Miracle-dz/UniFAR-FTUs huggingface dataset:
Speech based Query Searching Technique and it’s Application in Library Management System

Customary library inventories have turned into wasteful and badly designed in assisting library clients. Readers are spending too much time in looking through materials related to library by means of inventory copies. Pursuers need a smart and creative answer to sort out this issue using speech itself. Speech is the most effortless approach to speak with one another. Recently, Speech processing is mostly used in applications like devices used for security purposes, household appliances, cellular/mobile devices, Automatic Teller Machines (ATMs) ,computers and etc. The man machine interface is also created to associate people who are experiencing some kind of disabilities. Speech processing is nothing but the strategy to process and break down the speech signals. It has great advantages for disabled people and discovers their applications in our everyday lives. In this paper, we have connected different data mining models to distinguish the required course book which is available with using speech signals and furthermore findings in a book which is frequently issued to readers. It is very much useful to deaf peoples in society. In this we applied Mel-frequency cepstral Coefficients (MFCC) to extract the features from speech signal of isolated spoken words and applied GMM and DNN models for discovering whether required book is present or not and observed is DNN gives the great accuracy and We are also converting the given speech into text format and apply association rules to find the book that is frequently issued.
A Study on Different Approaches on Image Segmentation

-- Segmentation is the process to retrieve the feature or ROI from input image. The process is beneficial as the early preprocessing stage as well as application to identify the meaningful information from images. To obtain the meaningful information, more effective segmentation approach is required. In this work, a study is defined on the segmentation in image processing. The paper has discussed some of the common type of segmentation types applied on images.
HPTLC FINGERPRINTING OF CONVOLVULUS ARVENSIS L

ABTRACT Convolvulus arvensis L. is a long lived deep rooted weed belongs to the family convolvulaceae. It is commonly known as European bindweed, bindweed, creeping jenny, morning glory, and devil’s guts. Most people assume weeds have no therapeutic value. However, the difference between weeds and herbs may merely be our understanding of them. Weeds are unwanted plants and are considered harmful, as they compete with crops for light, moisture and nutrients, and harbour insects and diseases harmful to crops. For farmers and agriculture specialists, weeds are unwanted plants, but for herbalists, all weeds are useful plants. Traditionally its was commonly used as ant-helmintic in animals, anticancer, Cytotoxic, laxative and stimulant action . The present study deals with HPTLC fingerprinting of methanol extract of C. arvensis carried out by using various types of solvent system for separation of as many as phytochemicals. Results revealed that the presense of several constituents in the extracts. The number of constituent in the extract and their retention factor (Rf) are summarized in Table 1-11 and chromatographic profile given in figure 1-5. HPTLC results indicate the number of constituents and further facilitate their quantitative estimation and qualitative separation of pharmacologically active chemical compounds. More phytochemical research work is required for isolation, purification and characterizat ion of bioactive compounds.
TOrBAC: A Trust Organization Based Access Control Model for Cloud Computing Systems

--The access control models like DAC, MAC, RBAC, TBAC, TMAC, DomBAC, etc. mainly model security policies for information systems having a centralized governance. Moreover, they only specify permissions and prohibitions, sometimes obligations. Besides that, they generally do not allow the establishment of activated, dynamic and adapted rules. However, such rules are highly useful in a cloud environment where IT governance is shared, used or managed by different entities. In this paper, we propose a new model for specifying such security policies. This model called Trust Organization Based Access Control (TOrBAC) which relies on the use of a recursive formula for calculating a confidence index. We also formalize our work using a language based on first order logic and we apply it to a cloud computing (CC) related use case.
Emerging Markers from Molecular Studies: Application into Routine Salivary Gland Fine Needle Aspiration Biopsy Practice

Salivary gland neoplasm (SGN) is one of the largest groups of neoplasms, with over 3 dozen benign and malignant tumors in the 2005 WHO classification and with additional entities recognized during the last decade. Current success of fine needle aspiration biopsy (FNAB) in SGN diagnosis is largely because of its high sensitivity and specificity in: 1) distinguishing neoplastic from non-neoplastic salivary gland lesions and 2) distinguishing benign and low grade salivary gland neoplasms from high grade malignancies. However, precise subtyping of SGNs remains a diagnostic problem for some FNAB cases. These challenging cases include: 1) low grade malignancies with minimal malignant cytological features; 2) accurate subtyping of high grade malignancies, including metastatic malignancies; 3) benign SGNs that can only be differentiated from their malignant counterparts by growth pattern evaluation (e.g. basal cell adenoma vs. basal cell adenocarcinoma).
Denial-of-Service Attack Detection Using Anomaly with Misuse Based Method

-Denial-of-Service attack is an attempt to make a system, machine or network resources unavailable to its user by blocking or denying the services. The Denial-of-Service attack is identified with the help of detection algorithm. The anomaly detection mechanism not provides the better results so the user need to implement the hybrid detection algorithm which is the combination of anomaly detection with misuse based detection. The new techniques have the advantage of reduce the false alarm rate and improve the detection rate. The detection technique use time as a parameter to detect the intrusions. Denial-of-Service attack detection system that uses Multivariate Correlation Analysis for accurate network traffic characterization by extracting the correlations between network traffic features and increase the speedup of the process.
INTRUSION DETECTION SYSTEM BASED ON FCA USING GA

: Intrusion detection is the process of supervising the events taking place in a computer system or network and analyzing them for signs of possible activities, which are assaulted or close to threats of violation for computer security. Incidents have many causes, such as malware (e.g., worms, spyware), attackers gaining unauthorized access to systems from the internet, and authorized users of systems who misuse their privileges or attempt to acquire extra privileges for which they are not empowered. Proposed method includes GA-based fuzzy Class Association Rule Mining with sub-attribute utilization and its application to classification, which can deal with discrete and continuous attributes at the same time. In addition, the proposed method is applied to both misuse detection and anomaly detection. Since the association rules used in the traditional information detection cannot effectively deal with alterations in network behaviour, it will better satisfy the real needs of abnormal detection to introduce the concept of fuzzy association rules to strengthen the adaptability.
Unsupervised Learning on Cosmic Ray Daily Harmonic Variations

: Clustering is division of data into groups of similar objects. From a machine learning perspective cluster correspond to hidden patterns. In unsupervised learning we find cluster to represent a data concept. Since scientific organizations also generate large volumes of data, the challenges are to analyze the data using the recent data mining techniques, so as to arrive at meaningful conclusions. For real life applications, we have used the hourly cosmic ray intensity data from 1965 to 2006 to first derive for each day, the amplitude and phase of the harmonics of the daily variation (r 1 ,  1 , and r 2,  2 ). We have applied the k-mean partitioning algorithm, the agglomerative hierarchical clustering algorithm BIRCH, and the density based partitioning algorithm DBSCAN on the above set of daily data containing r 1 ,  1 , and r 2,  2 for each day. Many interesting clusters have been identified. The cluster analysis indicates that a very clear-cut 10-11 year periodicity is observed in the harmonics dataset even when all the four attributes are considered together. Moreover, similar characteristics are repeated after a gap of 10-11 years and many years occurring in pairs in the two sets (out of the 4 sets, each of about 10-11 years) are the outlier years. The years 1996 and 1997 are particularly emphasized as outliers. These results are similar to that reported in literature, though by statistical methods and by considering only r 1 and  1 and not all the four attributes taken together. As such the superiority of the mining technique is revealed in the real life situations.
A Focus on the Treatment of Anthracycline Extravasation and Tissue Protection

Accidental extravasation of anthracycline-based chemotherapy is a complication that has been feared since the introduction of the anthracyclines more than 40 years ago. Tissue infiltration with vesicant drugs may lead to progressive necrosis and destruction of muscles, tendons, nerves, and joints, and may be associated with severe functional and cosmetic changes. During the last four decades, much effort has been made to prevent such accidents from happening. In addition, different surgical approaches and several non-pharmacolgical and pharmacological treatments have been used to counteract the devastating effects of the extravasation. Most treatment modalities have been empirically based, and only a few have undergone thorough evaluation. Recently, dexrazoxane was shown to be an effective and non-toxic acute treatment for anthracycline extravasation. It has since become a widely recommended treatment, and Totect® is currently the only approved drug for this indication.
Accessibility analysis for the visually impaired using LazarilloApp

Visual impairment causes limitations, including mobility. Studies show that there are about 1.3 billion people in the world with some type of visual impairment. Another important factor refers to the need to include these visually impaired people in schools and universities, for autonomy, learning and personal development. Public policies seek to implement measures that ensure the inclusion of people with disabilities, in order to ensure the use of environments in an equal manner. However, these measures are not implemented due to several factors, such as the lack of knowledge of professionals and the lack of financial and technological resources. This research project aimed to evaluate the use of LazarilloApp, a georeferencing application that helps the mobility of people with visual impairment. The tests were conducted at a university in Brazil. Although it has many features and potential, the application was partially effective and efficient, since in only one of the four routes drawn by it the user arrived at the destination. The accessibility problems identified reinforce the need to enable access through structural changes in physical spaces. The results indicate the need to foster the improvement of the functionalities of LazarilloApp and other mobile applications of free access, for the disabled.
Real-time Communication System for the Deaf and Dumb

: This project aims to aid the deaf-mute by creation of a new system that helps convert sign language to text and speech for easier communication with audience. The system consists of a gesture recognizer hand-glove which converts gestures into electrical signals using flex sensors. These electrical signals are then processed using an Arduino microcontroller and a Python-based backend for text-to-speech conversion. The glove includes two modes of operation – phrase fetch mode and letter fetch mode. The phrase fetch mode speaks out words at once, while the letter fetch mode speaks out individual letters. This project forms a base infrastructure which can later be augmented with addition of different Sign Languages and integrating with other hearing impaired aid systems.
Evaluation of Textural Feature Extraction Methods for Prostate Cancer TRUS Medical images

imaging is one of the promising techniques used for early detection of prostate cancer. The image is segmented by different methods after preprocessing. In this paper, DBSCAN clustering with morphological operators is used to extort the prostate region. It is proposed to analyze the performance of the features extracted from the different Gray Level Co-occurrence Matrix (GLCM) constructed for various distances with different combination of directions, since there is no research has been conducted so far. Then, Support Vector Machine (SVM) is used to classify the images into benign or malignant using the extracted features. The performance of the classification is evaluated using various statistical measures such as sensitivity, specificity and accuracy. The proposed method is tested over 5500 digitized TRUS images of prostate. KeywordsVector Machine; SVM; Gray Level Co-occurrence Matrix; GLCM; DBSCAN; M3-Filter.
IMAGE MODIFICATION DEVELOPMENT AND IMPLEMENTATION: A SOFTWARE MODELING USING MATLAB

To solve problems in the related to digital image modification generally require experimental work involving software modeling and testing with large sets of images. This paper is presenting an overview of the fundamental steps of digital image modification. Some details of the layout and the working of an experimental software system that has been developed and executed using MATLAB is introduced. In this modeling system, a user friendly GUI is developed and two alternative methods for image acquisition are executed. Few algorithms based on computing operators for image modification are studied, programmed and examined. This research paper also includes an analysis and a software executed for an image comparing technique
The expression and function of RAGE and HMGB1 in airway structural cells in asthma

Asthma is characterised by airway hyperresponsiveness, airflow obstruction, chronic inflammation and airway remodelling, with an increase in airway smooth muscle (ASM) mass and contractility. ASM also releases mediators that support inflammation and remodelling. High-mobility group box 1 (HMGB1) is a nuclear protein that is released by damaged/stressed cells and activated immune cells. HMGB1 signals through pattern recognition receptors (PRRs) including the receptor for advanced glycosylation end products (RAGE) to promote inflammation and tissue repair. HMGB1 binding and function are governed by its redox state. Evidence suggests HMGB1 elevation in asthma; however, the redox state of airway HMGB1 is unknown. Moreover, the expression and role of RAGE in regulating airway mesenchymal cells are unknown. We aimed to investigate HMGB1 and RAGE expression in bronchial tissue; the redox form of sputum HMGB1; the expression and role of HMGB1 and RAGE in airway structural cells. HMGB1 was 3.5-fold higher in sputa of moderate-to-severe asthmatics (n=34), and the reduced form was shown to be increased in this group (n=16) for the first time. Reduced HMGB1 was chemotactic for peripheral blood leukocytes, and sputum HMGB1 correlated with sputum total cell counts. HMGB1, but not RAGE, expression was ~3-fold higher ex vivo in ASM of severe asthmatics (n=16). ASM and human bronchial epithelial cells (HBECs) expressed both HMGB1 and cell-surface RAGE in vitro. HMGB1 expression was upregulated in ASM cells stimulated with inflammatory cytokines. HMGB1 stimulation caused increased reactive oxygen species production in ASM cells from non-asthmatics, but not in asthmatics; ASM contraction and inhibition of ASM cell migration and HBEC wound healing. These results suggest that HMGB1 promotes inflammatory cell recruitment, impairs epithelial and ASM repair, and promotes ASM contraction in asthma. Further work is required to determine whether antagonising HMGB1 or its receptors would be a viable therapeutic approach for the treatment of asthma.
MULTI-BIOMETRIC AUTHENTICATION PROTOCOL FOR SMARTPHONES

Smartphones are increasingly used for different digital services such as social networks or e-commerce. User authentication using passwords on these devices is not friendly enough and does not offer a high level of security to the users. Voice biometrics can provide a popular solution to achieve a high level of security and privacy with the integration of smartphones’ fingerprint sensors. We propose in this paper a new protocol combining fingerprint and voice biometrics to improve users’ authentication security while maintaining ease of use and respect to privacy. The voice biometrics captured through an authentication word in addition to the authentication fingerprint is considered an effective method for quick authentication. We believe that the proposed solution offers many advantages in terms of security, with respect to privacy. We show through the experimental results the effectiveness of the proposed method even in case of attacks.
Natural Language Interface for Casual User to Retrieving the Information from Ontologies

— In the traditional keyword-based system the process of information retrieval is done only by keyword, and not by the meaning of that word. The machine cannot understand the meaning and relationships between the entities which are presenting in the system. In the semantic web, the meaning and relationship are described in structured knowledge representation or ontologies. In Semantic search, it provides the facility to machine to understand the meaning of terms and concepts. Typical users are overwhelmed by the formal logic of Semantic web. The fundamental problem is to help the users for querying ontologies whose logic they do not understand. For this, the solution is to provide the Natural Language Interface which can take the Natural Language Queries and mapped them into the SPARQL queries. But such tools suffer from the problem of the entering the ungrammatical queries. Furthermore, these kinds of system are hard to adopt the new domains. In this proposed system, we have used the simple approach to map relationship between the entities. Although the method is simple, it achieves the right information retrieval performance. It focuses on domain independent automatic mapping of NL to SPARQL for ease of use and portability.
Abnormal Web Video Detection Using IQR Method

: Recently, discovering outliers among large scale web videos have attracted attention of many web mining researchers. There are number of outlier videos exists in each category of web videos such as Entertainment, Sports, News and Politics, etc. The task of identifying and manipulate (to remove from the web or to share with others in the web, or to watch/download from the web etc.) such outlier web videos
Verilog Implementation of 64-bit Redundant Binary Product generator using MBE

Adders are the key element of the arithmetic unit, especially fast parallel adder. Redundant Binary Signed Digit (RBSD) adders are designed to perform high-speed arithmetic operations. Generally, in a high radix modified Booth encoding algorithm the partial products are reduced in multiplication process. Due to its high modularity and carry-free addition, a redundant binary (RB) representation can be used when designing high performance multipliers. The conventional RB multiplier re -quires an additional RB partial product (RBPP) row, because an error-correcting word (ECW) is generated by both the radix-4 Modified Booth encoding (MBE) and the RB encoding. This incurs in an additional RBPP accumulation stage for the MBE multiplier. In this paper, a new RB modified partial product generator (RBMPPG) is proposed; it removes the extra ECW and hence, it saves one RBPP accumulation stage. Therefore, the proposed RBMPPG generates fewer partial product rows than a conventional RB MBE multiplier. Simulation results show that the proposed RBMPPG based designs significantly improve the area and power consumption when the word length of each operand in the multiplier is at least 32 bits.
MODULATION CLASSIFICATION USING SPECTRAL FEATURES ON FADING CHANNELS

: Modulation classification plays a key role in demodulation of the received signal for extracting the required information. Modulation classification is a difficult task when there is no information about the received signal (Blind Classification) and especially in presence of multipath fading and white guassian noise. Emerging applications of automatic modulation classification (AMC) in military, civil and cognitive radio (CR) applications leads to the development of various AMC algorithms. The Automatic modulation classification can be achieved by two major approaches, Likelihood based and features based pattern classification approach. In this paper first we have analyze and discourse the merits and demerits of both categories, then we have proposed an algorithm based on spectral features of the modulated signal. The proposed classifier is Multilayer perceptron which is also referred as feed forward back propagation neural network. The channels considered throughout the simulations are additive white guassian noise (AWGN) channel, Rayleigh flat fading and Rician flat fading channel. The considered modulation formats are PAM 2 to 64, PSK 2 to 64, FSK 2 to 64 and QAM 2 to 64. The proposed algorithm will recognize the considered modulation formats with 100% success at 0dB SNR. Tables in the form of confusion matrix and graphs shows correct classification rate for considered modulation formats.
LOW-POWER CLOCK DISTRIBUTION IN EDGE TRIGGERED FLIP-FLOP

The major power consumption in portable electronics devices is due to the long interconnects. These interconnects are global buses, control signals and synchronization clock signals. Other the power dissipation interconnects causes the increase in path propagation delays. The conventional synchronization clocks signals are becoming increasingly difficult for multiple higher frequency integrated circuits because skew, jitter, and variability are often proportional to large latencies. This paper represents gilt edge solution to these problems.This paper's work reduce the sophisticated circuitary by reducing the number of transistors compulsions which further diminishes the stray capacitance. This paper's work reduce the aggressive power with merest feasible area and delay trade off by dimishing transistor size.
DATA MINING APPROACH FOR CLASSIFYING TWITTER’S USERS

Social networks are the most important communication channels in recent years, which popular among the different social groups. These networks affected the ideas and policies of individuals, groups and communities. Every day, millions of tweets on Twitter are being published. These tweets reflect opinions and beliefs of their publishers and affect others as well. Therefore, it is important to analyze these tweets and identify and classify trends of different users. This research aims to classify social network to anomaly groups such as: Terrorist and dissident; by analyzing tweets data on the Twitter; then identify an anonymous user’s affiliation to these groups. To address this problem, we first extract a set of features to characterize each group using different data mining techniques and store these features in the database. Text mining, sentiment analysis, and opinion mining techniques will be used to accomplish this extraction. The objective of data extraction is to measure the similarity of selected user tweets with respect to extracted features. It will enable to determine high percentage of similarity between the user tweets and group characteristics to expose his/her affiliation to this group.