m-commerce models for proving broadcasting capacity is the identical characteristic. E-commerce activities and tasks have observed from the real market places. The work has noted the m-commerce transaction. The study observed broadcasting capacity as identical characteristic of M-commerce from some other M-commerce models.

Keywords: M-Commerce, Broadcast.

[1]. Trivedi J. H, Dr. Pandya J G, Trivedi P. H, Patel J. B,"Rapid Growth of Customer Use and Adoption Of The Broadcasting Agent and Receivers: A Driving M-Commerce Factor", IOSR Journal of Engineer. ISSN (e): 2250-3021, ISSN (p): 2278-8719 (Vol.1, Issue 1, pp.61-65).
[2]. Trivedi J. H, Pandya J G, Dr. Jani A. N, Trivedi P. H, "Broadcasting and It's Receiving Agent Based M-Commerce Business Model", Research In Management,Research Journal Published by H N G University,Patan Vol.1.
[3]. Trivedi J. H, Darji J. H, Parikh P. P, Trivedi P. H, "Broadcasting and It's Receiving Agent Based M-Commerce Business Model Functioning In The Market", IOSR Journal of Engineering ISSN (e): 2250-3021, ISSN (p): 2278-8719 (Vol.2, Issue 8, Aug 12, 25-33).