2nd National Conference of Recent Trends in Computer Science and Information Technology

Paper Type :: Research Paper
Title :: Study On Crepuscule Perception Technologyin Automobiles
Country :: India
Authors :: Anjali Chandekar || Prof. Sandhya Dahake
Page No. :: 01-05
An automobile crepuscule perception machine is a device which increases the vehicle driving force's perception and enables the driving force to peer the gadgets which might be at a distance in darkness or negative climate beyond the attain of motors headlight imaginative and prescient is referred as a technology that provides us with the miracle of imaginative and prescient in total darkness and improvement of vision in low light surroundings. This era is an amalgam of numerous distinctive techniques. The most commonplace strategies defined right here are Low light Imaging, Thermal Imaging and Illumination..............

Keyword :Infrared, Inadequate illumination, Headlights, Visibility, Crepuscule, Perception.

[1]. Jones, Willie D. (March 2006). "Safer Driving in TheDead of Night". IEEE Spectrum. Spectrum.ieee.org.Retrieved 2009-12-08.
[2]. Night vision enhancement systems". I-CAR AdvantageOnline. I-car.com. 2006-05-15. Retrieved 2009-12-08.
[3]. Austin, Ian (October 31, 2005). "Illuminating Road Hazards That Lurk Beyond Lights". New York Times.
[4]. http://media.daimler.com/dcmedia/0-921-1685654-1-815115-1-0-0-0-0-1-0-1549054-0-1-0-0-0-0-
[5]. 0.html?TS=1419958720004 Be ahead: the new Mercedes-Benz S-Class - Superlative in design and technology
[6]. http://media.daimler.com/dcmedia/0-921-1198131-1-1205235-1-0-0-1205704-0-1-0-1549054-0-1-0-0-0-0-
0.html?TS=1419958869248 The 2009 Mercedes-Benz S-Class: Pacemaker in automotive development

Paper Type :: Research Paper
Title :: Machine Learning In Python
Country :: India
Authors :: Ms. Prajakta Ambalkar || Mr. Dhiraj Rane
Page No. :: 06-12

Scikit-learn is an increasingly popular machine learning library. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various contexts. In this paper, we present and discuss the libraries that arenumpy, pandas,scipy also discuss the design choices for the application programming interface (API) of the project. In particular, we describe the simple and elegant interface shared by all learning and processing units in the library and then discuss its advantages in terms of composition and reusability. Scikit-learn is the package focuses on bringing machine learning to non-specialists using a generalpurpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings.

Keywords: API, NumPy, Pandas,SciPy, Algorithms, Models, and Modules.

[1]. Springer article_available:https://link.springer.com/article/10.1007%2FBF00116251
[2]. Total LLC [US] (2010 - 2019) _available_https://www.toptal.com/python/python-machine-learning-flask-example
[3]. Intro to Pandas: -1: An absolute beginners guide to Machine Learning and Data science._"HACKER NOON"_ available:https://hackernoon.com/intro-to-pandas-1-an-absolute-beginners-guide-to-machine-learning-and-data-sciencea1fed3a6f0f3
[4]. This is an archival dump of old wiki content --- see scipy.org for current material_ available:https://scipy.github.io/oldwiki/ pages/History_of_SciPy
[5]. SPRINGER NATURE_ Kluwer Academic Publishers 1986 (2018)Introduction of Decision Tree_ available: https://scipy.github.io/old-wiki/pages/History_of_SciPy

Paper Type :: Research Paper
Title :: A Survey Of Indoor Positioning Using Mobile Cellular Network
Country :: India
Authors :: ms.Pooja Salame || ms.Bhagyashree Ambulkar
Page No. :: 13-17

The demand for Indoor Location Based Services (LBS) is increasing over the past years as Smartphone market expands. There's a growing interest in developing efficient and reliable indoor positioning systems for mobile devices. Smartphone users can get their fixed locations according to the function of the GPS receiver. This is the primary reason why there is a huge demand for real-time location information of mobile users. However, the GPS receiver is often not effective in indoor environments due to signal attenuation, even as the major positioning devices have a powerful accuracy for outdoor positioning.



[1]. Boon-Giin Lee, Young-Sook Lee, Wan-Young Chung; 3D Navigation Real Time RSSI-based Indoor Tracking Application,JournalofUbiquitousConvergenceTechnology, Vol.2, No.2, November 2008, pages 67-77
[2]. Cliff Randell Henk Muller; Low Cost Indoor Positioning System , report , Department of Computer Science, University of Bristol,UK.
[3]. https://en.wikipedia.org/wiki/Global_Positioning_System
[4]. http://www.n2yo.com/
[5]. R.Want , A.Hopper,V.Falcao and J.Gibbons; The activeBadge location system,ACM Transactions on Informationsystems Vol. 40, No. 1, pp. 91-102, January 1992

Paper Type :: Research Paper
Title :: Super Intelligence Futurescope
Country :: India
Authors :: Ms. Vikas K. Ravidas || Prof. Rashmi Dukhi
Page No. :: 18-25

Studies of super intelligent-level systems have typically posited AI functionality that plays the role of a mind in a rational utility-directed agent, and hence employ an abstraction initially developed as an idealized model of human decision makers. Today, developments in AI technology highlight intelligent systems that are quite unlike minds, and provide a basis for a different approach to understanding them: Today, we can consider how AI systems are produced (through the work of research and development), what they do (broadly, provide services by performing tasks), and what they will enable (including incremental yet potentially thorough automation of human tasks). Because tasks subject to automation include the tasks that comprise AI research and development, current trends in the field promise accelerating AI-enabled advances in AI technology itself, potentially leading to asymptotically recursive improvement..........

Keywords: Artificial Intelligence(AI), Center for Artificial IntelligenceinSociety(CAIS)

[1]. Halal, William E. "TechCast Article Series: The Automation of Thought" (PDF). Archived from the original (PDF) on 6 June 2013.
[2]. Aleksander, Igor (1996), Impossible Minds, World Scientific Publishing Company, ISBN 978-1-86094-036-1
[3]. Omohundro, Steve (2008), The Nature of Self-Improving Artificial Intelligence, presented and distributed at the 2007 Singularity Summit, San Francisco, CA.
[4]. Johnson, Mark (1987), The body in the mind, Chicago, ISBN 978-0-226-40317-5
[5]. Kurzweil, Ray (2005), The Singularity is Near, Viking Press

Paper Type :: Research Paper
Title :: Study Of Animal Health Detection Techniques
Country :: India
Authors :: Priya. N. Dubey || Rupali Chikhale
Page No. :: 26-31

In previous year it is difficult to detect the internal health problem of Animals. Outer health problem we detect easily by examine it and cure it. But it is difficult to detect the internal issues because they are speechless we can't examine properly what is exact problem or issue. By the latest technology like Bioscope sensor, wearable belt, Pulse detector etc. it became easy to detect the health issue of animals. In earlier periods the symptoms are not recognized easily it takes more days to recognize the exact problem. The latest technologies are the Quantified Ag system, by using which we examine easily.

Keywords: Bioscope, Pulse detector, Wearable belt

[1]. https://www.researchgate.net/publication/310591484_Recent_advances_in_wearable_sensors_for_animal_health_management
[2]. https://www.biorxiv.org/content/biorxiv/early/2017/04/19/128504.full.pdf
[3]. https://www.biorxiv.org/content/biorxiv/early/2017/04/19/128504.full.pdf
[4]. https://www.researchgate.net/publication/304425631_Application_of_wireless_sensor_networks_for_beehive_monitoring_and_inhive_ thermal_patterns_detection
[5]. https://www.researchgate.net/publication/275517604_Remote_Beehive_Monitoring_using_Acoustic_Signals

Paper Type :: Research Paper
Title :: Augmented Reality In Jewellery
Country :: India
Authors :: Mohini Ikhankar || Prof. Sandhya Dahake
Page No. :: 32-36

Augmented reality is new emerging technology, where things in the physical world are mixed with virtual content to increase user experience and simplicity. As augmented reality technology allows us to create a virtual world on top of the physical world, this can be used to share same physical resources with multiple users. During the recent years, the augmented reality technology has been taking over in distinct regions of business,most firmly in retail and e-commerce.With a new generation of consumers (i.e. millennials), new approaches in sales are vital to keeping your business in step with time. We are involved in the implementation of AR in the jewelry Industry to increase customer satisfaction and experiences.In this review paper, we basically present how AR actually works in jewellery.

Keywords- Augmented reality, Real world, Jewellery, Apps.

[1]. Ithinyai Moses Mutwiri "Research paper on Augmented Reality", South Eastern Kenya University, unpublished M. Young, The Technical Writer's Handbook. Mill Valley, CA: University Science, 1989.
[2]. R. Alain Pagani, Jose Henriques, Didier Stricker "Sensors for location based augmented reality: the example of Galileo and Egnos", The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B1, 2016
[3]. Nivedha, Hemalatha "A Survey on Augmented Reality", International Research Journal of Engineering and Technology, 2015
[4]. Miss. Arti Yadav, Miss. Taslim Shaikh, Mr. Abdul Samad Hujare, Prof. Murkute P. K.(Guide) "A Survey on interior Design using Augmented reality", International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 4 Issue 5, May 2015
[5]. Vikas Tiwari, Vijay Prakash Tiwari and Dhruvesh Chudasama "Augmented Reality and its Technologies", International Research Journal of Engineering and Technology (IRJET) Volume: 03 Issue: 4 April, 2016

Paper Type :: Research Paper
Title :: Machine Learning And Deep Learning Method For Computer Data Prevention
Country :: India
Authors :: Ms. Diksha Shankarrao Burde || Mr. Dhiraj Rane
Page No. :: 37-45

Machine learning and deep learning is adopted in a wide range of domains where it shows its superiority over traditional rule-based algorithms. These methods are being accommodatedfor computer data prevention systems with the goal of supporting or even replacing the first level of security analysts. Although the complete automation of detection and analysis is an enticing goal, the efficacy of machine learning and deep learning in computer data prevention must be evaluated with the due intensity. We present an analysis, addressed to security specialists, of machine learning techniques applied to the detection of intrusion, malware, and spam. The goal is twofold: to assess the current maturity of these solutions and to identify their main limitations that prevent an immediate adoption of machine learning and deep learning data prevention schemes. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems.

Keywords: Machine learning, deep learning, Computer data prevention

[1]. Zhi Liu (liuzhi@sdu.edu.cn) (2018) ,‖Machine Learning and Deep Learning Methods for Cybersecurity‖, Available: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8359287
[2]. Multiple Authors ,White Paper (2019 ),―MACHINE-LEARNING ERA IN CYBERSECURITY‖, Available:https://www.welivesecurity.com/wpcontent/uploads/2019/02/ESET_MACHINE_LEARNING_ERA.pdf
[3]. A. F. Agarap. (2017). ‗‗A neural network architecture combining gated recurrent unit (GRU) and support vector machine (SVM) for intrusion detection in network traffic data.'' [Online]. Available: https://arxiv.org/abs/1709.03082
[4]. Vinayakumar R1, Barathi Ganesh HB1,2, Prabaharan Poornachandran3, Anand Kumar M4 and Soman KP1 1Centre for Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore 2Arnekt Solutions Pvt Ltd, Pune, Maharashtra, India
[5]. 3Center for Cyber Security Systems and Networks, Amrita School of Engineering, Amritapuri, AmritaVishwa Vidyapeetham, India 4Department of Information Technology, National Institute of Technology, Karnataka, Surathkal. Mangalore. Available: file:///D:/idm/1812.03519.pdf

Paper Type :: Research Paper
Title :: Devops Cloud Computing Service
Country :: India
Authors :: Ms.Shubhangi Ramesh Dahake || Ms.Bhagyashree Ambulkar
Page No. :: 46-47

Whether you call it service-oriented architecture (SOA), modular computing or Web services, this new model breaks applications into pieces and connects them with workflow interfaces. Developers must send all integration and workflow information to those deploying and managing the application. This communication between developers and operations -- along with the processes that facilitate it -- was pegged as DevOps in 2009. Today, DevOps also refers to tools that use real-time development data to automate application deployment.

[1]. https://www.ibm.com/cloud/garage/architectures/devOpsArchitecture/reference-architecture/At QCon London, David Farley
(@davefarley77) told the audience that "continuous delivery changes the economics of software delivery".

Paper Type :: Research Paper
Title :: Visual Cryptography for Color Images
Country :: India
Authors :: Miss Reeta L. Apurkar || Prof. Rupali Chikhale
Page No. :: 48-51

"An image is worth a thousand words." This aphorism is indeed true. Huge amount of data available to us is in form of images which makes image
processing an indispensable operation. Digital Image Processing is a rapidly growing field with vast applications in science and engineering. Image processing developing the machine that could perform the visual functions over an image and words

Keywords: Visual Cryptography, halftonning, secret sharing scheme, Error diffusion.

[1]. Rafel C. Gonzalez and Richard E. Digital Image Processing.
[2]. http://www.ph.tn.tudelft.nl/Courses/FIP/noframes/fip-Contents.html
[3]. http://chesapeake.towson.edu/data/all_composite.asp
[4]. http://zone.ni.com/devzone/conceptd.nsf/webmain/709A9F665E431C5986256C3A006B4EB1
[5]. http://rkb.home.cern.ch/rkb/AN16pp/node130.html

Paper Type :: Research Paper
Title :: Hand Gesture Recognition
Country :: India
Authors :: Devyani Sengupta || Prof Sandhya Dahake
Page No. :: 52-56

In recent years, deep learning algorithms have become increasingly more prominent for their unparalleled ability to automatically learn discriminant features from large amount of data. Gesture recognition is a hot topic in computer vision and pattern recognition, which plays a vitally important role in natural human-computer interface. Although great progress has been made recently, fast and robust hand gesture recognition remains an open problem. Since the existing methods have not well balanced the performance and the efficiency simultaneously.

Keywords: Hand gesture recognition, fast, robust

[1]. Deep Learning for Electromyographic Hand GestureSignal Classification Using Transfer Learning Ulysse Cˆot´e-Allard, Cheikh Latyr Fall, Alexandre Drouin, Alexandre Campeau-Lecours, Cl´ement Gosselin, Kyrre Glette, Franc¸ois Laviolettey, and Benoit Gosseliny
[2]. Fast and Robust Dynamic Hand Gesture Recognition via Key Frames Extraction and Feature Fusion Hao Tang, Hong Liu, Wei Xiao, Nicu Sebe

Paper Type :: Research Paper
Title :: Mobile Operating System in Today's Era
Country :: India
Authors :: Pranali Bhute || Mr. Dhiraj Rane
Page No. :: 57-64

Earlier mobile communication technologies were dominated by vertically integrated service provision which are highly bounded mainly to voice and short message services that are organized in a monopolistic competition between few mobile virtual network operators, service providers and enhanced service providers. In the recent years, however, radical change driven by advancements in technology, witnessed the introduction and further development of smartphones where the user can get access to new applications and services by connecting to the device manufactures' application stores and the like. These smartphones have added many features of a full-fledged computer: high speed processors...........

Keywords: Mobile OS, Android, iOS, Windows Phone, Black-Berry OS, webOS and Symbian.

[1]. Apple1, (2014): "The Application Runtime Environment." Available: http://developer.apple. com/library /ios/#documentation/iphone/conceptual/iphoneosprogrammingguide/ Runtime Environment/RuntimeEnvironment.html
[2]. Apple2, (2014): "iphone in Business Security Overview." Available: http:// images. apple. com /iphone/business/docs/iPhone Security.pdf
[3]. CMER, (2014): "Mobile Operating System" Centre for Mobile Education and Research
[4]. DEVECO, (2013) "Developer Economics Q3 2013 Analyst Report" available at http://www.visionmobile.com/DevEcon3Q13
[5]. Fitzek F. and Reichert F. (2007): "Mobile PhoneProgramming and its Application to Wireless Networking" available at http://www.springerlink. com/content/978-1-4020-5968-1

Paper Type :: Research Paper
Title :: Study on Fog Computing
Country :: India
Authors :: Pranita Pusadkar || Mrs. Rashmi Dukhi
Page No. :: 65-69

Fog computing is a paradigm that expands cloud computing and services to the edge of the network. Similar to cloud Fog computing implement data, compute, storage, and relevance services to end users. In this paper elaborate the advantages of Fog computing and analyze its relevance's of real scenarios, such as smart traffic lights in vehicular networks, smart grid etc. Security and privacy issues are further impart according to current Fog computing paradigm. As example a typical barrage, man-in-middle barrage in Fog computing.

Keywords: Fog computing, Internet of things, Cloud computing, Smart streetlights, Latency.

[1]. CISCO. IoT Reference Model White Paper; CISCO: San Jose, CA, USA, 2014.
[2]. Arkin, H.R.; Diyanat, A.; Pourkhalili, A. MIST: Fog-based data analytics scheme with cost-efficient resource
[3]. provisioning for IoT crowd sensing applications. J. Netw. Comput. Appl. 2017, 82, 152–165.
[4]. Bonomi, F.; Milito, R.; Zhu, J.; Addepalli, S. Fog Computing and Its Role in the Internet of Things.
[5]. Stojmenovic, I.; Wen, S. The Fog computing paradigm: Scenarios and security issues. In Proceedings of the 2014 Federated Conference Computer Sciencean Information Systems (FedCSIS),Warsaw, Poland, 7–10 September 2014; pp. 1–8.

Paper Type :: Research Paper
Title :: Virtual Brain
Country :: India
Authors :: Miss. Smita S. Deulkar || Prof. Rupali Chikhale
Page No. :: 70-76

Today the scientists are researching for creating the artificial brain that is able to think, respond, to take decision, and store anything in memory. The main aim is that, uploading human brain into the machine. So that mancould think, that takes decisionseffortlessly. After the death of the body, the virtual brain will act as the man that means after the death of a person the data will not be loss like the knowledge, intelligence, personalities, feelings and memories of that man, whichwill be used for the development of the human society. Technology is growing faster with every day. IBM has now jumped in research for creating a virtual brain that is called as "Blue brain". If it is possible, then this would be the very first virtual brain of the world. IBM, is in partnership with the scientists at Switzerland's Ecole Polytech-nique Federale...........

Keywords: The Simulation, the Blue-gene, The Module,The Neural Code.

[1.] https://www.scribd.com/document/119046307/Chapter-5

Paper Type :: Research Paper
Title :: Research Paper on Basic Parallel Processing
Country :: India
Authors :: Ms. RupaYashwantaNagpure || Prof Sandhya Dahake
Page No. :: 77-83

In computers, parallel processing is the processing of program instructions by dividing them among multiple processor with the objective of running a program in less time. The next improvement was multiprogramming. In a multiprogramming system, multiple programs submitted by users were each allowed to use the processor for a short time. To users it appeared that all of the programs were executing at the same time. Problems of resource contention first across in these systems. Explicit requests for resources led to the problem of the deadlock. Competition for resources on machines with no tie-breaking instructions lead to the critical section routine. Vector processing was another attempt to increase performance by doing more than one thing at a time.

Keywords: Parallel Processing, multiprogramming, SISD, SIMD, MISD, MIMD

[1]. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=2ahUKEwjGwbH0xdbhAhUKc CsKHVT4Be0QFjABegQIABAB&url=https%3A%2F%2Fcomputing.llnl.gov%2Ftutorials%2Fparallel_comp%2F&usg=AOvVaw13yn9AyxPEwKPIU2Z2QVNW
[2]. https://www.google.com/search?client=firefox-b-d&q=evolution+of+parallel+computers
[3]. https://computer.howstuffworks.com/parallel-processing.htm
[4]. https://www.sciencedirect.com/science/article/pii/S096007790000223X

Paper Type :: Research Paper
Title :: Technical Support and Implementation of AI
Country :: India
Authors :: Manisha Dudhe || Mr. Dhiraj Rane
Page No. :: 84-89

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision. Nowadays lots of research is going on towards the development of application based on the artificial intelligence. In older days, traditional and successful programming languages were using for the development of AI. But, there is efforts to have the new tools and programming language for the AI implementation. This paper summarises the various programming languages available for the implementation of AI. It also discuss various system for the study of AI.

Keywords:Artificial Intelligence, Robotics, Lisp, Programming, Machine Learning.

[1]. Definition of AI as the study of intelligent agents:Poole, Mackworth & Goebel 1998, p. 1, which provides the version that is used in this article. Note that they use the term "computational intelligence" as a synonym for artificial intelligence.
[2]. Russell & Norvig (2003) (who prefer the term "rational agent") and write "The whole-agent view is now widely accepted in the field" (Russell & Norvig 2003, p. 55).
[3]. Nilsson 1998Legg & Hutter 2007.^ Russell & Norvig 2009, p. 2.
[4]. Maloof, Mark. "Artificial Intelligence: An Introduction, p. 37" (PDF). georgetown.edu.Schank, Roger C. (1991). "Where's the AI". AI magazine. Vol. 12 no. 4. p. 38.
[5]. Jump up to:a b Russell & Norvig 2009.Jump up to:a b "AlphaGo – Google DeepMind". Archived from the original on 10 March 2016.

Paper Type :: Research Paper
Title :: Study On Aquatic Animal Tracking
Country :: India
Authors :: Pooja Balbudhe || Mrs. Rashmi Dukhi
Page No. :: 90-96

Aquatic animal tracking is significantly improving our understanding of aquatic animal behaviour and are emerging as key sources of information for conservation and management practices. Over the past three decades, passive acoustic telemetry has significantly helped marine scientist to study and understand the spatial ecology, migratory behaviours, and mortality rates of aquatic animals. A popular telemetry system consists of two components: an acoustic transmitter tag attached to an aquatic animal and powered by a small battery, and a stationary station that receives the acoustic signals from the tagged animal and determines its location. The added weight and increased size of the tag introduced by the battery limit the implementation of this system to relatively large animals............

Keywords:Acoustics, Animals, Magnetoacoustics effect, Environmental monitoring.

[1]. http://imos.org.au/facilities/animaltracking/
[2]. https://atstrack.com/animal-class/marine-mammals.aspx
[3]. https://academic.oup.com/bioscience/article/67/10/884/4103291
[4]. https://www.sciencedirect.com/topics/earth-and-planetary-sciences/aquatic-organism
[5]. Auger-Méthé M, Albertsen CM, Jonsen ID, Derocher AE, Lidgard DC, Studholme KR, Bowen WD, Crossin GT, Flemming JM. 2017. Spatiotemporal modelling of marine movement data using Template Model Builder (TMB). Marine Ecology Progress Series 565: 237–249.