http://ijaers.com/ Open Access international Journal to publish research paper en-us June 2017 The accurate detection of lung lesions from computed tomography (CT) scans is essential for clinical diagnosis. It provides valuable information for treatment of lung cancer. However, the process is exigent to achieve a fully automatic lesion detection. Here, a novel segmentation algorithm is proposed, it’s an improved toboggan algorithm with a three-step framework, which includes automatic seed point selection, multi-constraints lesion extraction and the lesion refinement. Then, the features like local binary pattern (LBP), wavelet, contourlet, grey level co-occurence matrix (GLCM) are applied to each region of interest of the segmented lung lesion image to extract the texture features such as contrast, homogeneity, energy, entropy and statistical extraction like mean, variance, standard deviation, convolution of modulated and normal frequencies. Finally, support vector machine (SVM) and K-nearest neighbour (KNN) classifiers are applied to classify the abnormal region based on the performance of the extracted features and their performance is been compared. The accuracy of 97.8% is been obtained by using SVM classifier when compared to KNN classifier. This approach does not require any human interaction for lesion detection. Thus, the improved toboggan algorithm can achieve precise lung lesion segmentation in CT images. The features extracted also helps to classify the lesion region of lungs efficiently. http://ijaers.com/detail/feature-extraction-and-classification-of-automatically-segmented-lung-lesion-using-improved-toboggan-algorithm/ K. Bavya, Mr. P. Julian http://ijaers.com/uploads/issue_files/1 IJAERS-JUN-2017-1-Feature Extraction and Classification.pdf Breast cancer is a common cancer in women and the second leading cause of cancer deaths worldwide. Photographing the changes in internal breast structure due to formation of masses and microcalcification for detection of Breast Cancer is known as Mammogram, which are low dose x-ray images. These images play a very significant role in early detection of breast cancer. Usually in pattern recognition texture analysis is used for classification based on content of image or in image segmentation based on variation of intensities of gray scale levels or colours. Similarly texture analysis can also be used to identify masses and microcalcification in mammograms. However Grey Level Co-occurrence Matrices (GLCM) technique introduced by Haralick was initially used in study of remote sensing images. Radiologists f i n d i t d i f f i c u l t to identify the mass in a mammogram, since the masses are surrounded by pectoral muscle and blood vessels. In breast cancer screening, radiologists usually miss approximately 10% - 30% of tumors because of the ambiguous margins of tumors resulting from long-time diagnosis. Computer-aided detection system is developed to aid radiologists in detecting ma mammographic masses which indicate the presence of breast cancer. In this paper the input image is pre-processed initially that includes noise removal, pectoral muscle removal, thresholding, contrast enhancement and suspicious mass is detected and the features are extracted based on the mass detected. A feature extraction method based on grey level co- occurrence matrix and optical density features called GLCM -OD features is used to describe local texture characteristics and the discrete photometric distribution of each ROI. Finally, a support vector machine is used to classify abnormal regions by selecting the individual performance of each feature. The results prove that the proposed system achieves an excellent detection performance using SVM classifier. http://ijaers.com/detail/microcalcification-and-macrocalcification-detection-in-mammograms-based-on-glcm-and-odcm-texture-features-using-svm-classifier/ Lincy Golda Careline S, Dr. J. S. Leena Jasmine http://ijaers.com/uploads/issue_files/2 IJAERS-MAY-2017-67-Microcalcification and Macrocalcification Detection in Mammograms.pdf The most important domain is Agriculture in broadly cultivating countries like India. The situation of decision making can be amended by using the current technologies, the. So that the farmer’s can yield in an improved way. The major role in decision making to agricultural domains is Data mining. In this paper acquaints in connection with some of the most important data mining techniques used in agriculture. Mining in agriculture is a innovative groundwork domain. The problems in the agricultural field can be efficiently solved by using data mining techniques since it anticipate before in hand with the help of raw data’s. Previously mentioned, the paper discuses about various data mining techniques such as classification, clustering, association rule and regression. http://ijaers.com/detail/different-types-of-data-mining-techniques-used-in-agriculture-a-survey/ R. S. Kodeeshwari, K. Tamil Ilakkiya http://ijaers.com/uploads/issue_files/3 IJAERS-MAY-2017-60-Different Types of Data Mining Techniques.pdf In this paper two units cold standby system has been discussed with the facility that server inspect the failed unit before repair/replacement of the unit and server may allow to take refreshment whenever needed. The operative unit may fail directly from normal mode and the cold standby unit may be failed owing to remain unused for a longer period of time. There is single server who serves the dual purpose of inspection and repair immediately whenever required. Also, after having refreshment the server may eventually perform the better service efficiently. The time to take refreshment and repair activity follows negative exponential distribution whereas the distributions of unit failure and server failure are taken as arbitrary with different probability density functions. The expressions of various stochastic measures are analyzed in steady state using semi-Markov process and regenerative point technique. The graphs are sketched for arbitrary values of the parameters to delineate the behavior of some important performance measures to check the efficacy of the system model under such situations. http://ijaers.com/detail/cost-benefit-analysis-of-a-redundant-system-with-server-having-refreshment-facility-subject-to-inspection/ M.S. Barak, Dhiraj Yadav, Sudesh K. Barak http://ijaers.com/uploads/issue_files/4 IJAERS-MAY-2017-59-Cost-Benefit Analysis of a Redundant System.pdf Anti-islanding protection is one of the most important requirements for the connection of Distributed Generators in power systems. This paper proposes a Social Spider Optimization (SSO) algorithm to detect unintentional islanding in power systems with distributed generation. The SSO algorithm is employed to differentiate frequency oscillations in synchronous generator those caused by non-islanding events. The SSO algorithm is based on the forging strategy of social spiders, which generated vibrations spread over the spider web to determine the positions of preys or any other disturbances. The vibrations from the spider are used to detect the occurrence of islanding in the synchronous generator. The SSO algorithm has superior performance when tested with IEEE 34 bus distribution system. The taken test system is evaluated for different scenarios and load distribution. The proposed SSO algorithm detects the islanding and prevents the system from undue tripping and outages. Furthermore, this technique may apply to prevent the system from islanding and maintains the future Indian Distributed Generation (DG) system reliability. http://ijaers.com/detail/anti-islanding-protection-of-distributed-generation-based-on-social-spider-optimization-technique/ Dr.R.Vijay, V.Priya http://ijaers.com/uploads/issue_files/5 IJAERS-JUN-2017-14-Anti-Islanding Protection of Distributed.pdf The study was designed to find connection between pre-and post-stroke personality and cognitive functioning in cerebral ischemic stroke survivor,male, 65, right-hander, with higher education, diagnosed as having motor aphasia, partial sensory aphasia, left hemiparesis in upper and lower shoulder, as well as left-sided spatial neglect and moderate depression. Caregiver was requested to compare the one year period before the stroke to the earlier period with respect to the personality and cognitive functioning of stroke sufferer. According to caregiver’s witness, one month before stroke patient, when driving his car, used to disregard the left side of the road and counter cars, however, was not aware of this problem. Caregiver witnessed increase in the aggression and anxiety of the patient 10 months before the ischemic attack. Change in premorbid personality is suggested to predict the after-stroke moderate depression in cerebral ischemic stroke sufferer. Disregard to the left side of the road is suggested to associate with development of left-sided spatial neglect after cerebral ischemic stroke. http://ijaers.com/detail/spatial-orientation-and-personality-traits-before-and-after-cerebral-ischemic-stroke-a-case-report/ Malkhaz Makashvili, Bakur Kotetishvili, Irma Khachidze, Alexandre Kotetishvili,Teona Gubianuri http://ijaers.com/uploads/issue_files/6 IJAERS-JUN-2017-12-Spatial Orientation and Personality Traits.pdf The emergence of the global corporation and the global supply chain has brought about parallel changes in today’s global economy; however, supply chain management has become ever more complex. In recent years, the ever-increasing technical complexity of standard consumer goods, combined with the ever-increasing size and depth of the global market, indicate that the connection between vendors and consumers is usually the link in the supply chain. The stampede to acquire new technologies and scientific innovations are an imperative. Businesses will have to reorganize and continue to modify their business-model to capture potential benefits on emerging technology with the risk of altering existing ones. Some disruptive Technologies include; mobile internet, internet of things, cloud, advance robotics, autonomous and near-autonomous vehicles, energy storage, and renewable energy, and advanced materials. Some of these technologies do in fact have the potential to disrupt the status quo, alter the way people live and work. Within the nature of things, technology will continue to change, but this will require strong structure and retraining. These changes, will update business models that will lead to truly the next big thing with a new mantra “adapt or perish.” http://ijaers.com/detail/the-world-on-your-palm-an-implication-for-the-global-digital-supply-chain-economy/ Charles A. Briggs http://ijaers.com/uploads/issue_files/7 IJAERS-MAY-2017-50-The world on your Palm An Implication for.pdf Information is growing at an alarming rate. As the development of information, organizations need to manage them and make them can be processed are growing as well. So this makes the problem to get the right information at the right place for the right people. And this fact is important for the company to be successful. This is what causes the Business Intelligence (BI) in the preferences of today's technology. BI is a process from raw data to be read. BI solutions help transform raw data into actionable information that can help support business decision making. This can help companies develop new opportunities. By identifying new opportunities and implement effective strategies, it will result in a competitive market advantage and stable in the long term. In this study, analysis and visualization of large amounts of data from a travel agency in Jakarta to help make the right business decisions using BI tools. http://ijaers.com/detail/business-intelligence-dashboard-implementation-on-a-travel-agency-in-jakarta/ Euis Nina Saparina Yuliani, Heru Subawanto, Anggi Oktaviani http://ijaers.com/uploads/issue_files/8 IJAERS-FEB-2017-40-Business Intelligence Dashboard Implementation.pdf Cooperative communication is an efficient method for reducing the energy consumption of mobile terminal in wireless cellular network. However, it is hard to implement due to the lack of motivations for the Mobile terminals to cooperate. For this scenario as the benchmark case, where the information of the helping mobile terminals such as the channel and battery conditions is completely known by the source node terminal, the problem is formulated as a relay selection problem. Efficient algorithms based on dichotomous search and alternative optimizations are proposed to solve the problem for the cases of split and non-split data at the source MT, respectively. The cooperative communications scheme with pricing mechanism can decrease both the battery outages and communications for the mobile node, and can also increase the average battery level during the mobile terminals operation. In this paper, we state a Dynamic Multilevel Priority (DMP) packet scheduling scheme. In the proposed system, each node, except those which are at the last level of the virtual hierarchy in the zone based topology of Wireless sensor network , have three levels of priority queues. Real-time packets are placed in the highest-priority queue and can preempt data packets in other queues. Non-real-time packets are placed in other two queues based on a certain threshold of their estimated processing time. Leaf nodes will have two queues for real-time and non-real-time data packets since they do not receive data from other nodes and so this reduce end to- end delay. The performance of the proposed Dynamic multilevel priority packet scheduling scheme through simulations for real-time and non-real-time data packet. Simulation results shows that the DMP packet scheduling scheme outperforms conventional schemes interms of average data waiting time and end-to-end delay. http://ijaers.com/detail/improving-the-energy-efficiency-of-mobile-terminals-using-dynamic-multilevel-priority-packet-scheduling-in-cooperative-communication/ Dr. V. Latha, Mr. S. Mahaboob Basha, A. Sanjana http://ijaers.com/uploads/issue_files/9 IJAERS-JUN-2017-7-Improving the Energy Efficiency of Mobile.pdf Currently there is an active Post-Quantum Cryptography (PQC) solutions search, which attempts to find cryptographic protocols resistant to attacks by means of for instance Shor’s polynomial time algorithm for numerical field problems like integer factorization (IFP) or the discrete logarithm (DLP). The use of non-commutative or non-associative structures are, among others, valid choices for these kinds of protocols. In our case, we focus on a permutation subgroup of high order and belonging to the symmetric group S381. Using adequate one-way functions (OWF), we derived a Diffie-Hellman key exchange and an ElGamal ciphering procedure that only relies on combinatorial operations. Both OWF pose hard search problems which are assumed as not belonging to BQP time-complexity class. Obvious advantages of present protocols are their conceptual simplicity, fast throughput implementations, high cryptanalytic security and no need for arithmetic operations and therefore extended precision libraries. Such features make them suitable for low performance and low power consumption platforms like smart cards, USB-keys and cellphones. http://ijaers.com/detail/post-quantum-cryptography-s-sub-381-sub-cyclic-subgroup-of-high-order/ P. Hecht http://ijaers.com/uploads/issue_files/10 IJAERS-JUN-2017-15-Post-Quantum Cryptography.pdf This paper investigates meteorological drought in one of Afghanistan's most important socio-economic river basins called Kabul River Basin (KRB) using a 38 years monthly precipitation data. Several drought indices such as Standardized Precipitation Index (SPI), Percent of Normal Precipitation Index (PNPI), Deciles Index (DI), and China-Z Index (CZI) were applied for the first time on the basin in order to observe the correlation among the indices in the basin for drought, and to see which method is suitable for drought monitoring in KRB. Due to the concerns that climate is changing and especially the rapid snowmelt that accounts for 80% of the precipitation in Afghanistan, it was essential to carry such a study in order to warn the responsible bodies in the country for a better drought management. Moreover, the rapid population increase and usage of more water for both drinking and agricultural purposes in the basin with a possible decrease in the annual precipitation make it necessary to undertake such a study. The results of the investigation show that KRB area experienced drought conditions continuously from 2000 to 2004 with a peak extreme drought in 2001 which confirm to the reported worst drought in the region. It is noted that log-SPI, gamma-SPI, and Deciles captured the historical extreme and severe drought periods successfully, therefore, these methods are recommended to be applied to this region as drought assessment tools. http://ijaers.com/detail/proposing-a-popular-method-for-meteorological-drought-monitoring-in-the-kabul-river-basin-afghanistan/ Mohammad Musa Alami, Ehsanullah Hayat, Gokmen Tayfur http://ijaers.com/uploads/issue_files/12 IJAERS-JUN-2017-25-Proposing a Popular Method for Meteorological.pdf The target of this paper is to build up an exact model for ideal plan through outline the structure of wing that consolidate the composite (Skins) and isotropic materials (every single other structure) and contrast this and a similar wing made by changing the materials and the orientation of composite ply in skin.The ideal plan for each wing with various materials and different ply orientation can be obtained by comparing the displacement and stress on the wing. The structural design of the wing is finished with the assistance of CATIA V5, every parts modelled independently and collected in the IGS file. By using the IGS file as geometry, the Finite element modeling is completed in ANSYS and the Static analysis was done using ANSYS. In this analysis, the boundary conditions of inertia force of 1Kg and the lift force is used to simulate the wing loading on the wings. From this study, the Optimum design of the wing was found from the comparisons of stress and displacement of each material and ply combination. http://ijaers.com/detail/optimization-of-ply-orientation-of-different-composite-materials-for-aircraft-wing/ M. Rajadurai, P. Vinayagam, G. Mohana Priya, K. Balakrishnan http://ijaers.com/uploads/issue_files/13 IJAERS-JUN-2017-10-Optimization of Ply Orientation of Different.pdf Clustering is one of the most important unsupervised learning tools when no prior knowledge about the data set is available. Clustering algorithms aim to find underlying structure of the data sets taking into account clustering criteria, properties in the data and specific way of data comparison. In the literature many clustering algorithms have been proposed having a common goal which is, given a set of objects, grouping similar objects in the same cluster and dissimilar objects in different clusters. Hierarchical clustering algorithms are of great importance in data analysis providing knowledge about the data structure. Due to the graphical representation of the resultant partitions, through a dendrogram, may give more information than the clustering obtained by non hierarchical clustering algorithms. The use of different clustering methods for the same data set, or the use of the same clustering method but with different initializations (different parameters), can produce different clustering. So several studies have been concerned with validate the resulting clustering analyzing them in terms of stability / variability, and also, there has been an increasing interest on the problem of determining a consensus clustering. This work empirically analyzes the clustering variability delivered by hierarchical algorithms, and some consensus clustering techniques are also investigated. By the variability of hierarchical clustering, we select the most suitable consensus clustering technique existing in literature. Results on a range of synthetic and real data sets reveal significant differences of the variability of hierarchical clustering as well as different performances of the consensus clustering techniques. http://ijaers.com/detail/variability-analysis-of-the-hierarchical-clustering-algoritms-and-its-implication-on-consensus-clustering/ Lucia Sousa http://ijaers.com/uploads/issue_files/14 IJAERS-JUN-2017-28-Variability analysis of the hierarchical clustering.pdf