Miracle-dz/UniFAR-FTUs huggingface dataset:
A Competent and Protected Etiquette for Ensuring Secure Data Storage Security in Cloud Computing

: Here in this paper we are provided security in the cloud systems and how we can provide the security to the user data. When user was uploaded his files or his data it will encrypt and it will be translated in to an encryption format and that data will be share and store in the cloud server after the data has been stored in cloud server the user can know the status of uploaded files in cloud servers and for that he can have to store in cloud server only whenever the data has been modified in cloud server that data will be updated to the user for the purpose of he to know that what was happened to his data then the user can be aware of data in cloud sometimes if any attacks has happen simply the user can know the when the data was modified and where the changes was happen also he can know that for the protection of the data and for further modification and next usage of data through this paper user can be free of its process he simply store the data and he can feel that was a secure manner process and that data will in the protection. There is no lose of data in this types of process that’s why we are proposed this way in this paper and improved the security to the user data in cloud servers.
Mathematical Modeling and Signal Processing Technique In Automatic Number Plate Recognition

Automatic Number Plate Recognition is a special form of Optical Character Recognition(OCR) ,use to extract number plate/standard plate from the vehicle image or sequence of image(in case of video). Main aim of this system is to collect information of a car on the basis of License Plate (LP) only. License plate detection and character segmentation are the critical phases of this system, detection involves extraction of number plate from car image, this phase provide major contribution in the success of ANPR, vehicle speed, plate size, normal text (other than number plate) or stickers, environmental condition and another noise effects like uneven image, dirty plate, shadow etc are the major problem of this phase. Segmentation involves separating character from acquired number plate algorithm used for this phase should overcome problem of LP detection for the better performance of LP character recognition phase. Paper presents the comprehensive review of license plate recognition techniques and comparison of various paper on the basis of Global Image information ,Textual Feature and Artificial Intelligence and review also contain techniques used for license plate detection, segmentation and recognition and country/region information for which respective algorithm were designed, database used to test the algorithm with image resolution, processing time and accuracy.
Prediction Analysis Technique using Hybrid Clustering and SVM Classification

: Data mining is a technique to accumulate, explore and analyze a large amount of complex data. Prediction Analysis is a technique which is applied to predict future outcomes and trends according to the given input datasets. In the recent time, various techniques have been applied for the prediction analysis. In this paper, BFS, CFS, k-mean, and SVM classifier based prediction analysis technique is improved to increase accuracy and execution time. In the prediction analysis based technique, Breadth first search (BFS) & Correlation based feature selection (CFS) is applied for the feature selection, the k-mean clustering algorithm is used to categorize the data and SVM classifier is applied to classify the data. The Boltzmann algorithm has been applied to the k-mean clustering algorithm to increase the accuracy of prediction analysis system. The proposed algorithm is implemented in MATLAB and it has been tested that the accuracy of clustering is increased, execution time is reduced for prediction analysis.
CLINICAL SOLID WASTE MANAGEMENT PRACTICES AND ITS IMPACT ON HUMAN HEALTH AND ENVIRONMENT

The management of clinical solid waste (CSW) continues to be a major challenge, particularly, in most healthcare facilities of the developing world. Inappropriate disposal methods and improper handling exercised during handling and disposal of CSW is increasing significant health hazards and environmental pollution due to the infectious nature of the waste. In most of the cases, the main reasons of the mismanagement of CSW are the lack of appropriate legislation, specialized clinical staffs, awareness and effective control. Proper handling, treatment and disposal of clinical waste play a vital role in infection control. Most of the developing countries are looking for cost effective disposal methods of clinical wastes due to financial difficulties. Recycle-reuse program of CSW materials can be continued after sterilization by using Supercritical fluid carbon dioxide (SF-CO2) sterilization technology at the point of initial collection which inactivates the infectious micro organisms in CSW. This technology reduces exposure to infectious waste, decrease labor, lower costs and yield better compliance with regulatory. Thus healthcare facilities can save money and provide safe environment for patients, health care and clinical staffs. This review mainly emphasizes on the various technologies and techniques like Incineration, Autoclaving, Microwaves, Supercritical fluid carbon dioxide sterilization which are used to treat clinical wastes.
Solving the Hidden Terminal problems Using Directional- Antenna Based MAC Protocol for Wireless Adhoc Networks

In wireless networks, hidden terminal problem is common and leads to collision which makes it difficult to provide the required quality of multimedia services or support priority based services. To overcome these problems a directional antennas have been extensively used in designing MAC protocols for wireless network. Directional antennas provide many advantages over the classical antennas. In this paper, we show that directional antennas can be used effectively to solve a common hidden and exposed terminal problem by using an energy efficient MAC protocol for wireless sensor networks. This directional Antenna could be rotated in case of base station node to avoid directional hidden terminal problem. KeywordMAC protocol, Energy efficiency, Directional-Antenna,Transmission ranges,Mac frames.
File Clustering using Forensic Analysis System

-In this paper computer forensic analysis investigation, thousands of files are generally surveyed. In this much of the data in those files consists of formless manuscript, whose investigation by computer examiners is very tough to accomplish. Clustering is the unverified organization of designs that is data items, remarks, or feature vectors into groups (clusters). To find a noble clarification for this automated method of analysis are of great interest. In particular, algorithms such as K-means, K-medics, Single Link, Complete Link and Average Link can simplify the detection of new and valuable information from the documents under investigation. In This paper we are going to present a tactic that applies text clustering algorithms to forensic examination of computers seized in police investigations using multithreading technique for data clustering. Our experiments show that the Average Link and Complete Link algorithms provide the best results for our application domain. If suit-ably initialized, partition algorithms (K-means and K-medoids) can also yield to very good results. Finally, we also present and discuss several practical results that can be useful for researchers and practitioners of forensic computing.
Channel Prediction in Wireless Microcell and Picocell Systems Using Echo State Network

: Reservoir computing (RC) presents efficient approach for creating recurrent neural networks (RNN). RC encompasses echo state network (ESN) which has received increased attention owing to its effectiveness and relative simplicity due to fact that only connections from a reservoir to an output layer are trainable. This paper investigates the ESN-based prediction scheme for single-input single-output (SISO) systems in microcellular and picocellular environments using normalized mean squared error (NMSE) as a performance indicator. Presented simulation results show that gap between curves representing predicted and measured channel states is very small and no more than several neurons in input layer and several hundred neurons in reservoir should be used
Discovery of Plant Disease Based on Content Recovery from Images

This paper presents a technique to discover plant disease. We are concentrating on agriculture plants only. The method which we are using is relying on edge finding, color as well as histogram matching. This is nothing but content based image retrieval. In India, Farmers are bearing from an issues growing from several types of plant illnesses. Sometimes plant’s experts are also not able to identify the disease that results in need of recognition of accurate type of disease and consequently to crop spoil if not taken care of at appropriate time. Hence, we should take the advantage of available technology in automatic detection and categorization of agricultural plants has become crucial. This paper used CANNY’s edge detection procedure and compare the accuracy of disease plant with Sobel Edge Detection procedure and to obtain histogram for both healthy and unhealthy plant leaves. After histogram design, we are comparing all the stored images to recognize whether plant leaf has been polluted or not. In addition, this paper also shows how we can fetch images from digital camera attached to the computer on which our application software has been installed. Also calculate RGB histogram of each image for increasing the accuracy of image matching. Furthermore, Most of the existing software are not supporting database on larger scale, however our aim is to provide support to huge databases, so as to increase scope of the software. To sum up, this application software will definitely help Indian farmers to tackle with the problem of plant diseases which in turn assist them to increase the productivity of agricultural field.
Koch Fractal Microstrip patch Antenna for Triband Wireless Applications

A Koch fractal microstrip Rectangular patch antenna fortriband wireless Applicationsis presented. Significant reduction of antenna size can be realized when the Koch fractal microstrip antenna used instead of conventional rectangular microstrip patch antenna. In this paper side of the rectangular patch replace by Koch curve and Rotating koch fractal rectangular slot is added at the centre of the rectangular patch for the good circular polarazation . The Axial ratio is 3 dB down for triple band also return loss values below -10 dB for frequency 1.52GHz,2.04GHz2. 43GHz respectively. The antenna printed on a dielectric substrate FR4, dimension of patch is (45mmx58mm), relative permittivity εr =4.4 and h=1.6mm. This antenna simulated using HFSS software. Keywords-Koch fractal antenna, microstrip antenna, Bandwidth, radiation patterns, VSWR, returns loss.
Evaluation of Dexamethasone for of Postsurgical Sequelae of Molar Removal Reduction Third

Sixty patients with bilaterally symmetrical impacted third molars participated in this double-blind, within-subject study to quantify the effects of 4 mg of dexamethasone on reducing postsurgical sequelae. Each patient’s surgery was staged by mouth side and completed in two appointments 5 to 6 weeks apart. A preoperative dose of dexamethasone given intravenously was randomized to mouth side and surgical appointment; sterile water served as a control. Major areas assessed in this study were facial swelling, pain, and trismus. No difference in swelling and daily pain was noted. However, trismus and global pain were significantly affected by the steroid. Patients had a daily postsurgical increase in incisal opening of 4 to 6 mm over the control side during the examination period. Patients evaluated pain by choosing the least painful side. By a greater than 4:l margin, patients chose the steroid side as the least painful side. No increase in the rate or type of complications was detected between control and steroid sides. Reduction of postsurgical discomfort from exodontia is an area of concern to all practicing oral and maxillofacial surgeons, as well as their patients. Many modalities are used to abate sequelae in third molar removal. In recent years, long-acting local anesthetics, glucocorticosteroids, and nonsteroidal anti-inflammatory drugs have been evaluated for this purpose. ‘-’ Steroid use in exodontia deserves further scrutiny. For more than 30 years dentists have evaluated steroids for reduction of pain, trismus, and swelling after extractions.8-‘4 Even though these studies are numerous and generally support the use of steroids in exodontia, many suffer from methodologic inconsistencies that
Frequency Reconfigurable Log Periodic Microstrip Dipole Antenna Array for Wideband Applications

The concept of reconfigurable antenna is widely used as an additional feature of reconfigurable ability for future wireless communication systems especially for cognitive radio applications, radar system and multi-frequency communications. There are various configurations of reconfigurable antenna such as monopole, dipole and log-periodic wideband antenna. This paper describes the design and simulation of frequency reconfigurable log periodic microstrip dipole array (FRLPMDA) using dipole patch elements with an useful frequency range for C band (4-8 GHz), X band ( 8-12 GHz ) and Ku band (12-18 GHz ). The integration of reconfigurable antennas with radio frequency (RF) switches are needed to perform the switchable ability [3-6]. In this paper, a frequency reconfigurable LPMDA has been designed to perform a wideband frequency operations by connecting fifteen dipole antennas using coaxial feed line technique. Then, the diversity in frequency is achieved by switching ON and OFF of the PIN diodes connected at every transmission line. It is compact in size and useful to support on board Radar and many wireless applications where they can reduce the size of front circuitry in communication systems.
Content Based Audio Retrieval using Chord

—Music information retrieval (MIR) is a science of retrieving information from music signal. Extracting high-level features of music such as melody, harmony or rhythm from the raw music signal is a critical and challenging process in Music Information Retrieval (MIR) systems. Using one of such feature will be helpful in searching and retrieving relevant musical audio track effectively and efficiently from large collection of musical audio tracks. Content-based concept is based on the content of a given audio document and extracting the necessary information from it. The proposed content based audio retrieval system retrieves relevant songs from a large dataset of music audio tracks based on melody similarity. Relevant song retrieval is done by recognizing and extracting chord progressions (CPs). Chord progressions means transitions between adjacent chords which contains music information related to tonality and harmony which is helpful in effectively distinguishing whether music audio tracks are similar to each other or not. Various combination of features (4, 6 and 9) are used which consist of features like audio spectral centroid, spectral projection, audio spectrum flatness, audio spectrum spread, spectral crest factor, spectral decrease, spectral flux, spectral kurtosis, spectral Mfcc. Then supervised statistical machine learning model such as Support Vector Machine (SVM) and Hidden Markov Model (HMM) is used for recognizing and extracting CPs from music signals
Effects of an Undergraduate Nursing Program on the Self-Esteem, Submissive Behaviors, and Mental Problems: A Descriptive Cohort Study

This study aimed to evaluate the effects of a four-year undergraduate nursing program on the students’ self-esteem, submissive behaviors and mental problems. The study was designed as a descriptive cohort study. Participants were 80 first-year students who enrolled the nursing program of a university located in the center of Ankara, the capital of Turkey. Data were obtained using the Students Information Form, Coopersmith Self-Esteem Inventory, Submissive Acts Scale, and General Health Questionnaire-12. The first measurements were applied at the beginning of the first year, during the fall 2010 semester, and the second were applied at the end of the fourth year, during the spring 2014 semester. While students’ submissive behaviors decreased significantly during the nursing program, the self-esteem and risk of mental problem ratios did not show significant changes. Negative correlations were observed between self-esteem and mental problem risk, and submissive behaviors; there was a positive correlation between submissive behaviors and mental problem risk. There is a need to review the nursing curriculum and evaluate what affects the students’ self-esteem and mental health, and also introduce strategies to reduce the risk of mental problems and to increase self-esteem.
Antioxidant Activity of a (Leene and Buitendijk ,1949)

Astaxanthin extracted from Red Crab edwardsii was assayed for antioxidant activity viz., total antioxidant, reducing power, hydrogen peroxide radical scavenging assay, and DPPH free radicals scavenging activity. Final concentration of astaxanthin was quantified to be 49.05 μg/g using the standard astaxanthin. The antioxidant activity was found to be 60%, hydrogen peroxide scavenging activity showed 89% inhibition, whereas 1,1 diphenyl-2-picrylhydrazl (DPPH) activity showed 86% of scavenging activity. Present investigation proves that the astaxanthin from C. edwardsii promising antioxidant source, which can be used in food, pharmacological and aquaculture sectors.
Design & Development of a Suitable Model to Validate New Estimation Approaches for Effective Performance

: As COCOMO is a non-proprietary model, its details are available in the public domain, encouraging researchers and practitioners in the software engineering community to independently evaluate the model. There have been many extensions independently reported where machine learning techniques are used to generate effort models from the original COCOMO model. In our research work, we proposed a calibration method by transforming the model equation into a linear form and estimating the model parameters using standard linear regression techniques. This calibration method has been adopted by the COCOMO development team in their calibration work. COCOMO has also been a model used to validate new estimation approaches such as fuzzy logic and neural networks. The COCOMO development team continues to calibrate and extend the model using different calibration approaches on more augmented data sets and our research work is mainly based upon these approaches wherein we have evolved newer and better approaches over the existing approaches and gave a realistic outlook to the very purpose of achieving the best performance.
Review on Text Clustering Based on Frequent Itemset

Recently the vast amount of textual information available in electronic form is growing at staggering rate. This increasing number of textual data has led to the task of mining useful or interesting frequent itemsets (words/terms) from very large text databases and still it seems to be quite challenging. The use of such frequent itemsets for text clustering has received a great deal of attention in research community since the mined frequent itemsets reduce the dimensionality of the documents drastically. In the proposed research, we have considered an efficient approach for text clustering based on the frequent itemsets. A renowned method, called Apriori algorithm is used for mining the frequent itemsets. The mined frequent itemsets are then used for obtaining the partition, where the documents are initially clustered without overlapping. Furthermore, the resultant clusters are effectively obtained by grouping the documents within the partition by means of derived keywords. Finally, for experimentation, any of the dataset can be used and thus the obtained outputs can ensure that the performance of the proposed approach has been improved effectively.
Survey on Feature Engineering of Author-Paper Pair Matching in Bibliography Data

— Everyday thousands of research work is published in variety of journals, conference proceedings by academic and industrial researcher across hundreds of various disciplines. The tools and techniques which provide efficient search capability and provide the information for measures about publication like who has been published, which publication and when modern research is challenge. KDDCUP’13 addressed this challenge where given paper has been written by particular author (i.e. author-paper identification) for biographic dataset provided by Microsoft Academic Search Database. Many researchers has published their solutions for this problem based on incorporating selected proper features with different model like, Random Forest, GBDT (Gradient Boosting Decision Tree), FICO scorecard model, RGF. This paper focused on complete review for the solution published for KDDCUP’13 challenges.
EXTRACTING RELATIVE FACE NAMING SIMILARITY ON LOW SUPERIORITY IMAGE USING MIL

: Labelling faces in the images is tremendously challenging due to huge variation in image appearance of each character and the weakness, ambiguity of available annotation. Some of the pre-processing steps to be carried out before performing face naming. Even though successfully performing pre-processing step such as face detector and entity name detector, face naming is still a challenging task. So, the supervised approach requires sufficient labelled training data in order to achieve high accuracy. The supervised learning method such as Multiple Instance Learning algorithm would solve the ambiguity of the labelling process by making weaker assumptions about the labelling information. Based on Multiple Instance Learning algorithm, the two discriminative probabilistic learning method, “Quasi-Positive Bags” and “Extended Diverse Density” is used to develop an automatic training scheme. This algorithm will be applicable for large image databases and images does not have complete data labels.
Influence of Environmental and Governance Factors on Sustainability of Microfinance Institutions in Ghana

This study examines the environmental and governance factors and how they affect sustainability of Microfinance institutions (MFIs) in Ghana. Microfinance institutions like any other system are affected by peculiar environmental and governance factors which determine to a large extent how it survives. The study therefore measures seven variables by testing seven hypotheses from a survey data of 114 MFIs in Ghana. The study revealed that even though there was a positive and significant relationship between sustainability and improved regulatory framework, loan recovery, quality of staff and the MFIs ability to create jobs for their clients, existence of Board of Directors, and increased competition, do not impact on sustainability. Recommendations on how to enhance the environmental and governance factors to ensure sustainability of MFIs have been made. Key words : sustainability, environment, governance, microfinance
Design of Compact High Frequency Micro-Strip Antenna

In this paper a method of designing high frequency micro-strip antenna is presented. The proposed method is very simple than transmission line model or resonant cavity model of the micro-strip antenna design. In this paper the concepts of linear dipole antenna is implemented to design the high frequency micro-strip antenna. The results of proposed antenna are compared with different substrate thickness and transmission line method. Proposed antenna is designed for 10 GHz frequency and simulated using HFSS. The substrate used for the antenna is FR4 Epoxy having dielectric constant 4.4 and dielectric loss tangent 0.02. The proposed antenna is compact than the conventional design.