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The major problem in the transportation system is the interference of the emergency vehicle service, like fire fighting units, ambulance, and so on. When an emergency vehicle arrives on the multilane roadways, it is tough for the private vehicle’s driver to find out the correspondence of the emergency vehicle. Hence, there is a requirement of an intelligent traffic management system for effectively managing the emergency and the normal vehicles. This article surveys various research works in the field of emergency vehicle management. According to the existing works, an emergency vehicle management system is classified into six types, namely smart traffic control system, traffic timer synchronization, traffic forecasting, emergency vehicle recognition, route guidance and navigation for emergency vehicle, and dynamic path planning for emergency vehicle. Finally, an analysis is done based on the published years, techniques used, tools employed and metrics utilized in the emergency vehicle management techniques that are reviewed.

Transportation system, emergency vehicle management, traffic control, path planning, traffic forecasting

[1] V. Venkatesh and N. Syed, "Smart Traffic Control System for Emergency Vehicle Clearance," International Journal of Innovative Research in Computer and Communication Engineering, vol. 3, no.8, pp. 7242-7246, 2015.
[2] M.D. Srivastava, Prerna, S. Sachin, S. Sharma, and U. Tyagi, "Smart Traffic Control System Using PLC and SCADA," International Journal of Innovative Research in Science, Engineering and Technology, vol. 1, no. 2, pp. 169-172, 2012.
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[4] A.S. Amogh, S. Pujari. S.N. Gowda, and V.M. Nyamati, "Traffic Timer Synchronization based onCongestion," In Proceedings of the International Conference on Computational Systems and Information Systems for Sustainable Solutions, pp. 255-260, 2016.
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[7] V. Sciancalepore, K. Samdanis, X. Costa-Perez, D. Bega, M. Gramaglia, and A. Banchs, "Mobile Traffic Forecasting for Maximizing 5G Network Slicing Resource Utilization," In Proceedings of the IEEE Conference on Computer Communications, 2017.
[8] T. Swathi and B.V. Mallu, "Emergency Vehicle Recognition System," International Journal of Engineering Trends and Technology (IJETT), vol. 4, no. 4, pp. 987-990, April 2013.
[9] B. Fazenda, H. Atmoko, F. Gu, L. Guan, and A. Ball, "Acoustic based safety emergency vehicle detection for intelligent transport systems," In Proceedings of the conference on ICCAS-SICE, Fukuoka, Japan, 2009.
[10] Afdhal and Elizar, "Enhanced Route Guidance and Navigation for Emergency Vehicle Using V2I-Based Cooperative Communication," In Proceedings of the International Electronics Symposium, pp. 145-150, 2015.
[11] B. Gong, Z. Yang, and C. Lin, "Dispatching Optimization and Routing Guidance for Emergency Vehicles in Disaster," In Proceedings of the IEEE International Conference on Automation and Logistics, Shenyang, China, pp. 1121-1126, August 2009.
[12] L. Zuo, N. Zhang, Y. He, and T. Zhou, "Research on Dynamic Route Guidance and Navigation System Based on Multi Information Feedback," In Proceedings of the International Conference on Sensing, Diagnostics, Prognostics, and Control, pp. 421- 424, 2017.
[13] H.K. Gedawy, M.B. Dias, and K. Harras, "Dynamic Path Planning and Traffic Light Coordination for Emergency Vehicle Routing," 2009.
[14] C.C. Li, I. Wang, X. Wang, and Y. Zhang, "A Model based Path Planning Algorithm for Self-driving Cars in Dynamic Environment," In Proceedings of the Chinese Automation Congress (CAC), Wuhan, China, 2015.
[15] V. Singh and K.E. Willcoxy, "Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation," AIAA Journal, vol. 55, no. 8, pp. 2727-2738, 2017.
[16] J. Wang, M. Garratt, and S. Anavatti, "Dynamic Path Planning Algorithm for Autonomous Vehicles in Cluttered Environments," In Proceedings of IEEE International Conference on Mechatronics and Automation, Harbin, China, 2016.
[17] J. Zhao, Y. Guo, and X. Duan, "Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction," Journal of Advanced Transportation, pp. 1-14, 2017.
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Cyriac Jose, K.S. Vijula Grace, "Review and Study of Intelligent Techniques in Emergency Vehicle Management System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.366-371, 2018.

Since few decades, the simple password authentication has either replaced or compounded with biometrics (such as Facial Recognition, Fingerprint Scan etc.) to provide better security. Keystroke Dynamics is behavioral biometrics that can perform continuous authentication to detect intruders. In this paper, we investigate whether user specific password gives better performance than artificially rhythmed password. Also, impact of sensory data on overall performance of the system is examined. Finally, Genetic Algorithm is used to optimize the features. The features used to analyze the user data were hold time, flight time and X, Y and Z axis reading from accelerometer sensor. Results showed that user data gives better performance than artificially rhythmed passwords. Best accuracy of around 90% was achieved by using user specified passwords and optimizing the results with genetic algorithm.

Keystroke dynamics, Typing behaviour, Mobile, Authentication, Biometrics

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Baljit Singh Saini, Navdeep Kaur, Kamaljit Singh Bhatia, "Authenticating Mobile Phone User using Keystroke Dynamics," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.372-377, 2018.

The usual approach of planning a trip involves a serious of tedious tasks. The manual way is to book through a travel company, which will give you an itinerary for your trip and the costs involved, another way is to book through an online website, where you can pick a place, look for hotel, book a room and then make travel arrangements to your desired destination. The process involved is time consuming and involves looking through various booking websites to find the best bang for your buck. We propose a solution which will make this process as smooth as possible through the use of an interactive travel bot deployed on social media platforms. In this travel bot, a user enters a query asking for a place to stay in a location. The travel bot then constructs a persona based on transactional history of the user, for example, hotels that the user has shown interest in previously. Using this persona and a wide and deep neural network, personalized recommendations are generated by the travel bot.

Recommender system, TensorFlow, Wide and Deep Learning, Chatbot, Hotel booking

[1] “MyBuys study” available at https://www. digitalcommerce360.com/2009/09/03/product-recommendations-supercharge-online-conversion-rates-stu/ referred on 28/04/17
[2] “Alterra’s Marina” http://alterra.ai/ referred on 26/8/16
[3] “Hello Hipmunk” https://www.hipmunk.com/hello referred on 26/8/16
[4] Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, Rohan Anil, Zakaria Haque, Lichan Hong, Vihan Jain, Xiaobing Liu, Hemal Shah: Google Inc.: Wide and Deep Learning for Recommender Systems

Siddhant Rele, Danish Ali Furniturewala, Sagar Raulo, Neepa Shah, "Intelligent Travel Bot using Wide and Deep Learning," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.378-382, 2018.

Research in recent years has shown integration amongst the significant and dynamic areas of software engineering and semantic web engineering. The success of any software system is depending on how well it meets the requirements of the stakeholders. A software requirement specification written in natural languages, are basically ambiguous, which makes the documentation unclear. Due to unclear requirements, software developers develop software, which is different from the expected software based on the customer needs. Therefore, well documented requirements should be unambiguous and it is possible only when it has only one meaning.The main purpose of this research is to propose a technique that is able to detect ambiguity in software requirements specification document automatically using artificial intelligence. To validate the outcome of the proposed work, generated result of the proposed work will be evaluated and validated by making the comparison between the proposed prototype results, previous ambiguity detection framework and human-generated results to decide how the proposed work is more efficient and reliable for ambiguity detection.

Software Requirements Specification, Artificial Intelligence, Deep Learning, Ambiguity Detection

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Shruti Mishra, Vijay Birchha, Bhawna Nigam, "A Systematic Literature Survey for Detecting Ambiguity in SRS Using Artificial Intelligence," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.383-387, 2018.

The prime objective of this paper is to comprehend the human gait in biometric and biomedical applications. Human gait recognition is recognizing people from the manner in which they walk. It is identified with acquiring biometric data, for example, identity, gender, ethnicity and age from people walking patterns. Likewise, biomedical data can be acquired like individual`s illness, body abnormality. In the walking process, the human body shows general periodic motion, particularly upper and lower limbs, which reflect the person`s unique movement pattern. Contrasted with different biometrics modalities, gait can be acquired from distance and is hard to hide and camouflage. Gait has been topic in PC vision with extraordinary advancement accomplished in ongoing ten years. In this paper, we give a survey over state-of-art gait innovation; focus on different factors in gait methodology and ongoing advances in biomedical engineering.

Human gait, Gait recognition, Biometrics, Biomedical

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[12] W. G. Bhargavas, K. Harshavardhan, G. C. Mohan, A. N. Sharma and C. Prathap, "Human identification using gait recognition," 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, 2017, pp. 1510-1513.
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Ankita Yadav, Dipti Verma, "A Systematic Study of Human Gait Analysis Using Machine Learning Approaches," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.388-393, 2018.

Cloud computing has become a popular model for reducing cost of business, improvise quality of services, and provide good & secure computing. It opens up the Computing World by providing the access to anything and anywhere through Internet. It acts as a spectrum of substantial interest among IT professionals, technocrats & business leaders due to these proven potentials. Numerous emerging computing paradigms database outsourcing serves as future advantages of cloud computing. With the increasing speed of its popularity, many security questions are arising with their respective solutions aiming to give a better understanding of their complex scenario, in this paper we will provide a comprehensive view over security in context of cloud computing and also provide a view of current status of security at present. To start with, we`ll take a look at various Cloud computing models, cloud computing deployment models, key issues in security along with challenges in provocation of permissions to various platforms.

Cloud Computing, secure computing, database outsourcing, deployment models, challenges

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Manjot Kaur Bhatia, Akash Bhardwaj, Diksha Singla, "A Comprehensive Study of Security in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.394-398, 2018.

This paper describes how data mining is used in cloud computing. Data Mining used for extracting potentially useful information from raw data. The integration of data mining techniques into normal day-to-day activities has become commonplace. Every day people confronted with targeted advertising, and data mining techniques help businesses to become more efficient by reducing costs. Cloud computing provides a powerful, scalable and flexible infrastructure into which one can integrate, previously known, techniques and methods of Data Mining. Data security and access control are the most challenging in cloud computing because users send their sensitive data to the cloud service providers. The service providers must have a suitable way to protect their client’s sensitive data. Association rules are dependency rules, which predict occurrence of an item based on occurrences of other items. Apriori is the best-known algorithm to mine association rules. In this paper, we use Modified Apriori algorithm to mine the data from the cloud using sector/sphere framework with association rules.

Data mining, Cloud Computing Association rules

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Avinash Sharma, Sarvottam dixit, N. K. Tiwari, "Association Rules Mining in Cloud Computing Environments using Improved Apriori Algorithm," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.399-403, 2018.

Routers can likewise function as firewalls and perform variety of operations on the incoming and outgoing packets. On the off chance that when every one of the packets share common header attributes, it is named as a packet flow. With a specific end goal to classify a packet, routers perform a query on a classifier table utilizing at least one fields from the packet header to classify the packet into its relating flow. A classifier is a set of rules which distinguish each flow and the fitting actions to be taken for any packet having belonging to that flow. The paper analyzes the problem of packet classification and different proposed systems for the same.

Packet classification, dimensions, fields, flows, prefixes

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Chanchal Pandey, Dipti Verma, "A Study on Various Packet Classification Algorithm for Network Security Systems," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.404-408, 2018.

Detection of source code plagiarism is valuable for both the academia and industry. Plagiarism is an approach of unlawfully stealing other person source code or program code which is a serious issue for common open source programming and other software companies. Numerous techniques have been introduced priori for automatic detection of source code plagiarism using Evolutionary Intelligent algorithm like Genetic Algorithm (GA), Particle Swarm Optimization (PSO) etc. These techniques are more susceptible to premature convergence and more time consuming. In this paper, considering the benefits of artificial immune system, source code plagiarism approach is proposed that overcomes the drawbacks of previous genetic algorithm and particle swarm optimization algorithms. The sparse PCA is employed for dimensionality reduction prior to detection approach for obtained sparse matrix. Using CSA, the detection between source codes is computed and fitness evaluation is measured using Normalized Euclidean distance (NED) and Normalized Cumulative Reciprocal Rank (NCRR).The performance analysis of the suggested approach showed that it has better precision and recall values when compared with existing Meta heuristic based Source code plagiarism detection algorithms.

Source Code detection, Plagiarism approach, Artificial Immune System, Clonal Selection Algorithm, Sparse PCA

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M. Bhavani, K. Thammi Reddy, P. Suresh Varma, "A CSA based Source Code Plagiarism Detection Approach using Sparse Principle Component Analysis," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.409-417, 2018.

In the era of internet, social media has become a big boom for Internet users. These users used to share their day-to-day activities on social media sites like Facebook, Twitter, Flicker and so on. Different data gets uploaded related to users activities like check-ins, GPS locations, tagging friends, travel routes, shopping, dining and photos. The comfort of user convenience has resulted in tremendously increased user count of the Internet. Simultaneously, it is also leading to building of information as a huge database of places, routes, services etc. Considering these all things, our targeted work is to build an enhanced travel advisory and recommendation system. Such a system gives complete freedom to users for choosing their suitable trip options. The users gets able to fetch complete information like statistics of users visited given place, available facilities and most importantly preferred travel routes. All this information can have associated cost options for ease of decision-making. With the help of social media activities like recommendations, likes/dislikes, posts, shares, tags and check-in information, it can build automatic trip advisor to provide better travelling experience with cost-saving and user convenient features. This diverse database can provide features like text-based and pictorial search module. Thus the available maps and locations help users to synchronize their actions with existing routes along with probable route restructuring functionality. Also uses can use the combination of skyline representative concepts and keyword extraction module for appropriate decision making to choose the best place from multiple Places-of Interest (POIs).

Recommendation System, Decision Making, User Convenience, Keyword Extraction, Skyline Representative

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Shital.N.Raul, Nitin N. Patil, "Travel Route Recommendation System using Big-Multisource Social Media: A Survey," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.418-421, 2018.