Miracle-dz/UniFAR-FTUs huggingface dataset:
The Performance Optimization of Hadoop/Hive by Distributed Search and Computation Tasks

--In order to process structured data we use the tool Hadoop. To make querying and analyzing easy it is put on top of big data. Execution speed of queries is enhanced by hadoop MapReduce framework. Many opportunities can arise for distribution search and/ or computation tasks during simultaneous execution of multiple queries. Therefore, we propose to use Multiple Query Optimization (MQO) techniques to enhance the overall performance of Hadoop/Hive, an open source SQL-based distributed data warehouse system based on MapReduce. Our framework, transforms a set of interrelated HiveQL queries into new global queries that can produce the same results in remarkably smaller total execution times. It is experimentally shown that DistributedHive outperforms the conventional Hive by 20-50% reduction, depending on the number of queries and percentage of shared tasks, in the total execution time of correlated TPC-H queries.
A Review Study on Big Data Analysis Using Hadoop

:- The emerging Big Data Science term, showing its broader impact on our society and in our business life cycle, has insightful transformed our society and will continue to attract diverse attentions from technical experts and as well as public in general. It is obvious that we are living in Big Data era, shown by the sheer volume of data from a variety of sources and its rising rate of generation. So far, most of the current mobile systems are mainly targeted to voice communications with low transmission rates. In the near future, however, big data access at high transmission rates will be. This is a review on accessible big-data systems that include a set of tools and technique to load, extract, and improve dissimilar data while leveraging the immensely parallel processing power to perform complex transformations and analysis. “Big-Data” system faces a series of technical challenges.
WIMAX BASED COMMUNICATION SYSTEM FOR TRANSPORTATION NETWORK

: The geographical coverage area of communication is increased for the efficiency of the ITS (Intelligent Transportation System) customers. The maximum extent of coverage area provides the beneficiary of satisfying the customers with the desired needs of the customers, as it keeps changing rapidly. Convergence of the noble technologies WIMAX and MIMAX helps to achieve the desired goal. The convergence also provides compatibility with the existing standards of ITS.
WPBS: A Workload Pattern Based Scheduler for Competent Task Assignments in Hadoop

— MapReduce has emerged as a popular paradigm for processing large datasets in parallel over a cluster. Hadoop is an open source implementation of Map Reduce, which is very attractive for parallel processing of a variety of different applications, e.g., web crawling, log processing, video and image analysis, recommendation systems, etc. Multiple users with various types of workloads share MapReduce cluster. When a group of jobs are simultaneously submitted to a MapReduce cluster, they compete for the pooled resources and the overall system performance in terms of job response times, might be degraded. Therefore, key challenge is the ability of proficient scheduling in such a shared MapReduce environment. However, we find that conventional scheduling algorithms supported by Hadoop cannot always assurance good average response times under diverse workloads. In this paper, we address this problem by introducing a novel Hadoop scheduler, which leverages the knowledge of workload patterns to reduce average job response times by dynamically tuning the resource shares among users and the scheduling algorithms for each user.
Image Forensics for Forgery Detection using Contrast Enhancement and 3D Lighting

: Nowadays the digital image plays an important role in human life. Due to large growth in the image processing techniques, with the availability of image modification tools any modification in the images can be done. These modifications cannot be recognized by human eyes. So Identification of the image integrity is very important in today‟s life. Contrast and brightness of digital images can be adjusted by contrast enhancement. Move and paste type of images are Created by malicious person, in which contrast of one source image is enhanced to match the other source image. Here in this topic contrast enhancement technique is used which aimed at detecting image tampering has grown in different applications area such as law enforcement, surveillance. Also with the contrast enhancement, we propose an improved 3D lighting environment estimation method based on a more general surface reflection model. 3D lighting environment is an important clue in an image that can be used for image forgery detection. We intend to employ fully automatic face morphing and alignment algorithms. Also we intend to use face detection method to detect the face existence and 3D lighting environment estimation to check originality of human faces in the image.
Recursive CORDIC-Based Low Power DCT Architecture

- One of the maximum commonly used transform technique is Discrete Cosine Transform (DCT). In the DCT algorithm the inputs are in spatial domain and the outputs are in frequency domain and it is mostly used for image compression. DCT using Coordinate Rotation Digital Computer (CORDIC) algorithm lessen the number of calculation and increases the accuracy. Therefore discrete cosine transform design using CORDIC is used to obtain low power. All calculation in DCT are not equitably essential in producing the frequency domain output. Therefore the calculation energy can be lessen without severely incriminating the image quality. The 2-D DCT achieves more power saving. In a lookahead CORDIC approach, all interior data path become individualistic and the number of repetition can be easily controlled but the implementation complexity of lookahead CORDIC is considerably high because it requires more area. Therefore the recursive CORDIC is proposed in this project. This technique is easy to implement and considered as an appropriate technique. The power requirement for recursive CORDIC is less compared to lookahead CORDIC. The implementation is done using the Modelsim SE9.1i software.
A Survey on Efficient Protocol for Privacy Preserving Association Rule Mining

- We propose a protocol for secure mining of association rules in horizontally distributed databases. The current leading protocol is that of Kantarcioglu and Clifton [18]. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm of Cheung et al. [8], which is an unsecured distributed version of the Apriori algorithm. The main ingredients in our protocol are two novel secure multi-party algorithms — one that computes the union of private subsets that each of the interacting players hold, and another that tests the inclusion of an element held by one player in a subset held by another. Our protocol offers enhanced privacy with respect to the protocol in [18]. In addition, it is simpler and is significantly more efficient in terms of communication rounds, communication cost and computational cost.
Fingerprint Recognition using orientation features

:The paper is to study and implement a fingerprint recognition system based on Minutiae based matching quite frequently used in various fingerprint algorithms and techniques. The approach mainly involves extraction of features from the sample fingerprint images using Orientation Features and Local Direction Pattern and then using Euclidean classifier. SVM Classifier is used for getting better results in terms of FAR and GAR. Our implementation mainly incorporates image enhancement, image segmentation, feature (minutiae) extraction and minutiae matching. It finally generates a percentage score in the term of FAR & GAR which tells the efficiency of the overall system.
Investigating the Factors Limiting the Use of Visual Aids in English Language

ARTICLE HISTORY Received: 20.05. 2017 Revised 27.05. 2017 Accepted 27.06. 2017 ABSTRACT This study focused on English language teaching in English Medium Primary Schools in Meru District. The study employed qualitative and quantitative techniques for data collections; observation and interview were used school environment (classroom), The results findings point out the average mean score of 1.8286 meaning that the respondents disagreed that classroom environments does not give full support in using vis equipped so well due to the fact that they are of poor physical and technical conditions to support the use of modern technology such as computer, video, Television etc. For item on School leadership supports teachers by suppl language teaching Aids, the respondents disagreed with mean score of 1.7449 that school leadership does not supplying them teaching aids to facilitate learning, also they disagreed with mean score of 1.9429 that the government education polic does not support the use of visuals aids in English language teaching. For item on my school economic position can support the purchase and supply of visuals for the school the respondents disagreed with their mean score of 1.8529 that their school eco on supply of visuals in business centers, the results from the respondents point out the average mean score of 2.3143 meaning that the respondents disagreed that business cent presentation of the above respondents on teacher training and seminars there is lack of good seminars to language teachers regarding the modern technology visuals and how should be incor language teachers lacks quality in their teaching which subsequently leads to poor learning outcome. The study recommends that: The government and other responsible authorities in schools should spend a lot of language teaching. Teachers especially in primary schools should be encouraged to use as many teaching learning aids to stimulate and make the event conductive to learning and the education system should promote on training and semi given to ESL teachers on modern technology visuals usage in teaching.
Short and Secure CLS Pattern Using Simple Crypto Analysis Hash Technique

In the irregular oracle miniature under the hardness presumptions of K-CAA and Inv-CDHP we introduce a CLS (Certificateless Signature) which proved to be a much secured in traditional public key cryptosystem (PKC). We overcome the incompetent MaptoPoint hash technique by replacing a simple cryptoanalysis hash technique by indulging most common properties of CLS conspires. The extent of signatures generated in this paper is nearly 160 bits, which strength our assumption towards less calculation cost and essentially more productive than every single known CLS plans. In this way it can be utilized generally and particularly in low-data transmission correspondence situations.
Security issues in SaaS of cloud computing

: Cloud computing is becoming increasingly popular in distributed computing environment. Locking at the impact it as on numerous business applications as well as this makes IT resources available,known as cloud computing ,opens opportunities to small ,medium-sized ,and large companies. Data storage and processing using cloud environments is becoming a trend worldwide. Software as a Service (SaaS) one of major models of cloud which may be offered in a public, private or hybrid network. If we look at the impact SaaS has on numerous business applications as well as in our day to day life, we can easily say that this established technology is here to stay. Cloud computing can be seen as Internet-based computing. By using a cloud computing specimen can have positive as well as negative effects on the security of service consumer’s data. Many of the important features that make cloud computing very attractive, have not just challenged the existing security system, but have also exposed new security risks. In this paper we are going to showcase some major security issues of current cloud computing environments.
Implementation of ANN Classifier using MATLAB for Skin Cancer Detection

— Skin cancer is the deadliest form of cancers in humans. Skin cancer is commonly known as Melanoma. Melanoma is named after the cell from which it presumably arises, the melanocyte. Skin Cancers are of two types-Benign and Malignant Melanoma. Melanoma can be cured completely if it is detected early. Both benign and malignant melanoma resembles similar in appearance at the initial stages. So it is difficult to differentiate both. This is a main problem with the early skin cancer detection. Only an expert dermatologist can classify which one is benign and which one is malignant. The Artificial Neural Network based Classification methodology uses Image processing techniques and Artificial Intelligence for early diagnosis. Main advantage of this computer based classification is that patient does not need to go to hospitals and undergo various painful diagnosing techniques like Biopsy. In this Computer Aided Classification, dermoscopy image of skin cancer is taken and it is subjected to various pre-processing and image enhancement. The cancer affected region is separated from the healthy skin using Segmentation. In order to reduce the complexity of classification, some unique features of malignant and benign melanoma are extracted. 2DWavelet transform is the Feature Extraction Method used. These features are given as the input to the Artificial Neural Network Classifier. It classifies the given data set into cancerous or non-cancerous.
Performance Effects of Market Orientation and the Mediating Role of Innovation of Service Process in Insurance Industry: Case Study of Dana Insurance Company

Achievement of large organizations in the competitive environment first requires sustained and long-term competitive advantage. Such benefit acquisition and utilization depends on market oriented attitude and innovation of service process. This approach makes efforts in developing and dissemination of organizational performance and provides the opportunity for valuable service delivering to customers and benefiting their satisfaction. In this regard, the present research studied the effect of mediating role of innovation of service process in the relation between market orientation and organizational performance. This study is analyzed based on individual and all Dana insurance company agents including about 2000 individuals, throughout the country, are regarded as statistical population. Research statistical participants consisted of 325 agents who were selected through clustering sampling method. Data collected through using a questionnaire (by content validity; factor analysis and validity by measuring Cronbach alpha coefficient). Data analyzed and research hypotheses were tested using structural equations method. Results showed that market orientation has a positive, significant effect on innovation of service process and organizational performance; moreover, mediating role of innovation of service process was maintained between market orientation and organizational performance variables. 1 Corresponding author’s email: toolo.dana@gmail.com International Journal of Management, Accounting and Economics Vol. 3, No. 1, January, 2016 ISSN 2383-2126 (Online) © Authors, All Rights Reserved www.ijmae. com 29
KNOWLEDGE OF ENGINEERING STUDENTS ON ENVIRONMENTAL ISSUES

The knowledge of environmental issues is one of parameters that affect the behavior of the student. This study try to analyze the issues related to the knowledge of environmental issues of the graduate students in Engineering Faculty Universitas Negeri Makassar. The sample of this research is 150 first year students in graduate program of engineering faculty. There are three variables in this research are factual, procedural and conceptual of knowledge, while environmental issues are global and local issues. Data were collected by true false questionnaire and analyzed by using descriptive analysis. The results showed that the scores of the students knowledge about local issues is higher than the global issues. The highest value is environment factual, while the lowest value on the procedural aspect of environmental knowledge. It is also indicated that the information of resources are still limited. Therefore, global issues still has minimal information. In addition, this article suggest that curriculum in Engineering Faculty should integrate with knowledge about local and global issues in each course due to improvement of environmental knowledge.
Using Categorical Attributes for Clustering

The traditional clustering algorithms focused on clustering numeric data by exploiting the inherent geometric properties of the dataset for calculating distance functions between the points to be clustered. The distance based approach did not fit into clustering real life data containing categorical values. The focus of research then shifted to clustering such data and various categorical clustering algorithms are proposed till date. The clustering of categorical data turns complex because of the absence of a natural order on the individual domains, high dimensionality of data and the existence of subspace clusters in the categorical datasets. This survey focuses on the shortcomings of categorical data and the recent developments in the direction of using data with categorical attributes for clustering
Design of Robust Power System Stabilizer for Interconnected System

Electrical Power System is one of the most complex real time operating systems. It is probably one of the best examples of a large interconnected non-linear system of varying nature. This system changes it's state time to time with change in load, transmission and generation conditions. Such changes in the system causes small signal oscillations, the frequency range of such oscillations is about 0.2 to 3 Hz, if they are persist for long duration they may limiting the power transfer capability of the system. For the stable and secure operation of the system adequate damping for small signal oscillations is required. A auxiliary controller can provide adequate damping for the system called power system stabilizer (PSS). Fixed parameter controllers are most commonly used controller for this applications. This is a conventional method of designing power system stabilizer. It gives the better performance for single operating condition only. In this paper a technique for designing a robust power system stabilizer using H∞ control theory has been discussed. These stabilizers gives the comparable performance for a wide range of operating condition. In case of interconnected system conventional method of designing power system stabilizer is extremely complex, and there is need of system information external to the plant. Modified Heffron-Phillip's model provide solution for this problem, it allow designing power system stabilizers without using system information external to the plant. In this paper modified Heffron-phillip's model has used for designing stabilizer for multi-machine system. PSS at each machine can be synthesized using information available at local buses only.
Removal of Fe(II) and Cu(II) from Aqueous Solutions using Activated Carbon Derived from Wooden Parts of Mangifera Indica by Chemical Activation with ZnCl2

The purpose of this study was to investigate the use of activated carbon derived from wooden Parts of Mangifera Indica by chemical activation with ZnCl2, named (MI-ZnCl2), in the removal of Fe(II) and Cu(II) ions from aqueous solutions. Batch experiments were conducted to determine the effect of varying adsorption parameters on their removal. The adsorption of Fe(II) ions was found to be maximum (82%±2.21), at pH 6 using adsorbent mass of 1.00 g. While the optimum adsorption of Cu(II) ions was found to be (61%±1.74), at pH 5 using adsorbent mass of 1.80 g. The Langmuir level of conformity for Cu(II) is high compared to Fe(II) ions, according to the correlation coefficients(R2) of 0.9942 and 0.9753, respectively. The adsorption capacity, Qo, (mg g-1) of Cu(II) is higher than that of Fe(II) ions, they were found to be 7.08 and 3.59 respectively. The affinity of the two metals for the adsorbent surface in terms of b is higher for Cu(II). The values of b (L/mg) were high, which implies high surface energy in the process and consequently high bonding between metal ions and the (MI-ZnCl2). Freundlich level of conformity for Fe(II) is to a high extent compared to the Langmuir adsorption isotherms as indicated by higher correlation coefficient value of 0.9929. On the other hand, the level of conformity for Cu(II) is low compared to the Langmuir adsorption isotherms as indicated by the lower correlation coefficient value of 0.9729 . The values of n (2.56 and 2.43) for Fe(II) and Cu(II) ions respectively, confirm that the (MI-ZnCl2) have a heterogeneous surface since the values satisfy the heterogeneity condition where n, must be in the range 1 < n< 10. (MI-ZnCl2) can be used as a cost effective adsorbent for the removal of Fe(II) and Cu(II) ions from aqueous solutions in the treatment of industrial effluent. Keywords— Mangifera Indica (MIZnCl2), Activated carbons; Adsorption; Heavy metals; Langmuir and Freundlich isotherms.
Mobile Cloud Computing: Overview and challenges

Today is the era of Cloud Computing Technology in IT Industries. Cloud Computing is Internet-based computing, whereby shared information, resources, and software, are provided to terminals and portable devices on-demand. The rapid development of mobile technology and wireless networking and drives a strong demand for Mobile Cloud Computing (MCC). In MCC environment Cloud Computing, Mobile Computing and Networking are combined to offer cloud based services to mobile users where the data are stored and applications are processed in a centralized computing applications located in the cloud. In this paper first, we present the overview of MCC in terms of architecture, deployment models, service models and applications of MCC. Then we outlined issues and challenges related to MCC.
Review on Classification Mechanism for Outlier‘S with Imperfect Data Labels for Streaming Data Environments

: Outlier detection is the set of data points that are considerably different than the remainder of the data. Consequently, for high dimensional data, the notion of finding meaningful outliers becomes substantially more complex and non-obvious. Earlier solutions typically build a model using the normal data and identify outliers that do not fit the represented model very well. However, in addition to normal data, there also exist limited negative examples or outliers in many applications, and data may be corrupted such that the outlier detection data is imperfectly labeled. These make outlier detection far more difficult than the traditional ones. To overcome these difficulties proposed system focuses on outlier detection with limited labeled outliers and data with imperfect labels. Also capture local data information by generating the likelihood values of each input example towards the positive and negative classes respectively. Such information is then incorporated into the generalized support vector data description technique to enhance a global classifier for outlier detection. Here presented outlier detection approach to address data with imperfect labels and incorporate limited abnormal examples into learning. To deal with data imperfect labels, here introducing likelihood values for each input data which denote the degree of membership of the normal and abnormal classes respectively. Proposed approach works for online streaming data environment and different classification techniques such as K-means, Naives Bayes. Here considering combining approach to compute the likelihood values. By integrating local and global outlier detection, proposed method explicitly handles data with imperfect labels and enhances the performance of outlier detection.