Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Security System for Dynamic Group in Cloud

Sharing group resource among cloud users is a major problem, so cloud computing provides an economical and efficient solution. Due to frequent change of membership, sharing data in a multi-owner manner to an untrusted cloud is still a challenging issue. In this proposal a secure multi-owner data sharing scheme, for dynamic group in the cloud. By providingAES encryption while uploading the data, any cloud user can securely share data with others. Meanwhile, the storage overhead and encryption computation cost of the scheme are independent with the number of revoked users. In addition, I analyze the security of this scheme with rigorous proofs. One-Time Password is one of the easiest and most popular forms of authentication that can be used for securing access to accounts. One-Time Passwords are often referred to as a secure and stronger forms of authentication, and allowing them to installed across multiple machines. It provides a multiple levels of security to share data among multi-owner manner. First the user selects the text based password. Then OTP is generated automatically and sent to corresponding e-mail account. Keyword—Cloud computing, Broadcast encryption.
Multiagent-based Autonomic and Resilient Service Provisioning Architecture for the Internet of Things

Summary This paper proposes the Agent-based Internet of Things (AIoT) architecture and AIoT middleware to realize autonomic and resilient service provisioning in IoT systems. As a massive number of devices are becoming part of the Internet, it is highly difficult to organize IoT devices as a system to provide appropriate services in our lives. It is difficult because the IoT devices are heterogeneous, and the situation often changes overtime which requires complicated reconfigurations of IoT systems. Our AIoT middleware provides IoT devices with the functionality of autonomic and resilient service provisioning in IoT systems. In this paper, we propose AIoT architecture of IoT application, AIoT organization and re-organization scheme to compose and operate IoT application according to user requirement and environmental condition. As the evaluation, we have implemented an autonomous logistics application with simplified logistics robots using proposed AIoT middleware, and conducted logistics experiments and scalability measurement simulation, to evaluate the effect of introducing AIoT architecture and AIoT middleware. We have also performed an architectural flexibility analysis on our architecture to examine further feasibility of proposals. The results of evaluations show the evidence of the realized capability of autonomic and resilient service provisioning, as well as the architectural flexibility of our middleware.
Reduction of Leakage Power in D-Flip Flop using LC nMOS Technique

__ Abstract - In CMOS circuits, Leakage Power dissipation is the major problem in front of the designers. There are various techniques introduced in the past decade to reduce the leakage power technique. One technique discussed in this paper. We propose a technique called LCnMOS for designing D-Flip Flop which significantly reduce down the leakage current without increasing the switching power dissipation. LCnMOS, a technique to tackle the leakage problem in all digital circuits, uses single additional leakage control transistor LCT, driven by the output from the pull up and pull down networks, which is placed in a path from pull down network to ground. This LCT provides the additional resistance thereby reducing the leakage current in the path from supply to ground. All the performance has been investigated using 90nm and 180nm Technology at 1 voltage as power supply and evaluated by the comparison of the simulation result obtain from TSPICE.
FACE RECOGNITION USING FACIAL FEATURES AND OBJECTS MATCHING IN UNCONSTRAINED IMAGES

: Detection of human posture is a research topic in visual research which finds its application in many areas such as intelligent digital content manager, social robotics and human activity reorganization, crowd behavior analysis and control, etc. Apart from this human posture detection is also used in pedestrian detection, 2D-3D animation, surveillance and robotics. Using the human posture detection method in real system is a challenging problem. As it require to compute the detection process in real time. Parallel computation provides the functionality to run the computation in minimum time utilizing all the resources . The developed algorithm will give better face recognition rate which is independent of variation in pose, lighting, expression, background, race etc. Many of these databases might be created under controlled conditions to facilitate on the face recognition problem to study the speciﬁc parameters. These parameters contain many variables such as camera quality, lighting position, pose, expression, background, occlusion, age, and gender. While there are many applications for face recognition technology in which one can control the parameters of image acquisition, there are also many applications in which the practitioner has little or no control over such parameters. This work is provided as an aid in studying face recognition problem as unconstrained. The existing database represents an initial attempt to provide a set of labeled face photographs in their everyday lives spanning the range of conditions typically encountered by people. This work describes a face detection system which goes beyond traditional face detection approaches normally designed for single faced images to few faces. The system described in this paper has been designed while taking into account of spatial coherence contained in multiple face detection. The resulting system constructs a feature based model for each detected face, and searches them using various model information in the database. It provides a feasible way to locate the positions of two eyeballs, near and far corners of eyes, midpoint of nostrils and mouth corners from face image. This approach would help to extract useful features on human face automatically and improve the accuracy of face recognition.
Probabilistic Multicast Trees in Different Network Topology Environments

Node loss and congestion changes the performance characteristics of the multicast trees. Probabilistic Multicast Trees (PMT) makes use of performance feedback, generates a probability of usage for each multicast tree based on that feedback and then makes intelligent choices about which multicast tree to use for a given packet in the presence of node loss and congestion. The advantage gained by using PMT is that it improves upon the management of the dynamic behavior of the clients where the target connectivity is constantly changing because of its feedback mechanisms and probabilistic tree selection. PMT is inserted onto three network latency topology models in a multiple tree multicast tree environment with positive improvements in the performance of data distribution.
Comparing Blood Values Sampled From Venipuncture and Continuous Infusion Catheter

Background: Most patients hospitalized at intensive care units have a continuous infusion catheter in place for receiving drugs and solutions; nonetheless, blood sampling in these units is still performed through an invasive and painful venipuncture. However, it is possible to take blood from a peripheral venous catheter to obtain accurate laboratory test results and alleviate the suering of patients. Objectives: The aim of this study was to compare hematology, chemistry, and blood gas values sampled from venipuncture and continuous infusion intravenous catheter. Methods: In this cross-sectional comparative study, a convenient sample of 61 adult patients was drawn according to the inclusion and exclusion criteria, from the intensive care unit. Two blood samples, one from a continuous infusion catheter, which was already in place and one from venipuncture at the other extremity, were obtained from each patient. The two sets of samples were compared in terms of hematology, biochemistry and blood gas values by using the paired-samples t-test. Results: The two sets of samples diered significantly in terms of blood sugar values. Other dierences between the two sets were not statistically significant. Conclusions: Except for blood sugar, blood sampling from a continuous 24-hour infusion catheter produces reliable hematol- ogy, biochemistry and blood gas results as that of venipuncture blood sampling method. Moreover, compared with the routine venipuncture method, sampling from a continuous infusion catheter is simpler, easier and safer.
A Comparative Survey on Various Load Balancing Techniques in Cloud Computing

Cloud computing is an emerging technology adopted by both industry and academia pro viding a flexible and efficient way to store and retrieve the data files. Today’s cloud comprises too many hardware and software resources. Load balancing is the crucial parameter required for efficient operation of various components in cloud computing environment. Clients request specific resources from the cloud. A efficient load balancing strategy must needed to be employed to map clients request to available resources in such way that lead to minimum load on the system and provide the resources at rapid rate. In this paper various load balancing algorithms and how this algorithms help in solving the issues of load distribution among various resources / virtual machine are discussed.
Scanning Severe Motion Blur Level inBarcode Images Using Image Blur EstimationScheme

The paper presents a fresh linear barcode scanning system based on hybrid template matching scheme. In current area, charge coupled device based scanning skills are not talented of handling motion blur image and trust severely on camera systems for capturing good quality, well focused barcode images which are due to the lack of selfcontrolled and proficient mechanisms. The proposed system is capable of understanding barcodes from low- resolution images containing severe motion blur and works totally in the dimensional domain. The proposed system also uses image blur estimation scheme for retrieving the severe motion blur in barcode images. We first estimate a lowdimensional approximation to the PSF by using some parts of clean barcode that are known by construction. This lowdim representation only involves a few parameters, which can be iteratively computed via the Levenberg-Marquardt (LM) algorithm. Polynomial interpolations are obtained in the rest of the PSF. A focused graphical model is designed to characterize the relationship between the blurred barcode waveform and its corresponding symbol value at any specific blur level. A hybrid programming-based inference algorithm is designed to regain the optimal state series, enabling synchronized decoding on mobile devices of limited processing power.
International Journal of Soft Computing and Engineering

Semantic similarity measures play an important role in the extraction of semantic relations. Semantic similarity measures are widely used in Natural Language Processing (NLP) and Information Retrieval (IR). The work proposed here uses web based metrics to compute the semantic similarity between words or terms and also compares with the state-of-the-art. For a computer to decide the semantic similarity, it should understand the semantics of the words. Computer being a syntactic machine, it cannot understand the semantics. So always an attempt is made to represent the semantics as syntax. There are various methods proposed to find the semantic similarity between words. Some of these methods have used the precompiled databases like WordNet, and Brown Corpus. Some are based on Web Search Engine. The approach presented here is altogether different from these methods. It makes use of snippets returned by the Wikipedia or any encyclopedia such as Britannica Encyclopedia. The snippets are preprocessed for stop word removal and stemming. For suffix removal an algorithm by M. F. Porter is referred. Luhn’s Idea is used for extraction of significant words from the preprocessed snippets. Similarity measures proposed here are based on the five different association measures in Information retrieval, namely simple matching, Dice, Jaccard, Overlap, Cosine coefficient. Performance of these methods is evaluated using Miller and Charle’s benchmark dataset. It gives higher correlation value of 0.80 than some of the existing methods.
COMBINING THE CLASSIFIERS AND LSI METHOD FOR EFFICIENT AND ACCURATE TEXT CLASSIFICATION

Text classification involves assignment of predetermined categories to textual resources. Applications of text classification include recommendation systems. Personalization, help desk automation, content filtering and routing, selective alerting, and training. This paper describes an experiment for improving the classification accuracy of a large text corpus by the use of dimensionality reduction and multiple-classifier combination techniques. Three different classifiers have been used namely Naive Bayes, Decision Tree and Association rule mining. The results of these classifiers are combined using techniques such as Simple Voting, Weighted Voting and Probability-based Voting. The classification accuracy is further improved by the use of a dimensionality reduction method called Latent semantic indexing (LSI). Experiments conducted on the Reuters 21578 dataset indicate that the combination approach provides an improved and scalable method for text classification. Also, it is observed that concept indexing helps with classification accuracy in addition lo efficiency and scalability.
Comparative Analysis and Performance Evaluation of MANET Routing Protocols

:- (MANETs) is a kind of distribution network system such as the internet World Wide Web social network and in MANET node are mobile and have the freedom to join or leave the network system . A simulation have carried out to evaluate the efficient of event MANET routing protocols (DSR, AODV, DSDV, TORA, FSR, CBRP and CGSR [9]. In this paper we have sure comparative performance analysis of different routing protocol. The number of node increasing random way point mobility and scenario where the node for detail simulation result and analysis a stable routing protocol can be close for specification. MANET network is a collection of mobile nodes that are dynamically and arbitrarily located in such a manner that the interconnections between nodes are capable of changing on a continual basis. In order to facilitate communication within the network, a routing protocol is used to discover routes between nodes. The primary goal of such an ad hoc network routing protocol is correct and efficient route establishment between a pair of nodes so that messages may be delivered in a timely manner
Classification of Microarray Data Involves Naïve Bayes and Dimension Reduction Using Haar Wavelet

: A general problem solving for handling microarray data is classification process with added a selection process from huge attributes. In particular, the escalated of attributes dimensionality provides a challenge to microarray handling techniques, related to microarray represents the large amount of genes expression. The multi-dependency (multicollinearity) may affect the performance when determining the parameter of classification. Many ways of solving the multicollinearity problem exists, the variable selection technique has become particularly popular. This is the method which use wavelet transformation for a few carefully selected variable and the method which regress respond variable onto a few linier combinations (components) of the original attributes. Wavelet is commonly used in image processing, spectral data using wavelet transformation have proved very successful in capturing the distinction among hyperspectral data. This paper investigates a new method of transformation data using Haar wavelet for selection processes. Our extensive study compares the selection processes using Haar wavelet transformation and Genetic Algorithm considering the selection dataset that implemented to Naïve Bayes classification. In addition, the selection-classification using Haar wavelet and Naïve Bayes describes a classification cancer and non-cancer quite well related to the accuracy of confusion matrix
EFFECTS OF NITROGEN SOURCES AND LEVELS ON YIELD AND NUTRITIVE VALUES OF SPINACH (SPINACIA OLERACEA L.)

Nitrogen (N) fertilizers as growth components in leafy crops are one of the main nutrients and play a significant role in crop yield and quality. Every year farmers have increased the application of N fertilizers on land, without considering the response of different nitrogen sources to N rate. This study was carried out to evaluate the effect of nitrogen sources and nitrogen fertilizer rates, on yield and quality of spinach (Spinacia oleracea L.). Field experiments were conducted during two successive seasons of 2011 and 2012, on three different nitrogen sources i.e., (ammonium nitrate, urea, calcium nitrate and five nitrogen fertilizer levels (0 (control), 80, 160, 240 and 320 kg N/ha. ). The experiment was arranged in a split plot, based on a randomized complete block design, in three replications. The main plot comprises three different nitrogen sources; i.e., (ammonium nitrate, Urea, calcium nitrate and five nitrogen fertilizer levels (0 (control), 80, 160, 240 and 320 kg N/ha. ) that were considered as subplots. The results showed that N fertilization level had significant effect on the weight of the fresh leaves, total nitrogen, nitrate and vitamin C content. The highest weight of the fresh leaves and C vitamin content were observed at 240 kg/ha nitrogen fertilizer level, whereas the highest total nitrogen and nitrate content were observed at 320 kg/ha nitrogen fertilizer level. While results of control treatment (no application of fertilizers) showed low weight of fresh leaves, total nitrogen, nitrate and vitamin C content. The higher weight of the fresh leaves and vitamin C content was found at the ammonium nitrate fertilization, compared to the calcium nitrate and urea, but the application of calcium nitrate had significant effect in a higher content of total nitrogen and nitrate.
Active Fault Tolerant Control (FTC) Design for Takagi-Sugeno Fuzzy Systems with Weighting Functions Depending on the FTC

In this paper the problem of active fault tolerant control design for noisy systems described by Takagi-Sugeno fuzzy models is studied. The proposed control strategy is based on the known of the fault estimated and the error between the faulty system state and a reference system state. The considered systems are affected by actuator and sensor faults and have the weighting functions depending on the fault tolerant control. A mathematical transformation is used to conceive an augmented system in which all the faults affecting the initial system appear as actuator faults. Then, an adaptive proportional integral observer is used in order to estimate the state and the faults. The problem of conception of the proportional integral observer and of the fault tolerant control strategy is formulated in linear matrices inequalities which can be solved easily. To illustrate the proposed method, It is applied to the three tanks systems.
Removal of Refractory COD from Pharmaceutical Wastewater using HCO3

The increasing concern on the presence of pharmaceutical compounds in the drinking water has increased nowadays mainly due to the potential risk to the health of human being. Advanced oxidation processes (AOPs) are widely used for the removal of recalcitrant organic constituents from industrial wastewater. This study mainly aimed to investigate removal of chemical oxygen demand (COD) from pharmaceutical wastewater using HCO3 and Fenton oxidation process in a batch reactor. Experiments were conducted under the various pHs (3-7) and temperatures (19-27°C) condition. Various amounts of H2O2, Fe 2+ and HCO3 were taken in order to optimize the refractory COD reduction.COD reduction was found 70% and 15% in Fenton oxidation process and HCO3 process subsequently. Moreover the results showed that Fenton oxidation process is capable of achieving high refractory COD removal at about pH-3. Keywords-pharmaceutical compounds; advanced oxidation processes; recalcitrant organic constituents; industrial wastewater; refractory COD.
Current Control Strategy for Parallel Operation of Inverters Based on Micro grids

In this paper, a new control method for the parallel operation of inverters operating based on LV micro grids is proposed. This new approach can be applied to the inverter-based micro grids using renewable energy sources where communication wires are not reliable due to the remote locations. The proposed strategy is based on the advanced droop control technique where only the locally measured values are used as feedback. Unfortunately, the trade-off has to be made between the transient response and the power sharing accuracy for the conventional voltage and frequency droop control method. Moreover, the output and line impedance of the inverter presents a great impact on the power sharing accuracy. This paper explores the resistive output impedance and line impedance of the parallel connected inverters in island micro grid. The active and reactive output current is used as the control variables so as to limit the current spikes during the initial and transient states. Additionally, the derivate-integral terms are introduced to enhance the dynamic response of the inverters. Simulation results and waveforms are given to validate the proposed control strategy.
EFFICIENT FACE RECOGNITION SYSTEM USING HYBRID METHODOLOGY

Recognizing frontal countenance of human beings by a computer system is an interesting and challenging problem. Facial recognition System has emerged as an adorable solution to address many instant needs for identification and the verification of identity claims. It brings together the portend of other biometric systems, which attempt to tie identity to individually distinctive features of the body. Facial feature extraction consists in restraining the most characteristic face countenance such as eyes, nose, and mouth regions within the face images that portray the human faces. In this paper, the two most well-known algorithms i.e. PCA and LBP are introduced and the combination of Local Binary Pattern (LBP) and Principal Component Analysis (PCA) is presented as our proposed approach in which the proposed approach has achieved 93.5% of gain in processing memory. LBP algorithm is used as feature extractor of the face image. LBP is used for their resistance against changing frontal facial expressions. PCA algorithm is used for dimension reduction of the countenance vector. The complete approach has been tested on databases of people under different facial expressions.
High Speed Radix-8 based MAC used for 2D-Image Compression

Field programmable gate arrays are ideally suited for the implementation of DCT based digital image compression. However, there are several issues that need to be solved. The Multiply-Accumulate Unit (MAC) is the main computational kernel in DSP and DIP architectures. The proposed MAC unit determines the power and the speed of the overall system; it always lies in the critical path. In this work, a fast and low power MAC Unit is proposed for 2D-DCT computation. The proposed architecture is based on modified booth radix-8 with merged MAC architectures to design a unit with a low critical path delay. The new architecture has reduces the hardware complexity of the summation network, it reduce the overall power. Increasing the speed of operation is achieved by feeding the bits of the accumulated operand into the summation tree before the final adder instead of going through the entire summation network. The FPGA implementation of the proposed booth radix-8 based MAC unit saves 64% of the area, to the regular MAC unit with conventional multiplier.