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Diabetic Retinopathy (DR) is a disease caused by abnormalities in blood vessels in the eyes. DR can be detected in the early stages by the Detection of Micro Aneurysms in fundus retinal images. Retinal fundus pictures are commonly used for finding and analysis of DR disease that help ophthalmologists to complete the evaluation of retinal diseases. By reduction in noise level and by enhancing some features in the image pre-processing techniques are adopted. Restoration of images is done to happen by numerous pre-processing techniques. Here in this paper, the comparison of pre-processing in the retinal fundus image is done. For the precise visual view of DR-related highlights, the nature of fundus pictures should be enhanced to a satisfactory level. The difference is a more critical quality than a unique degree of splendor and goals. The main purpose of the pre-processing technique is to increase the diagnostic possibility in fundus images for visual assessment and also for computer-aided segmentation. This paper deals with the comparison of different retinal image denoising technique and their parameters such as MSE, PSNR, Correlation coefficient, RMS values, etc were reviewed and compared with different datasets for retinal images in connection with the identification of DR and Micro Aneurysms (MA).

Spatial Domain filtering; Contrast Enhancement; Vessel enhancement

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P.S. Bindhya, R. Chitra, V.S. Bibin Raj, "A Review on Methods of Enhancement And Denoising in Retinal Fundus Images," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.1-9, 2020.

This paper presents a cloud detection based framework for addressing the problem of accurate cloud detection using Ka-band scanning polarimetric radar (Ka-SPR). This framework benefits from Python , which is capable of pixel level labeling of cloud regions and also for identification approach is proposed to identify Cloud Height(CTH), Cloud Base(CB), Cloud Top(CT) and Cloud Temperature (CTemp). Cloud properties detection is an important application of science and technology to detect clouds and measure the amount of water content over a region. The detection is based on various data collection means. Some most recent techniques for weather data collection are based on graphical data from satellite, sensor data collected from different areas, the radar data for cloud parameters, rain gauge which major liquid precipitation for a specific period and disdrometer data which gives drop size distribution. Correlation of CTH, CT, CB is used for calculating reasonable estimation of these parameters. Estimates may also improved somewhat by an observation of cloud types. By using CT data and Cloud pressure the estimation of CTemp is carried out. Different constants were derived from the microscopic properties correlation consistent with each respective cloud type.

Cloud detection, Ka-band scanning polarimetric radar (Ka-SPR), Cloud Height, Cloud Base, Cloud Top and Cloud Temperature.

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Nikita S. Tandale, S.V.Gaikwad, "Detection of Cloud Top Height, Cloud Base, Cloud Height and Cloud Temperature Using Ka-Band Radar Data," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.10-14, 2020.

Mobile Ad Hoc Network (MANET) is infrastructure free, highly dynamic wireless network, where central administration or configuration by an administrator is very difficult. In contrast to infrastructure based network, MANET supports autonomous and spontaneous networking and thus should be capable of self-organization and configuration. This self-configuring network allows the nodes to automatically configure addresses and routes based on ongoing traffic. Due to the distributed and dynamic nature of MANETs, centralized servers like DHCP cannot be used to assign IP address to nodes. In this paper we present a novel approach DADAR, for the efficient duplicate address detection and auto configuration of nodes in a MANET. Special features of DADAR are the support for frequent network partitioning and merging and very low protocol overhead. Nodes choose initial address using random numbers. Duplicate Address Detection (DAD) algorithm resolves the address conflict which can occur due to partitioning or merging. We are devising a novel approach to detect duplicate address using Address Resolution Protocol. ARP messages are sent by nodes to translate IP address to Hardware address. ARP packets contain the IP address and Hardware address pair of the nodes. These packets are analyzed in the background to identify duplicate addresses and conflicts are resolved. This approach does not introduce any new protocol or packet format.

DADAR, ARP, Duplicate Address Detection, MANET

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K. Victor Rajan, V. Rhymend Uthariaraj, "DADAR: Duplicate Address Detection using ARP in Mobile Ad Hoc Network (MANET)," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.15-20, 2020.

Artificial Intelligence and Machine Learning can be cited as one of the greatest technological advancements in this century. They are revolutionizing the fields of computing, finance, healthcare, agriculture, space, tourism. Powerful models have achieved excellent performance on a myriad of complex learning tasks. One such product of AI is a chatbot. A chatbot is an intelligent software which can simulate a conversation with a user like a real human being. Chatbots have found their use in customer service, recommender systems, smart appliances, etc. Chatbots can be broadly divided into 2 types: Retrieval and Generative. Retrieval type chatbots are trained to provide the best fit answer from a database of predefined responses, whereas, generative type chatbots can generate the final answer from a training corpus. This paper proposes the design and implementation of a generative type travel chatbot using seq2seq model, which can generate answers to the user queries based on Kolkata tourism.

Chatbot, Machine Learning, Neural Network, Deep Learning, NLP

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Subhadeep Jana, Souradeep Ghosh, "Proposal of a Generative type Travel Chatbot using Seq2Seq model," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.21-26, 2020.

With the expanding data moving over the remote frameworks, the channel capacity is lessening on a fast rate. To empower high piece rate information move we need wide channel capacity. This can be actualized by utilizing Multiple Input-Multiple Output (MIMO) that is, executing various sending recieving wires and numerous accepting radio wires. Symmetrical Frequency Division Multiplexing (OFDM) when utilized with MIMO improves the nature of the sending data and limit of the communicating channel. In this examination, MIMO and OFDM are applied together so as to decrease Signal-to-Noise Ratio (SNR) and improve the blunders experienced. Here, different channel assessment methods are dissected and executed, for example, (LS) Least Squares and (MMSE) Minimum Mean Square Error for MIMO-OFDM System. The Bit Error Rate, Mean Square Error (MSE) execution attributes of channel are examined for Quadrature Amplitude Modulation (QAM) conspire over the Additive White Gaussian clamor (AWGN). The general presentation of the proposed strategy and existing procedure is estimated utilizing BER and MSE.

MIMO (Multiple input multiple output), OFDM (Orthogonal frequency division multiplexing), SNR (signal to noise ratio), MSE (Mean square Error), QAM (quadrature amplitude modulation), AWGN (additive white Gaussian noise)

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Randeep Kaur, Sarabjeet Kaur, "MIMO-OFDM System Using Bit Error Rate LS & MSE Analysis in Pilot Based Channel Estimation," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.27-32, 2020.

— Due to the increasing significance of cloud computing, additional and tremendous information of data owners are made to outsource their information to cloud servers for excellent convenience and to lessen cost in information management. However, sensitive information ought to be encrypted before outsourcing for privacy needs that obsoletes information utilization like keyword-based document retrieval. In this paper, a secure multi-keyword search method over encrypted cloud data is described. At the same time it also supports dynamic update operations like deletion and insertion of documents. For index construction and query generation, the vector space model and widely-used TF_IDF model both are combined. A special tree- based index structure is constructed and a “Greedy Depth-first Search” method is proposed to produce economical multi-keyword ranked search. The secure KNN is used to encrypt the index and vectors. It also guarantees about correctness in appropriate score calculation between encrypted index and query vectors. In order to stop statistical attacks, phantom terms are intercalary to the index vector for accurate search results. As special tree-based index structure is used, the proposed method is able to do sub- linear search time and also handle the deletion and insertion of documents flexibly.

Searchable encryption, multi-keyword ranked search, dynamic update, cloud computing

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Poonam Patil, Seema Mane, "Privacy Preserving Search Over Encrypted Data with Secure and Dynamic Operation in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.33-38, 2020.

Social networking has become the topmost application among users to share and communicate information. With the advancement in communication and smartphone capabilities increasing number of users are connected to social network. News items, memes and marketing campaigns are all hosted on social network. Enterprises are also using social network to reach to more customer bases. The popular online social networking platforms such as Twitter, Facebook, Instagram etc. have attracted public helping them connected to family, friends, and relatives. People share videos, texts, pictures, and some confidential information knowingly or unknowingly through these sites and thus, OSNs have become the main source of targets for cyber attackers. Cyberattacks have been increasing for the last few decades throwing a serious threat to the internet world. Security of personal data on social network user is important. In this survey, the various methods of intrusion of social networks for gaining access to private information and the countermeasures are studied. The goal of study is to identify open issues, so that a more secure solution can be designed to solve the problem and discuss about various OSN threats such as misuse of identity, malware, phishing attacks etc. and recommends some of the threat’s preventive measures.

Online Social Networks, Cyberattack, Identity theft, Security

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[7] LinqingLiu, YaoLu, YeLuo "Detecting Smart spammers On Socia lNetwork: A Topic Model Approach" Proceedings of NAACL-HLT 2016
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[16] Shareen Irshad1 and Tariq Rahim Soomro "Identity Theft and Social Media" IJCSNS International Journal of Computer Science and Network Security, VOL.18 No.1, January 2018.
[17] Michael Fire, Dima Kagan, Aviad Elishar, and Yuval Elovici "Social Privacy Protector - Protecting Users’ Privacy in Social Networks" The Second International Conference on Social Eco-Informatics SOTICS 2012.
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Jamuna Rani S., Vagdevi S., "Online Intrusion and Security Measures in Social Networking Environment – A Survey," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.39-45, 2020.

Risk Management is important for insurance industry to ensure the eligibility of a new customer for approval. Insurance companies need to analyze the existing customer’s information such as income, assets, occupation, premium payment records to decide whether a new customer is qualified for an insurance policy. This paper focuses on forecasting the eligibility of the new customers for insurance approval by performing classification on a real time insurance company dataset using three Machine Learning algorithms such as Decision Tree Induction, Naive Bayes Classification and K-Nearest Neighbor algorithms. These algorithms are examined against their classifier accuracy after implementation and the algorithm that demonstrates the best accuracy is chosen for predicting the new customers.

Insurance, Machine Learning, Decision Tree Induction, Naive Bayes Classification and K-Nearest Neighbor, Classifier

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CH. Lakshman Vinay, G. Vijay Sagar, M. Ajay, SK. Hussain, Bh Padma, "Insurance Approval Analysis using Machine Learning Algorithms," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.46-50, 2020.

In this Research we are using canny detector and Hough Transform algorithm for Lane detection. In this research Hough Transformation is use for Find all the edge points in the image using any suitable edge detection scheme and Canny detector for is to detect sharp changes in luminosity (large gradients), such as a shift from white to black, and defines them as edges, given a set of thresholds.

edge detection, histogram, time complexity, accuracy, lane detection

[1]Dr Narapareddy Ramarao 1 B Vivek Bhat 2 Kartik Kulkarni3 Ashley4 Raban Akbary5 1 2 3 4 5 Department of Electrical and Electronics, BMSIT&M, Banglore-64 Corresponding Author; Dr Narapareddy Ramarao, ISSN : 2248-9622 Vol. 9, Issue 3 (Series -VI), pp 28-35, March 2019.
[2]Farid Bounini, Denis Gingras LIV – Université de Sherbrooke Sherbrooke, Canada farid.bounini@usherbrooke.ca denis.gingras@usherbrooke.ca Vincent Lapointe, Herve Pollart Opal-RT Technologies Inc, Montreal, Canada vincent.lapointe@opal-rt.com herve.pollart@opal-rt.com
[3]Proceedings of the International Conference on Computer and Communication Engineering 2008 Kuala Lumpur, Malaysia 978-1-4244-1692-9/08/$25.00 ©2008 IEEE “Real Time Lane Detection for Autonomous Vehicles” Abdulhakam.AM. Assidiq, Othman O. Khalifa, Md. Rafiqul Islam, Sheroz Khan, Department of Electrical & Computer Faculty of Engineering, International Islamic University Malaysia, Jalan Gombak, 53100 K.L., Malaysia. E-mail: khalifa@iiu.edu.my, May 13-15, 2008.
[4] Benefits of V2V Communication for Autonomous and Connected Vehicles, Swaroop Darbha, Shyamprasad Konduri, Prabhakar R. Pagilla
[5]web.ipac.caltech.edu/staff/fmasci/home/astro_refs/HoughTrans_lines_09.pdf

Gurpreet Kaur, Deepinder Kaur, "Apply Canny Detector and Hough Transform For Lane Tracking by Autonomous Type Vehicles," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.51-54, 2020.

Approaches of handwritten signatures is no longer adequate for protection with the development of Internet technology, so the modern technique called digital signature has emerged. Digital signature is more typically used as term encompassing only cryptographic signatures. Digital signatures are mainly used in the delivery of financial transfers, certificates and applications, where the prevention of forgery or tampering of data is crucial. But even within digital signature, there are cryptographic techniques like AES, SHA and asymmetric enciphering mechanism such as ECC combined together to make it highly secure, used three steps mechanism of generation and verification called as 3-D signature. This research paper discusses the combination of all three modes of security such as Symmetrical, Hashing and Asymmetrical cryptography to make the digital signature more secure and invulnerable to attack. The simulation results shows that the proposed 3-D digital signature scheme along with Galois Field is suitable for used in real time environment like IoT, WSN, Cloud computing and low memory devices such as smart cards. The proposed technique is based on mathematical model used in SHA-AES-ECC with Galois Field GF(2n) with irreducible polynomial. Python Programming language is used to grasp the method used.

Digital Signatures, AES, ECC, SHA, Galois Field, 3-D, ECDSA, Encryption using symmetrical and asymmetric cryptography, Hash function, Irreducible Polynomial.

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Mohammad Amjad, Aman Arora, "3-D Digital Signature based on SHA-AES-ECC Scheme using Galois Field over GF(2n)," International Journal of Computer Sciences and Engineering, Vol.8, Issue.12, pp.55-61, 2020.