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i-manager's Journal on Computer Science (JCOM)

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Blockchain Scalability Analysis and Improvement of Bitcoin Network through Enhanced Transaction Adjournment Techniques
Data Lake System for Essay-Based Questions: A Scenario for the Computer Science Curriculum
Creating Secure Passwords through Personalized User Inputs
Optimizing B-Cell Epitope Prediction: A Novel Approach using Support Vector Machine Enhanced with Genetic Algorithm
Gesture Language Translator using Morse Code

Most Cited

Volume 5 Issue 4 December - February 2018

Research Paper

Adaptive Fuzzy Based Nonlinear Filter For De-speckling Ultrasound Images

Saranya. B.S* , Ramya, A, M. Kowar*

- Research Scholar, Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.

Professor, Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.

Saranya, B.S., Ramya, A., and Murugan, D. (2018). Adaptive Fuzzy Based Nonlinear Filter for Despeckling Ultrasound Images. i-manager’s Journal on Computer Science, 5(4), 1-6. https://doi.org/10.26634/jcom.5.4.14144

Abstract

Medical image processing is used for analyzing medical images, quantitatively. There exists many medical image modalities like Magnetic Resonance Images (MRI), Computed Tomography (CT), Ultrasound (US), etc. Among them, Ultrasound is a conventional device still practiced in medical field. The Ultrasonic image obtained from US devices is often degraded by the speckle noise. Speckle noise degrades the original image quality; so it needs an efficient denoising for despecklng it. Hence, the authors have found a non-linear denoising filter to remove the speckle noise effectively. In this paper, adaptive fuzzy based non- linear filter has been applied to various ultrasound images which got corrupted with the speckle noise. Experimental results are achieved by calculating the performance metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) and Signal-to-Noise Ratio (SNR), that shows the workability of the proposed approach. These results are also compared with other median based denoising filters by analytical proportion.

References

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Research Paper

Location Based Query Processing by Anonymizer

Jency.I*

Assistant Professor, Department of Computer Science and Engineering, Ponjesly College of Engineering, Nagercoil, Kanyakumari District, Tamil Nadu, India.

Jency, I. (2018). Location Based Query Processing by Anonymizer. i-manager’s Journal on Computer Science, 5(4), 7-13. https://doi.org/10.26634/jcom.5.4.14609

Abstract

Location based query services are popular, and have a great demand. The authors have proposed a framework using Anonymous query processing to find the exact location of the places. Previous network database requires no specified storage or functions. In this paper, an anonymous query processing is utilized, where the user can send a query and get the results without leaking their identity to the server. By this anonymous technique, the user can identify the locations very easily using two types of query. This technique has achieved better performance.

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Survey Paper

State of Research on Phishing and Recent Trends of Attacks

Aniket Bhadane* , Sunil B. Mane**

* M.Tech Scholar, Department of Computer Engineering, Government College of Engineering Pune (COEP), Shivajinagar, Pune, Maharashtra, India.

** Associate Professor, Department of Computer Engineering and Information Technology, Government College of Engineering Pune (COEP), Shivajinagar, Pune, Maharashtra, India.

Bhadane, A., and Mane, S.B. (2018). State of Research on Phishing and Recent Trends of Attacks. i-manager’s Journal on Computer Science, 5(4), 14-35. https://doi.org/10.26634/jcom.5.4.14608

Abstract

Phishing attacks cause companies and individuals huge economic as well as intangible damages. Phishing attacks employ a litany of attack vectors. To deal with such attacks, counter work needs to be done in several areas. In this paper, the authors have presented a survey of literature on phishing detection and the current trends in phishing. The authors have also mentioned that phishing detection can be classified into three main categories namely, disallowing attacks to reach the users, user training, and more useful user interfaces. The goal of this paper is to cover all important aspects involved in phishing detection as compared to existing surveys on phishing detection that have focused on individual aspects. There has been a continuous increase in phishing attacks, with a sharp rise in Spear phishing and attacks over Social Media.

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Survey Paper

Edge analytics on Internet of Things: A Survey

K Ramya Sree* , B. Lalitha**

* Research Scholar, Jawaharlal Nehru Technological University, Anantapur, Andhra Pradesh, India.

** Assistant Professor, Jawaharlal Nehru Technological University, Anantapur, Andhra Pradesh, India.

Sree, K.R., and Lalitha, B. (2018). Edge analytics on Internet of Things: A Survey. i-manager’s Journal on Computer Science, 5(4), 36-40. https://doi.org/10.26634/jcom.5.4.14272

Abstract

Internet of Things (IoT) is a system of connected physical objects that are accessible through internet. Values that are allocated to an IP address have the potential to collect and fetch the data over a network, without manual involvement. With continuous developments in Internet of Things (IoT) applications, the conventional computing is facing severe challenges such as high latency, decreased efficiency, long transmission times and increased power consumption. In order to meet these requirements, the data computation and service supply are moved from cloud to edge known as Edge Analytics. An Edge Analytics application utilizes the handling energy of IoT gadgets to channel, pre-process, and total the IoT information. It utilizes the power and adaptability of Cloud administrations to run complex examination on the information, that refers to the enabling technologies allowing computation to be performed at the edge of the network. The term “edge” refers to any computing and network resources along the path between data sources and cloud data centers.

References

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[2]. Ananthanarayanan, G., Bahl, P., Bodík, P., Chintalapudi, K., Philipose, M., Ravindranath, L., & Sinha, S. (2017). Real-Time Video Analytics: The Killer App for Edge Computing. Computer, 50(10), 58-67.

[3]. Chen, Z., Xu, G., Mahalingam, V., Ge, L., Nguyen, J., Yu, W., & Lu, C. (2016). A cloud computing based network monitoring and threat detection system for critical infrastructures. Big Data Research, 3, 10-23.

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[11]. Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3(5), 637-646.

[12]. Stankovic, J. A. (2014). Research directions for the internet of things. IEEE Internet of Things Journal, 1(1), 3-9.

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[14]. Wu, J., & Zhao, W. (2017). Design and realization of WInternet: From net of things to internet of things. ACM Transactions on Cyber-Physical Systems, 1(1), 1-12.

[15]. Yu, W., Liang, F., He, X., Hatcher, W. G., Lu, C., Lin, J., & Yang, X. (2018). A survey on the edge computing for the Internet of Things. IEEE Access, 6, 6900-6919.

[16]. Yu, W., Xu, G., Chen, Z., & Moulema, P. (2013, October). A cloud computing based architecture for cyber security situation awareness. In Communications and Network Security (CNS), 2013 IEEE Conference on (pp. 488-492). IEEE.

i-manager's Journal on Computer Science (JCOM)

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Volume 5 Issue 4 December - February 2018

Adaptive Fuzzy Based Nonlinear Filter For De-speckling Ultrasound Images

Saranya. B.S* , Ramya, A**, M. Kowar***

*-** Research Scholar, Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India. *** Professor, Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.

Saranya, B.S., Ramya, A., and Murugan, D. (2018). Adaptive Fuzzy Based Nonlinear Filter for Despeckling Ultrasound Images. i-manager’s Journal on Computer Science, 5(4), 1-6. https://doi.org/10.26634/jcom.5.4.14144

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Location Based Query Processing by Anonymizer

Jency.I*

Assistant Professor, Department of Computer Science and Engineering, Ponjesly College of Engineering, Nagercoil, Kanyakumari District, Tamil Nadu, India.

Jency, I. (2018). Location Based Query Processing by Anonymizer. i-manager’s Journal on Computer Science, 5(4), 7-13. https://doi.org/10.26634/jcom.5.4.14609

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State of Research on Phishing and Recent Trends of Attacks

Aniket Bhadane* , Sunil B. Mane**

Bhadane, A., and Mane, S.B. (2018). State of Research on Phishing and Recent Trends of Attacks. i-manager’s Journal on Computer Science, 5(4), 14-35. https://doi.org/10.26634/jcom.5.4.14608

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References

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Edge analytics on Internet of Things: A Survey

K Ramya Sree* , B. Lalitha**

* Research Scholar, Jawaharlal Nehru Technological University, Anantapur, Andhra Pradesh, India. ** Assistant Professor, Jawaharlal Nehru Technological University, Anantapur, Andhra Pradesh, India.

Sree, K.R., and Lalitha, B. (2018). Edge analytics on Internet of Things: A Survey. i-manager’s Journal on Computer Science, 5(4), 36-40. https://doi.org/10.26634/jcom.5.4.14272

Abstract

References

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Saranya. B.S* , Ramya, A, M. Kowar*

- Research Scholar, Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.

Professor, Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.

* Research Scholar, Jawaharlal Nehru Technological University, Anantapur, Andhra Pradesh, India.

** Assistant Professor, Jawaharlal Nehru Technological University, Anantapur, Andhra Pradesh, India.