Miracle-dz/UniFAR-FTUs huggingface dataset:
TRIANGLE AREA MAP POWERED MULTIVARIATE CORRELATION ANALYSIS FOR ANOMALY BASED DENIAL-OF-SERVICE ATTACK DETECTION

: The world of information has become immensely open with the widespread growth in IT industry. This growth, while it has opened the doors for infinite developments, has also paved the path for welcoming a variety of threats that attack the data and the systems worldwide. Among many such attacks one of the most menacing and aggressive attacks is the Denial of Service attack. In this paper, a proposal is made for DoS attack detection using Anomaly based technique. We also propose the use of Multivariate Correlation Analysis (MCA) that extracts the geometrical correlations between multiple network traffic features to determine the anomalous patterns that can signal a potential attack. Furthermore, to power up the MCA process we make use of Triangle Area Map technique. Evaluation of the overall process is performed using the KDD Cup 99 Data set. The proposed MCA system is examined for both non-normalized and normalized data sets. With our proposed system the detection rates and the false positive rates are much better than the other state-of-the-art detection systems.
A 10-bit 150 MS / s Pipelined ADC with 2 . 5 bit Gain Stage for High Frequency Applications

This paper proposes a 10-bit pipelined Analog to Digital Converter (ADC) which incorporates various techniques for lesser power and higher performance. The proposed method reduces the computational burden while comparing to the modified Monte-Carlo (MC) method. Pipelined ADC has N number of stages, it has higher resolution and higher frequency of conversion while comparing to other ADCs. The proposed ADC employs five 2.5bit gain stages; instead of 1.5bit gain stages for high accuracy. This method is implemented in the Tanner Software with the Generic 250nm library at a maximum power supply of 5V. The maximum frequency attained is 150MHz; and the ADC exhibits a SNR of 61.96dB. It also attains a 10bits as effective number of bits at the maximum sampling rate.
Numerical study of the influence of ultra-thin veneer materials and its thickness on their biomechanical behavior

This study investigated the influence of ultra-thin veneer materials and its thickness on their biomechanical behavior using the 3D finite element method to find out which of all these models have a better performance. The distribution of stresses in the models was studied when composite resin and feldspathic porcelain were used in ultra-thin veneers with thickness of 0.2 mm and 0.3 mm under static loads. The results showed that the use of composite resin in the preparation of veneer of 0.2 mm in thickness reduces the maximum stresses by 65.24% at least compared to feldspathic porcelain, and it reduces the maximum stresses by 56.28% at least compared to feldspathic porcelain in veneer with thickness of 0.3 mm. The results showed also that the use of composite resin ultra-thin veneer with thickness of 0.2 mm reduces the maximum stresses by 49.48% at least compared to veneer with thickness of 0.3 mm, and the using of feldspathic porcelain ultra-thin veneer with thickness of 0.2 mm reduces the maximum stresses by 36.46% at least compared to veneer with thickness of 0.3 mm. Therefore, it is recommended to use composite resin ultra-thin veneer with thickness of 0.2 mm as it reduces induced stresses, which improves the stability and durability of veneers and prolong its lifespan.
A Survey on: Improved Reliability of Distributed Deduplication System using Variable Size Hashing

: Now a day’s cloud technology are being continuously used in IT field as well as in other to keep the data, cloud re-copying is also such service which has to be focused on. As the cloud service has improved huge focus in last few years. Cloud storage massive management has become important. This document surveying various works previously done in the area of cloud services and therefore, re-copying of data over cloud storages has still scope of improvement. Inspestion on the papers or researches emphasizes various deduplication idea and the ways they are differ from each other for efficient deduplication. Thus as there are many ways of deduplication in clouds, an efficient technique is to be search out having less drawbacks and more outcome.
Analysis of Cancer Gene Expression Profiling in DNA Microarray Data using Clustering Technique

— DNA microarray technology has been extremely used in the field of bioinformatics for exploring genomic organization. It enables to analyze expression of many genes in a single reaction. The techniques currently employed to do analysis of microarray expression data is clustering and classification. In this paper, the cancer gene expression is analyzed using hierarchical clustering that identifies a group of genes sharing similar expression profiles and dendrograms are employed that provides an efficient means of prediction over the expression.
GATEWAY RELOCATION BY BANDWIDTH BASED ADMISSION CONTROL SCHEME IN WiMAX

: To support multimedia services with different Quality of Services (QoS) and bandwidth requirements is current aim in the wireless networks. To enhance network performance is important in effective management of limited resources. Access Service Network Gateway (ASN GW) relocation is the process of changing the traffic‟s Anchor Point (AP) from one GW to another which is independent of Mobile Station‟s (MS‟s) Link Layer (LL) handover. The existing standardsdo not specify when the ASN GW relocation has to be performed, buthave details about the ASN relocation procedures. The proposed system combines gateway relocation and Admission Control to determine when to perform ASN GW relocation, as relocation is closely related to Admission Control. This novel Bandwidth based Admission Control (BAC) Scheme considers the size of requests from each MS rather than taking the number of MSs as a whole. Hence the mobility management, which refers the IEEE 802.16e, scheme minimizes the packet loss, new call blocking probability, maximizes the throughput, handover delay and handover probability.
EFFECT OF PROBIOTIC, PREBIOTIC AND SYNBIOTIC ON COLON AND CECUM MICROBIOTA OF RATS

Prebiotics, probiotics and synbiotics have been considered alternatives for the maintenance of a healthy gut. A large number of data exists corroborating beneficial effects upon consumption of these functional food ingredients but experimental works evaluating the three approaches in the same study are rare. In this work we evaluated the implications on the increase of bifidobacteria and decrease of E. coli, as well as the modulation of some groups of the rat native microbiota upon administration of newly isolated human Bifidobacterium breve strains (UFVCC 1087-1100), a fructooligosaccharide (FOS) Meioligo®, and a synbiotic containing the bifidobacteria and FOS. A 28-day experiment included forty female adult Wistar rats, randomly assigned to one of the four groups (control, prebiotic, probiotic, synbiotic). The three treatments increased bifidobacteria counts in cecum and colon (P<0.01). However, the synbiotic treatment was superior in bifidobacteria counts (P<0.01). Escherichia coli numbers were lower (P<0.01) in both segments of prebiotic and synbiotic groups. The weight index of the animals in all groups were the same (P>0.05), indicating no splenomegaly or hepatomegaly. The data strongly indicated that consumption of Meioligo® and Bifidobacterium breve (UFVCC 1087-1100), modulates favourably the bifidobacteria levels (P<0.01) and reduce E. coli numbers in the gut of the rat.
Using Semantic Web technologies to create a learning management system based upon Mixed Diagnostic Tests

—An approach to the construction of learning management systems based on combined usage of Semantic Web and Mixed Diagnostic Tests that are a compromise between unconditional and conditional components is considered. The main concepts and definitions are provided. Ontology models that describe the academic subjects and test assignments are proposed. Construction of learning management systems that use the developed models as knowledge base is proposed. Directions of follow-up research are provided.
High Data Rate MIMO-OFDM System using V-BLAST Architecture

High date rate wireless systems with very small symbol periods usually face unacceptable Inter-Symbol Interference (ISI) originated from multipath propagation and their inherent delay spread. Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier-based technique for mitigating ISI to improve capacity in the wireless system with spectral efficiency (bps/Hz). On the other hand, Multiple -Input Multiple-Output (MIMO) systems have rising attention of the wireless academic community and industry because their promise to increase capacity and performance with acceptable BER proportionally with the number of antennas. Thus we have obtained better bit error rate using V-BLAST technique.
SVM BASED CLASSIFICATION AND IMPROVEMENT OF FINGERPRINT VERIFICATION

: - Fingerprints are the oldest and most widely used form of biometric identiﬁcation. This recognition system is having the problem in terms of extraction of the fingerprint. One of such problems is the rotational aspect. There is also a problem of accuracy in identification and verification. The traditional PST and PCT rotational techniques do not provide 100 percent accuracy. In this proposed work, SVM classification along with the PST is used to get 100 percent accuracy and rotational invariency. The aim of this paper is to use the ability of SVM in pattern recognition and classification with PHT to improve the false acceptance rate (FAR) and false rejection rate (FRR). To give an objective assessment to the approach, both international and domestic fingerprint verification databases have been used for the evaluation. Afterwards, the training of data and data classifications has been done. Experimental results showed the substantial improvements in the accuracy and performance of fingerprint verification as well as in false acceptance rate (FAR) and false rejection rate (FRR) as compared to simple PST or PCT for image classification.
Approach forExtracting Opinion Targets and Opinion words from Online Reviews

Mining opinion pursuits and opinion words from on-line reports are fundamental duties for first-class grained opinion mining,the important thing aspect of which entails detecting opinion relations among phrases. We be taught a novel procedure, which looks for opinionrelations within the type of alignment approach. After thatgraph-situated algorithm is be trained. And at the last, acandidate who has bigger self belief those are extracted.As when put next with different approaches, this model is making theundertaking of opinion members of the family, for tremendous-span members of the family additionally. Asin comparison with the syntax procedure, the word alignmentmodel is looks for unintended effects of once we are watchingfor on-line texts. We will say that this model obtains betterprecision, As compared to the ordinary unsupervisedalignment model. When we seek for candidateconfidence, we get to understand that higher-degree vertices inthe graph-founded algorithm are decreasing the probabilityof the iteration of error.
A Survey on Assistive Technology for the Visually Impaired

- This paper outlines the various recent developments in assistive technologies for the visually impaired. The currently existing technology enables its users to detect and differentiate between objects, navigate, recognize text and provide vibrational and audio feedback to the user. The technologies make use of various techniques such as text-to-speech and speech-to-text translation, various sensors, image and video processing and recognition, natural language processing and generation and binaural image mapping. Assistive technologies are available for various platforms like android and iOS. Most of these applications take images as input and produce audio output to assist the user. However, some applications have dived into video processing and wearable technologies too. The technologies mainly focus on providing a user-friendly interaction and ease of access so that the user can get the knowledge of the objects in front of him or instructions to navigate in an easy and hassle freeway. This
Innovative results in the treatment of inespecific anusitis-proctitis with the use of bergamot gel (Benebeo gel)®

In lammation is a complex biological reaction induced by the alteration of tissue homeostasis, which occurs in response to the presence of a biological, chemical or physical agent in the body [1]. The acute in lammatory response is composed of an elaborate cascade of both proin lammatory and anti-in lammatory mediators, and balance between these mediators often determines the outcome after injury [2]. Generally during acute in lammation, cellular and molecular events and interactions reduce the risk of eventual injuries or infections. However, acute in lammation can become chronic, contributing to a variety of chronic in lammatory diseases [3]. Major micro circulatory events that occur during the in lammatory process include changes in vascular permeability, leukocyte recruitment and accumulation, and in lammatory mediator’s release [4].
A Middleware-level Approach to Adaptive Distributed Systems

This paper proposes an approach to adapting distributed applications to changes in environmental conditions, e.g., user requirements and resource availability. The key idea behind the proposed approach is to introduce the relocation of software components to deﬁne functions between computers as a basic mechanism for adaptation on distributed systems. It also introduces application-speciﬁc built-in policies for relocating components to deﬁne higher-level adaptation. It is constructed as a middleware system for Java-based general-purposed software components. This paper describes the proposed approach and the design and implementation of the approach with three applications, e.g., dynamic deployment of software at nodes in a sensor network and adaptive selection between data replication between primary backup and chain replication approaches in a distributed system.
RAPID SIMULTANEOUS SEPARATION OF FOUR SARTANS BY ISOCRATIC RP-HPLC METHOD: APPLICATION TO DETERMINATION OF OLMISARTAN IN PHARMACEUTICAL DOSAGE FORM

A simple, fast, precise, specific, highly sensitive, an accurate and reproducible isocratic reversed phase HPLC method has been developed for the separation of four sartans and validated for quantitation of Olmesartan in pure and in pharmaceutical formulation. One of the prominent aims for the method development is to achieve constant, reproducible separation. The effects of mobile phase composition, buffers, pH, and acetonitrile concentrations were investigated on the separation of sartans (Valsartan, Telmisartan, Olmesartan and Irbesartan) were assayed without any interference. The chromatographic separation was achieved on Welchrom C18 Column (4.6 X 250 mm, 5 μm) as stationary phase with the mobile phase comprising of phosphate buffer pH-3.3 and acetonitrile in the portion of 50:50 v/v. Isocratic elution at a flow rate of 1ml/min was employed. The detection was performed with Shimadzu SPD-20A prominence UV-Vis detector set at 232 nm. Total run time was 8 minutes and the elution window of two minutes. The validated method was successfully applied to the commercially available Olmesartan pharmaceutical dosage form yielding very good and reproducible results. During method validation parameters such as linearity, precision, specificity, robustness and ruggedness were evaluated from spiked tablet samples according to ICH guidelines, which remained within acceptable limits. The proposed method can also be extended for the determination of other three sartans or their combinations with hydrochlorothiazide. This method provides a fast simple method with good retention, excellent peak shape and high resolution.
Chlamydophila Pneumonia

Chlamydophila pneumoniae (formerly Chlamydia pneumonia (is a Gram-negative intracellular bacterium [1] responsible for acute upper and lower respiratory tract infections. The first known case of infection with C. pneumoniae was a case of sinusitis in Taiwan. This atypical bacterium commonly causes pharyngitis, bronchitis, sinusitis [2] and atypical pneumonia [3] not only in elderly and debilitated patients, but also in healthy adults [4]. The term atypical pneumonia was used by Reiman in 1938 to describe the infection of noncharacteristic course resistant to sulphonamide therapy [5]. Some researchers used the term “infections with atypical pathogens” to describe infection caused by Chlamydia, Mycoplasma and Legionella [6]. In addition to pneumonia, C. pneumoniae causes extrapulmonary manifestations include nervous system disorders such as Guillain-Baré syndrome and meningoencephalitis as well as atherosclerosis and coronary artery disease [7], reactive arthritis [8] and myocarditis [9].
Ranking of Resulting Objects and Snippet Generation

Semantic web search engine Falcons support keyword based search for linked objects by using comprehensive virtual document which it creates for each object. In our work we are suggesting idea of using Selectivity Estimation of triple patterns for ranking of resulting objects and generating snippet for the keyword query for Falcons Semantic web search engine. Selectivity of a triple pattern is the fraction of triple satisfying the keyword query. Our work ranks resulting objects considering their relevance to the keyword query. For each resulting object for a searched keyword query, Object-rank is calculated by calculating the query-relevant-index for
Feature Selection for High Dimensional Data

: Feature selection is an active research area in pattern recognition, statistics and data mining community. Idea behind feature selection is to choose a subset of input variables, eliminating features with little or no predictive information. Feature selection (FS) is to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. This can significantly improve the comprehensibility of the resulting classifier models and often build a model that generalizes better to unseen points. Rough set theory (RST) can be used as a tool to discover data dependencies and to reduce the number of attributes contained in a dataset using the data alone, requiring no additional information. In this paper, feature selection technique has been used in high dimensional data for removing irrelevant features and producing high accuracy for post processing data.
MEAN SQUARED KERNEL INDUCED FUZZY POSSIBILISTIC C-MEANS: AN ANALYZING HIGH DIMENSIONAL DATABASE

In order to find an available subgroups in real life databases this paper presents effective fuzzy c-means by incorporating the membership function of fuzzy c-means, the typicality of possibilistic c-means approaches, mean squared kernel induced distance. To show the effectiveness of the proposed method this paper successfully implements the proposed method with synthetic dataset and it shows the superiority of the proposed method through clustering accuracy.
Independent Feature Detector for Image Quality Assessment

- Image quality assessment plays a key role in evaluating and optimizing image processing systems. Such Image Quality Metrics (IQM) are largely based on visual perception characteristics as the human visual system (HVS) is the ultimate receiver of images. Independent Component Analysis (ICA) models are similar to the primary visual cortex which is an important part of the HVS. Inspired by this, we make use of Independent Feature Similarity (IFS) index for the full reference IQA. The proposed technique involves a feature detector which is trained on the natural images by ICA. Independent features are acquired from this feature detector. The computation of IFS involves two components: feature and luminance. Based on these two components the IFS index is computed. The performance score of IFS is also obtained.
DIRECT AND INDIRECT MICROPROPAGATION OF TURNERA ULMIFOLIA (L.) A MEDICINAL PLANT

The successful protocol for direct and indirect micropropagation of Turnera ulmifolia was developed. In vitro direct regeneration, multiplication and rooting of plantlets were observed from the nodal culture on MS medium supplemented with BAP (2.22μM) and TDZ (0.90 μM). The best callus proliferation and shoot formation from stem explants were observed in MS medium containing BAP (8.88μM). The higher percentage (87.34%) of root formation was observed in MS medium contain IBA (2.46 μM). The well rooted plants were acclimatized in shade house with mist chamber with 93.83 survival percentage.
Segmentation and Detection of Text in Natural Scene Images

Any text data present in natural scene images contains useful information like text based landmark etc. Extraction of text from scene images involves many stages. Each every stage is equally important to get efficient results. Detecting the text, localising the text, and segmentation, recognition are important steps. Extract.ion from scene text images is very difficult due to variations in size, orientation, alignment from one image to another. From all these difficulties extract.ion of text from scene images is a challenging task. However, text in such images is not confined to any page layout, and its location within in the image is random in nature. In addition, motion blur, non-uniform illumination, skew, occlusion and scale-based degradations increase the complexity in locating and recognizing the text in a scene/born-digital image. In our proposed method we have used The otsu binarization TECHNIQUE. It is applied on separated R, G, B channels. Based on connected component information the text is extracted. This method is implemented to handle light and night scene images. Keywords— Connected-Components, Dilation, Otsu-Method, Logical “And” Operation, Morphological, Rgb Channel
CARD-Utility Guided Clustered Anonymization of Relational Data with Minimum Information Loss and Optimal Re-Identification Risk

: Accumulation of relational data about the individual are exponentially grooming to support various organisations in maintaining financial records, manufacturing and logistical information and personnel data. These organisations are required to publish their data for analytical purposes. However this may cause privacy breach, if an invader deeds to link the possibly identifiable information to the records present in the published databases. Many data anonymization procedures that averts this threat by altering relational data before release have proposed in recent years, however these procedures suffers from information loss and utility loss. To address this issue, we propose a new utility guided clustered anonymization framework to anonymize relational data with high utility and less information loss. Based on this frame work, we developed three approaches varies on clustering process adopted for Record oriented Anonymization (RoA), which explores large solution space than existing methods and satisfies an extensive variety of privacy necessities. Furthermore, a classification analysis is performed on the anonymized datasets to ensure utility necessities. Experimental results on the benchmark data sets confirm that our framework expressively outperforms from 18% to 60% in terms of information loss, re-identification risk and classification accuracy than the existing procedures.