Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of Ventricular Fibrillation Based on Sequential Increment Method

 Abstract — T his study is for developing an embedded method for automatic diagnosis of ventricular fibrillation (VF) by using a neuro-fuzzy system embedded in an automated external defibrillator (AED). To diagnose VF using AEDs, we use the neural network with weighted fuzzy membership functions (NEWFM), a wavelet transform (WT), a sequential increment method (SIM), and phase-space reconstruction (PSR) in order to classify normal sinus rhythm (NSR) and VF of electrocardiogram (ECG) episodes. This study has the following key points. The first contribution is the extraction of peaks from ECG episodes by the use of the WT and SIM by a time-frequency technique. The second contribution is that NSR and VF are distinguished by means of three-dimensional (3D) PSR based on a 3D graphic model. The third contribution is the identification of feature differences between NSR and VF by the use of graphical characteristics of weighted fuzzy membership functions (WFMs) supported by the NEWFM. The final contribution is the development of a neuro-fuzzy system for automatic diagnosis of VF using the WFMs embedded in the AED. The following four preprocessing steps are implemented to extract features from ECG episodes. In the first step, the WT is used for multi-scale representation and analysis and wavelet coefficients are then generated from the ECG episodes. In the second step, the SIM is used to extract peaks from the wavelet coefficients. In the third step, successive peaks are plotted in a 3D phase-space diagram by performing 3D PSR. In the final step, the distance between the origin (0, 0, 0) and the successive peaks plotted in a 3D phase-space diagram is calculated; then, 20 features are extracted from the calculated distances by using statistical methods, including frequency distributions and their variability. The 20 extracted features are applied as inputs to the NEWFM, and the result is that the classification accuracy of the NEWFM is 100%.
Review of MIMO Zero-Order Resonant Antenna

MIMO is often traced back to 1970s research papers concerning multi-channel digital transmission systems and interference (crosstalk) between wire pairs in a cable bundle: A R Kaye and D A George (1970) [1], Branderburg and Wyner (1974) [2], and W. van Etten (1975, 1976) [3]. A multiple input multiple output (MIMO) technique has been considered one of the most developing techniques for various wireless applications to enhance the performance of wireless communication system. A MIMO system utilizing several antenna components is more advantageous than a single input single output (SISO) system in terms of increasing channel capacity and reducing transmitting power. When the transceiver uses more than one antenna, the antennas must be placed minimum at least half of the carrier wavelength apart, in order to transmit or receive an uncorrelated signals. Up to date, most MIMO antenna systems with more than two antennas are three-dimensional instead of planar. But the basic problem with the MIMO systems is the requirement of electrically small antennas which usually have several constraints. Since antenna integration and miniaturization are two major challenges in MIMO systems, the performance parameters of antenna are optimized to achieve an Omni directional radiation pattern with reasonably wide impedance bandwidth and high gain. In order to achieve the above challenges we can implement the MIMO antenna using zero-order resonant materials.
LEVITATION AND SPEED CONTROL OF BEARINGLESS SWITCHED RELUCTANCE MOTOR USING FUZZY SLIDING MODE CONTROLLER

The bearingless switched reluctance motor (BSRM) is an integrated device of the switched reluctance motor and the magnetic bearings (MBs) with simple structure possessing no mechanical contact and friction. The nonlinear and uncertain nature of BSRM makes the design of controller difficult for steady levitation of rotor and one of the prominent model-free control techniques to tackle such uncertain systems is the sliding mode control (SMC). This paper proposes a control strategy by merging the intelligence of fuzzy logic with SMC, known as fuzzy sliding mode controller (FSMC) to overcome the drawbacks of SMC regarding high control gains and chattering. The proposed controller modifies the signum function of switching control term with fuzzy logic function, to eliminate rotor vibrations (chattering) with assured robust levitation control under load variations and disturbances. The effectiveness of the proposed FSMC is demonstrated through simulation studies using Matlab/Simulink software comparing with the conventional sliding mode controller.
Isolation and Identification of Anaerobic Yeasts and Bacteria from Weasel Coffee for Cellulase and Pectinase

Weasel coffee possesses an unique flavor which was an incredibly delicious combination of musty, syrup, chocolate and high extraction soluble solids content. However, low quantitative production of this traditional fermented coffee increased their cost. As a result, there was a steaming necessary of a new method to process coffee in industry and out of biosystem by enzymes or microbes to make high quality and productive coffee yield with a much lower cost. Thus this was the primary study aimed to isolate yeast and anaerobic bacteria that produced cellulase and pectinase from Lam Dong weasel coffee. Fifteen strains of anaerobic microorganism including four bacteria and eleven yeasts were isolated on malt medium in the anaerobic condition. All isolated microorganisms could produce cellulase and pectinase. Only 6 strains of isolated microorganisms with very fast growth rate, and highest evaluation of cellulase and pectinase were chosen to be identified with DNA sequencing method. Three highest cellulase producer strains were identified as Torulaspora delbrueckii, Hanseniaspora uvarum, Candida boidinii, while Wickerhamomyces anomalus, Enterobacter sacchari, Pantoea vagans acconted for the 3 highest pectinase production microoraganisms found in this study.
Design and Implementation of Control system for Magneto-rheological damper for vibration reduction in a cantilever beam like structures

ARTICLE INFO The analysis and design of control system for Adaptive vibration for cantilever beam like structure is presented in this paper. The control system is implemented via semiactive magneto rheological (MR) damper located on the suspension that links the beam to the ground. Project study is concerned with the Single degree of freedom (SDOF) isolation system with MR fluids damper under harmonic excitation. A mathematical model of the MR fluid damper with experimental verification will be adopted. The motion characteristics of the SDOF system with the MR damper will be studied and compare with those of the system with a conventional damper. The energy dissipated and equivalent damping coefficient of the MR damper in terms of input voltage, displacement amplitude and frequency will be investigated. Keywords— Magneto rheological (MR) fluids, Magneto rheological dampers; control system, Carbonyl powder particle; Magnetic field intensity. Article History Received :18 th November 2015 Received in revised form :
Enterprise Resource Planning (ERP) in Universities

Implementing Enterprise Resource Planning (ERP) systems allows organizations to achieve many benefits including the availability of integrated information, high responsiveness to customers' and suppliers' needs and the provision of timely information to decision makers. Another key benefit of ERP systems is the integration of information throughout the supply chain which leads to cost and inventory reductions and improved operating performance. This of course excels the performance of the functional areas within organizations. The major problems of ERP implementation are not technologically related issues such as technological complexity, compatibility, standardization, etc. but mostly about organization and human related issues like resistance to change, organizational culture, incompatible business processes, project mismanagement,
Effective Strategy for MPPT in PV/Wind Hybrid Electric Power System Interconnected with Electrical Utility Grid

This paper focusing in modeling and simulation of incremental conductance(inc. cond)algorithm of maximum power point tracking (MPPT) method used in photo voltaic/wind hybrid electric power system inter connected to the electric utility. PV/wind HEPS, taking into account all radiation, temperature, variation of wind speed and load demand. The resultant system is capable of tracking MPPs accurately and rapidly without steady-state oscillation, and also, its dynamic performance is satisfactory. The incremental conductance algorithm is used to track MPPs, because it performs precise control under rapidly changing atmospheric conditions. MAT LAB and SIMULINK were employed for simulation studies. Simulation results indicate the feasibility and improved functionality of the system. The main objective of this paper is maximizing the PV output power and wind energy system (WES) output power independently by tracking the maximum power on every operating condition by using MPPT technique and interconnected to utility grid.
in Computer

— In this paper we propose and prove a new technique called “Overlapping Slicing” for privacy preservation of high dimensional data. The process of publishing the data in the web, faces many challenges today. The data usually contains the personal information which are personally identifiable to anyone, thus poses the problem of Privacy. Privacy is an important issue in data publishing. Many organizations distribute non-aggregate personal data for research, and they must take steps to ensure that an adversary cannot predict sensitive information pertaining to individuals with high confidence. Recent work in data publishing information, especially for high dimensional data. Bucketization, on the other hand, does not prevent membership disclosure. We propose an overlapping slicing method for handling high into more than one column; we protect privacy by breaking the association of uncorrelated attributes and preserve data utility by preserving the association between highly correlated attributes. This technique releases mo correlations thereby, overlapping slicing preserves better data utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute
Study of Germination behavior of two populations of Centaurea depressa under different temperature and lighting condition

Seyedeh Zohreh Ebadi1*, Farid Golzardi2, Yazdan Vaziritabar3, Yavar Vaziritabar3, Mozhgan Sadat Ebadi4 1Department of Agronomy, Karaj Branch, Islamic Azad University, Karaj, Iran *: Corresponding author Email: Zohreh_29147@yahoo.com 2Young Researchers and Elite Club, Karaj Branch, Islamic Azad University, Karaj, Iran 3Department of Agronomy, Science and Research Branch of Tehran, Islamic Azad University, Tehran, Iran 4Tehran North Branch, Islamic Azad University, Tehran, Iran
A Study of Grammatical Code Switching Among EFL University Students

Code switching is a widely observed but less studied phenomenon, especially in multilingual and multicultural communities. So, the present study investigated the status of grammatical code switching among Iranian EFL university students. Also, the role of the teacher in managing the code switching was investigated, too. Two classes including 96 participants from two different universities were observed carefully and the required data were collected. Analyses of the data revealed varying nature of code switching in both settings. Moreover, the obtained frequencies revealed the fact that among the four types of „trigger words‟ only „proper nouns‟ and discourse marker „OK‟ remarkably were responsible for code switching in one setting, while „lexical transfer‟ and also the discourse marker „OK‟ lead to code switch in another. Meanwhile, four functions for code switching were determined, which included providing equivalents for the key word, showing humor, inspiring learners, and explaining the required assignments, as teacher‟s role in dealing with code switching .
QUALITY OF SERVICE METRICS FOR DATA TRANSMISSION IN MESH TOPOLOGIES

Mesh topologies are important for large-scale highly engineered systems. The Quality of Service (QoS) in such systems is known to decrease as the number of nodes and messages increases. We present a scalable approach for dissemination that exploits all the shortest paths between a pair of nodes and improves the QoS. Despite the presence of multiple shortest paths in a system, we show that these paths cannot be exploited by spreading the messages over the paths in a simple round-robin manner; nodes along one of these paths will always handle more messages than the nodes along the other paths. We characterize the set of shortest paths between a pair of nodes in regular mesh topologies and derive rules, using this characterization, to effectively spread the messages over all the available paths. These rules ensure that all the nodes that are at the same distance from the source handle roughly the same number of messages. By using multipath propagation and demonstrating the transmission results in case of propagation irregularities and link failures the QoS improved with this approach.
Face Image Retrieval Using Attribute Sparse Codeword’s

: Many applications including face verification use face image retrieval method. It’s a challenging technique since all the faces will be similar due to its similar geometrical configuration of face structure. This paper retrieves similar faces using content based method. In earlier stage content based retrieval was performed using low level features such as appearance and posing. But low level features lack to give correct semantic description of images. For an e.g., face of different people is retrieved as similar in low level features. This problem is solved by incorporating low level features with high level human attributes like race, gender, hair etc. Two valuable methods such as attribute enhanced sparse coding and attribute embedded inverted indexing are proposed here to retrieve the image more effectively. These techniques can achieve above 43.5% improvement by comparing with existing techniques.
Identification of Cotton Diseases Based on Cross Information Gain_Deep Forward Neural Network Classifier with PSO Feature Selection

-This work exposes the automatic computation system to analyse the cotton leaf spot diseases. First to initialize the images from the database (Image features) that are highly related to the test image (new image), where test image is given by the user. Three features are used for matching the train image features in database images, namely color feature variance, shape and texture feature variance. These features are extracted by PSO. The feature selection method which helps to identify the injured leaf spot of cotton and at the same time improve the accuracy of the system and reduce the error rate also. These features are calculated by different techniques. The proposed Skew divergence color variance feature is calculated by color histogram and color descriptor. The shape Skew divergence feature is calculated by Sobel and Canny through the find out edge variance, edge location using Edge detection method. The skew divergence texture feature is calculated by Gober filter and texture descriptor. This investigation is based on six types of diseases like Bacterial Blight, Fusarium wilt, Leaf Blight, Root rot, Micro Nutrient, Verticillium wilt. This work utilizes these three features and combined the classifier of proposed Cross Information Gain Deep forward Neural Network (CIGDFNN) which helps to recognize and identify cotton leaf spot diseases. The forceful feature vector set is a combination of three features to obtain the higher accuracy rate and sensitivity, specificity when tested with the cotton leaf dataset.
sing DT-CWT Based Preprocessing Techniques

the main objective of this paper is to improve the image quality by de-noising and resolution enhancement Techniques. The medical image quality parameters are mainly noise and resolution. This paper targets the average, median and wiener filters for image denoising and Discrete Wavelet Transform (DWT) and Dual tree Complex Wavelet Transform (DT-CWT) techniques for resolution enhancement, and it shows the results comparisons between DWT and DT-CWT. The performance of these techniques is evaluated using Peak Signal to Noise Ratio (PSNR). Keywords— Image preprocessing, salt and pepper noise, Discrete Wavelet Transform (DWT) , Stationary Wavelet Transform (SWT), Dual Tree complex Wavelet Transform (DT-CWT) , and Peak Signal to Noise Ratio (PSNR).
Predicting Academic Cheating Among the Fifth Grade Students: The Role of Self-Efficacy and Academic Self-Handicapping

The main purpose of this study was to predict academic cheating, based on some personal factors (self-efficacy and self-handicapping strategies). 477 students from fifth grade were selected by random cluster sampling method. To measure the research variables, were used the three sub-scales of Patterns of Adaptive Learning Scale (Midgley et al, 1997). Data were analyzed using descriptive statistics, Pearson correlation, analysis of variance and multiple regression analysis by using software SPSS17. Findings showed that there is significant difference (P<0.01) between the mean scores of male and female students in self-handicapping strategies and selfefficacy. While, between male and female students were not found significant differences in terms of cheating. Also, with the 2tailed test, at 99% confidence level (P<0.01) was found a significant inverse relationship between academic self-efficacy score and cheating score (r= 0.28), also, was found a significant positive relationship between self-handicapping strategies scores and cheating score(r= 0.29). Finally, using multiple regression analysis revealed that between the two variables, the self-handicapping strategies were the best predictor of academic cheating. Findings and implications for use in educational environments have been discussed.
Magical Thinking and Obsessional Experiences: Mediator Role of Thought Control Strategies -

Research has shown that magical thinking is a critical variable in Obsessive Compulsive (OC) symptoms, as well as in some related cognitions. On the other hand, a number of thought control strategies to address unwanted thoughts have been found to have paradoxical roles in these symptoms, and there is no empirical study investigated the role of these strategies in magical thinking towards OC symptoms. Accordingly, the aim of this study is to explore the association between some specific and maladaptive thought control methods (i.e., worry, punishment and suppression) and magical thinking for obsessional experiences, after controlling for negative affect. A community sample of 496 people completed a self-report measures of their paranormal beliefs, thought control, thought suppression, and symptoms of depression, anxiety and OC in 2015. The results of the correlation analysis indicated a positive association between magical thinking, punishment and suppression, as well as symptoms of OC, depression and general anxiety; after general negative affect was partialled out, these relationships still maintained. Furthermore, a series of hierarchical regression and bootstrapping analyses revealed that paranormal beliefs specifically trigger these two control methods, which in turn contribute to the emergence of symptoms of OC. The findings of the current study seem to concur with cognitive accounts and research and support the paradoxical roles of some control strategies, namely punishment and suppression, in cases with obsessional experiences. Thus, community should be informed about nature of intrusions, the impacts of magical thinking and these thought control strategies.
ADOLESCENTES EM HEMODIÁLISE: REPERCUSSÕES DO ADOECIMENTO E TRATAMENTO NA SAÚDE MENTAL

The research aimed at analyzing the impact of the disease and treatment in the mental health of adolescents on hemodialysis. This is a clinical qualitative study carried out in a dialysis clinic of the city of Fortaleza/Ceara from february to april 2013. Data were used as instruments of production to semi structured interviews and nonparticipant observation. The participants were eight teenagers diagnosed with chronic renal failure undergoing 1434 Ramos IC, Braga VAB, Cavalcante LP, Oliveira FJG Cienc Cuid Saude 2015 Out/Dez; 14(4):1427-1435 dialysis selected by intentional sampling. The analysis of thematic content of Bardin was used. As a result of the interviews, taking the corpus, two categories emerged; 1 Perception of chronic renal hemodialysis teen about the c\ondition experienced: feelings and expectations and 2 Impact of hemodialysis on lifestyle and mental health of adolescents. The results show that, among the study participants, mental health is affected intensively because in includes a constant struggle to overcome the changes caused by the disease and the need to learn to deal with feelings that cause discomfort. It is conclude that the illness and particularly the hemodialysis affects the mental health, but it can be minimized by the provision of a humanized and comprehensive care.
Feature Selection for Post Processing In High Dimensional Data

: Feature selection has been an active research area in pattern recognition, statistics and data mining community. Idea behind feature selection is to choose a subset of input variables by 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.
Content based Image Retrival

In this paper, we propose a content-based image retrieval system which takes into account the local attributes of the image for defining the feature space. This method presents a way to localize the characteristics of the queries by partitioning the image into a rectangular grid and applying a different feature vector to each region in the similar measuring phase. The assignment map specifying the feature space for each image region is implicitly selected by the user, through the system interface, according to perception of the content. This is the most important aspect of the system, which provides flexibility to the user to query at the object level by selecting the “type” of the regions. User only intervention to the system is at this phase, but the way of preparing the query, directs the system‟s similarity calculation in the later stages. The experiments indicate that the proposed system yields better results for images having distinctive objects compared to global systems using the same features for the entire image.