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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder dementia. The main challenges for medical investigators have been the early diagnosis of patients with AD because an early diagnosis can provide greater opportunities for patients to be eligible for more clinical trials. The transitional state between healthy control (HC) and AD with mild memory problems is Mild cognitive impairment (MCI). A reliable diagnosis of MCI can be very effective for early diagnosis of AD. In this study, a fast and accurate method based on rotation invariant descriptors is proposed and moments are used to distinguish the patients with AD and MCI from normal participants (HC) using structural Magnetic Resonance Images (MRI). The rotation invariant descriptors are among the best region based shape descriptors which are used in many medical image processing applications. The angular radial transform (ART) is one such rotation invariant descriptors. This descriptor has two essential characteristics as compared to moment based descriptors, viz., it has low computation cost and provides a large number of numerically stable features. However, its kernel consists of the sinusoidal functions which still needs high computation time. In this paper, we developed fast and effective method to compute the radial & angular sinusoidal functions using 8-way symmetry and also used fast & recursive method to extract the features from MRI images using OFMMs. These methods are used not only for binary images but for gray level images also. The proposed method is not only fast but also more reliable and numerically stable.

Alzheimer, Early Diagnosis, Rotation Invariant Descriptors, Angular Radial Transform, Mild cognitive impairment, Healthy control, Orthogonal Fourier Mellin Moments, Zernike Moments

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R. Upneja, A. Prashar, "An Effective Method for early Diagnosis of Alzheimer Disease using Angular Radial Transform and Orthogonal Fourier Mellin Moments," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.1-9, 2017.

Computationally speaking, there are a few ways to tackle problems of rule-based permutations and iterations. This paper seeks to explore two algorithms and their possible application in the field of bioinformatics and biochemical engineering. We believe that accurately predicting RNA secondary structure formations can only be achieved by extensive analysis of specific RNA folds that have already been documented to occur in nature and others like them that have the same Amino acid sequence structure and similar minimal free energies. This paper focuses on algorithms to extract every single RNA sequence that fits a given amino acid sequence. We concern ourselves mainly with the computation intensive issue of the outputting various permutations of given protein sequences and their respective minimal free energies. Results: We present a way to computationally improve analysis of secondary structure minimization. Using C++, Sequence permutations of amino acids are extracted to be analyzed in terms of minimum free energies. ViennaRNA-2.1.6 is used to facilitate our computation of the RNA fold and the corresponding minimal free energy. The Odometer Weighted Counter (OWC) approach comes in second with its critical length of six amino acids and a computations time of 68 seconds. The Vector Permutation Mapping (VPM) approach comes in as the more desirable approach with a critical length of 10, and a computation time of 26896 seconds. All tests were made on critical path length of sequences. An output of importance to our paper is the minimal free energy of each RNA sequence that the ViennaRNA RNAfold function processes. Analysis of the resulting minimal free energies in comparison to already documented RNA strings in nature is the key to more effective secondary structure prediction.

RNA, minimal free energy, amino acid, folding, ViennaRNA

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E. Lloyd-Yemoh, H.B. Shi, "Minimum Free Energy-Based Amino Acid Sequence Permutation From Amino Acid," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.10-15, 2017.

Wireless sensor network are gathering of number of mobile nodes which are associated wirelessly with each other to carry out some tasks. Wireless sensor network are self-configured, infrastructure less network. In a WSN an effective utilization of resources is a vital issue because nodes in the network depend on limited resources like battery power. Hence, energy efficient routing for this network is essential which will provide better performance with the restricted resources. The purpose of this paper is to design energy aware routing protocol; here we consider classical AODV and Modified AODV (M-AODV). This protocol based on remaining energy of each node which will help to lengthen the life of network. Network Simulator NS-3.20 determined for simulation between AODV and M-AODV.

Wireless Sensor Networks, AODV, M-AODV, Energy Efficiency

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[9] Umesh Kumar Singh, Jalaj Patidar and Kailash Chandra Phuleriya, "On Mechanism to Prevent Cooperative Black Hole Attack in Mobile Ad Hoc Networks", International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.1, pp.11-15, 2015.
[10] R. Kumar, S. Tripathi, R. Agrawal, "Energy Efficient Routing Protocol for Secure Wireless Sensor Network", International Journal of Computer Sciences and Engineering, Vol.5, Issue.4, pp.1-4, 2017.
[11] Pallavi S. Katkar, Vijay R. Ghorpade, “Fuzzy Approach to Predict Mobility and Energy To Prolong the Life of Wireless Sensor Network”, IEEE International Conference on WIECON-ECE, December 2016.
[12] Ruchi Gupta, Akhilesh A. Waoo, Sanjay Sharma and P. S. Patheja, “A Research Paper on Comparison between Energy Efficient Routing Protocol with Energy and Location in MANET”, Journal of Computer Engineering, Vol. 9, Issue 4, 2013
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[14] R.Kumar, S.Tripathi, R.Agrawal, “Energy Efficient Routing Protocol for Secure Wireless Sensor Network”, International Journal of Computer Sciences and Engineering, Vol. 5, Issue. 4, pp.1-4, Apr-2017

Pallavi S. Katkar, Vijay R. Ghorpade, "Energy Efficient Modified AODV for Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.16-19, 2017.

In this paper we have studies the effect of coefficient of variation (CV) on single sampling plan for variables indexed by acceptable quality level (AQL) and average outgoing quality limit (AOQL)based on the assumption of normality and independence are affected when the characteristic of an item possesses a normal distribution. Procedures and tables are given for the selection of single sampling plans for variables for given AQL and AOQL, whenever rejected lots are 100% inspected for replacement of nonconforming units. The operating characteristic (OC) function is described for different values of coefficient of variation. It is clear that the value of OC function with known CV shows higher values for the lot of bad quality. The values of n and k are also calculated with known coefficient of variation.

CV, sampling plan, AQL, AOQL, OC

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J.R. Singh, A. Sanvalia, "Single Sampling Plan for Variable Indexed by AQL and AOQL with Known Coefficient of Variation," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.20-25, 2017.

Vehicular Ad-hoc Network (VANET) is a variant of Mobile Ad-hoc Network (MANET).The key goal of VANET is to facilitate communications among vehicles and also amongst vehicles and fixed infrastructure. Regardless of the fact that VANET is considered as a sub-class of MANET, it has distinctive features in terms of high mobility of vehicles, fabricating to recurrent topology changes, random node density and boundless network size. Hence most of the clustering algorithms considered for MANET are inappropriate for VANET. Much of the literature recently published focus on clustering in VANETs. However most of them are concentrated on diminishing network overhead value, number of clusters formed and do not consider the vehicles interests (viz. traffic congestion, looking for petrol pumps, free parking space, etc.). To decrease the complexity of transmissions, only context-aware data is required to be communicated to the intended recipients as needless information may cause a performance bottleneck in VANETs. Hence in this paper, we propose a context aware multicast/clustered routing algorithm based on agent technology which addresses above mentioned issues and improves the performance parameters associated with routing in VANET. The performance of the proposed scheme is tested with respect to bandwidth consumption, cluster formation time, multicast grouping time and communication overhead.

VANETs, Cluster, Multicast, Context, Interest

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A. D. Devangavi, Rajendra Gupta, "Multi-Agent Based Context Aware Multicast Routing in VANET," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.26-37, 2017.

Content based image retrieval (CBIR) has been one of the significant research areas in computer science in the recent time. Various feature like Texture, color & shape are used in CBIR for image retrieval. Basically, color is the most striking feature in the content based image retrieval. Different extraction methods are used in content based image retrieval (CBIR). A retrieval method which is based on color histogram by using fuzzy inference system approach is proposed in this paper. We propose a fuzzy rule based approach with27 rules, for effective image retrieval. The experimental results show the robustness and the efficiency of the proposed system for CBIR.

CBIR, Fuzzy, Fuzzy Inference System ,Color Histogram

[1] Nadira T., Rehna K., Fepslin Athish Mon, "A Study and Analysis on Feature Extraction in Content-Based Image Retrieval", International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.305-307, 2017.
[2] Sergyan, Szabolcs. "Color histogram features based image classification in content-based image retrieval systems”, Applied Machine Intelligence and Informatics, 2008. SAMI 2008. 6th International Symposium on. IEEE, 2008.
[3] P. Rachana, S. Ranjitha, H.N. Suresh, "Stride Towards Developing an CBIR System Based on Image Annotations and Extensive Multimodal Feature Set", International Journal of Computer Sciences and Engineering, Vol.2, Issue.1, pp.18-22, 2014.
[4] Raina, Nikita, et al. "A fused features approach on Content-Based Image Retrieval based on Fuzzy rule-set", Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on. IEEE, 2014.
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[8] Alladi Ujwala, Nagaratna P. Hegd, “Image Retrieval Using Quadratic Distance Based On Color Feature And Pyramid Structure Wavelet Transform And Glcm Based On Texture Feature”, International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 2, Issue 4 (July-Aug 2014), PP. 169-172
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Dahale Sunil V., Thorat S.B., P.K. Butey, M.P. Dhore, "Efficient Content Based Image Retrieval Using Fuzzy Approach," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.38-43, 2017.

Multi-cluster environment consists of computational nodes that allow computational problems with resource requirement more than those available resources in a cluster to be treated. Scheduling jobs in heterogeneous multi-cluster environments where each cluster has varied number of processors and each computational node has a varying speed is NP hard. Thus, we always search for sub-optimal solution for scheduling jobs. Various meta-heuristics have been proposed for scheduling jobs. The literature shows that the Genetic algorithm has been employed for parallel jobs scheduling in heterogeneous multi cluster environment. But it suffers from certain limitations like slow convergence speed, local optima problem. In this research work, a Grey Wolf Optimization algorithm (GWO) has been introduced in order to minimize makespan, flowtime and mean waiting time. The proposed methodology has shown quite significant improvement over available ones.

Heterogeneous multi-cluster environment, Scheduling, Co-allocation, Grey wolf Optimization Algorithm(GWOA))

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Sapinderjit Kaur, Kirandeep Kaur, Amit.Chhabra, "Parallel Job Scheduling Using Grey Wolf Optimization Algorithm for Heterogeneous Multi-Cluster Environment," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.44-53, 2017.

In this paper, we present a survey of the spanning trees. The general properties of spanning trees, algorithms for generation of all possible spanning trees from a graph and minimum spanning tree algorithms are discussed in this paper. The purpose of this study is to give fundamental details on the spanning trees and related work done based on their application domains. The application domains include computer networks, bio-informatics, image processing etc. It is found that research related to spanning trees can be related to the area of graph mining.

Graph, Spanning Tree, Minimum Spanning Tree

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K. Lakshmi, T. Meyyappan, "Spanning Tree- Properties, Algorithms and Applications," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.54-58, 2017.

Internet is expanding day by day in terms of its users and websites. Web Analytics is the process of measuring statistics of the website and analyzing the behaviour of traffic. 39 percent of the companies present now do not use any web analytics. This paper studies evolution of web analytics, the strategic methodologies that allows us to assess online activities, process, and the tools used. This paper also discusses the benefits obtained to small and large scale businesses if they incorporate web analytics to their websites.

Web analytics, Java script, e-commerce, web usage, log file, page tagging

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[4] Prasanthi, B. V., Prathyusha Kanakam, and S. Mahaboob Hussain. "Cyber Forensic Science to Diagnose Digital Crimes-A study."International Journal of Scientific Research in Network Security and communication (IJSRNSC),2017
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U.Padma Jyothi, Sridevi Bonthu, B V Prasanthi, "A Study on Raise of Web Analytics and its Benefits," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.59-64, 2017.

Groundwater is an important natural resource available on the earth. Contamination of groundwater resources has become a major problem today due to some artificial and natural activities. Identification of groundwater pollution sources is a major step in groundwater pollution remediation. A pollution source is said to be known only when its source characteristics (location, strength and duration of pollution activity) are known. Identification of unknown groundwater pollution source is an inverse problem, which is generally ill posed due to existence of local minima. This problem becomes more complex for real field conditions, when the lag time (defined as the time difference between the first reading at the observation well and the time when source becomes active) is not known. Genetic Algorithm (GA) based simulation optimization methodology has been used in this study for complete identification of unknown groundwater pollution source. GA is non-gradient based search technique and it is capable of finding the global optimum. A contaminant transport model, which can simulate the concentrations at the observation well location, is combined with the GA based optimization simulation model. The performance of the developed methodology is evaluated for one and two dimensional cases with error free and erroneous concentration measurement data. Performance results show the capability and practical applicability of proposed methodology. Main advantage of the proposed methodology is that complete identification of unknown groundwater pollution source is possible with the help of only one observation well when the lag time is also not known.

Groundwater Pollution, Genetic Algorithm, Inverse Problem, Optimization, Pollution source identification

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Md. Ayaz, "Groundwater Pollution Source Identification Using Genetic Algorithm Based Optimization Model," International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.65-72, 2017.