Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Characteristics of a Two-level VSC with a Third-Harmonic Injection Bus-clamping SVM– Detailed Study

At present, power electronics-based technologies are widely penetrating the power systems in an effort towards “smart-oriented” operational systems. Voltage-sourced converters (VSCs) are such power electronics-based technologies that currently seem rather to preponderate in many promising applications including FACTs, HVDC grids, DGs and VSDs. VSCs are found in a plethora of structures ranging from a simple half-bridge to an advanced modular topology and in order to exploit all their possible inherent features, a number of modulation strategies have been established. This paper investigates holistically the 3Φ two-level VSC with a 3 rd harmonic injection bus-clamping space-vector modulation. It is essentially envisioned to further [7]-[8] studies, which compare two common VSC topologies, by including the abovementioned bus-clamping topology. The modulation strategy implemented through the principle of the equivalence linear trianglecomparison-based PWM with a bus-clamping SVM, mainly the MAX and MIN bus-clamping schemes. The resultant asynchronised SV-PWM has been investigated with a passive RL load and an active asynchronous vector-controlled motor with the aid of Simulink® simulated models. Index Words: Voltage Sourced Converter (VSC), SVPWM, Bus-clamping control strategy, THD%, Induction motor
Chronic Myeloid Leukemia in India: A Review

Chronic myeloid leukemia (CML) is a clonal myeloproliferative disorder of a pluripotent stem cell. CML is the commonest adult leukaemia in India and the annual incidence ranges from 0.8–2.2/100,000 population in males and 0.6–1.6/100,000 population in females in India. The median age of diagnosis is 38-40 years. Chronic myeloid leukemia is divided into three phases based on clinical characteristics and laboratory findings. CML prognostic scoring systems stratify patients into risk groups based on patient and disease related characteristics at diagnosis . With the introduction of the Tyrosine Kinase Inhibitor, imatinib, the treatment and natural history of CML has changed dramatically in recent years, with an improvement in the 5-year survival rate from little more than 20% to over 90%. This article presents a brief review about chronic myeloid leukemia and its therapy.
Effect of Toxicity of Hyoscyamus niger leaf extract on Heteropneustes fossilis (Cat Fish)

Ninety Six hours of toxicity test was conducted to observe the lethal concentration (LC50) value of Hyoscyamus niger leaf extract on Heteropneustes fossilis. The fishes were exposed to seven different concentrations of the extract (20 mg 1, 40 mg 1, 50 mg 1, 60 mg 1, 70 mg 1 and 80 mg 1) for toxicity test and one remained as control. The LC50 value of H. niger in H. fossilis was found to be 50 mg 1 for 96 hours exposure periods. Analysis of variance for the effect of the extract on the percentage mortality of fish showed a significant relation between both the factors (p<0.05, F=13.42). The correlation coefficient between concentration and mortality of fish was calculated (R = 0.714) and showed a strong positive correlation between different concentrations of the leaf extract and mortality percentage of fish. The present finding established that H. niger has potential toxic effect on fish and could be use widely to control undesirable fishes.
A n E n h a n c e d A p p r o a ch t ow a r d s Detection of Malicious PDF Files

: Malicious PDF files are of grave concern as they pose a serious threat to system security in terms of confidentiality, integrity and availability. Social engineering techniques are generally preferred by the attackers to prompt users for accessing malicious PDF files. The available antivirus mostly lags a step behind the attackers and fails to detect such files. In this paper, a Machine-learning model based framework has been proposed through segregating the features for classification to detect malicious PDF files. The features, which are used to create malicious PDF files, are identified and a model is built based on these features to classify the PDF files as Benign or Malicious.
Endosulfan Induced Male Reproductive changes and their Treatment with Withania somnifera

Available online on http://www.ijlsci. in ISSN: 2320-964X (Online) ISSN: 2320-7817 (Print) The ameliorating effect of Withania somnifera was evaluated against changes in sperm profile of mice. The animals received Endosulfan (Pesticide) once daily for 35 days at the dose of 3 mg/kg body wt by oral gavage method and observed toxic effect such as of reduction in the number of sperm and sperm motility which signify the testicular dysfunctions and finally causes infertility. To ameliorate the toxic effect made by endosulfan, Withania somnifera (Ashwagandh) was administered to mice along with its food @ 150 mg/kg body wt. The potent medicinal power like antioxidant, anti-stress, antiinflammatory, anti-aging, aphrodisiac, astringent, deobstruent, diuretic, narcotic, sedative, anti-tumor and anti-ulcerogenic activities in the root extract of Withania somnifera alleviate the fluctuation in sperm count and sperm motility which was decreased by pesticide treatment.
Performance Evaluation of Spectrum Sensing Methods for Cognitive Radio

Spectrum is an important asset in communication. Efficient spectrum utilization is of major concern for the wireless communication networks in the future. The allocated spectrum is scarce and has been challenging the unlicensed wireless users. An ingenious technology, cognitive radio, has been proposed which is proving to be an answer to this situation. Spectrum Sensing is the building block in cognitive radio. It helps the unlicensed users to access the licensed spectrum, thus increasing the spectrum utilization and efficiency. In this paper, two of the most practiced spectrum sensing methods, namely Matched filter detection and Energy detection, have been compared on the basis of their performances. The performance evaluation of these two methods is done by using different parameters.
A HYBRID NAMED ENTITY RECOGNITION SYSTEM USING NATURAL LANGUAGE PROCESSING AND DECISION TREE LEARNING

: Named Entity Recognition is classified as a subfield of Information Extraction and it is the core of Natural Language Processing (NLP) system. It helps machine to recognize proper nouns in text and associates it with appropriate types like person, location and organization, date and time, mentions of monetary amounts and percentages. This recognition of proper nouns and their extraction is significant in research areas like Information Retrieval, Machine Translation, Answering and Summarization Systems, Video Annotation, Semantic Web Search and Bioinformatics, Terrorism Event Extraction . Various approaches can be used for NER like Rule Based NER, Machine Learning Based NER and Hybrid NER. In this paper we propose a hybrid method using linguistic rules of natural language processing and supervised machine learning technique.
Characterization and Clinical Applications of Amniotic Membranes

Figure 1: Diagram of the amnion and chorion layers of the placental membrane. The amnion is a thin, avascular membrane, with a thickness of about 35-60 microns [2], and it is comprised of three major structures: the amniotic epithelium (i.e. epithelial layer), the basement membrane, and the avascular stroma (i.e. stromal layer, mesenchymal layer). See Figure 1 for a rendering of the amnion and chorion layers of the placental membranes and their constituent parts. The epithelial layer of the amnion is directly in contact with the amniotic fluid and nearest to the developing fetus. It is comprised of a single layer of simple cuboidal epithelial cells (i.e. human amniotic epithelial cells, or hAECs), which exhibit pluripotent stem cell-like characteristics [1].
CORDIC Based DCT for an Efficient Reconfigurable Architecture

ABSTARCT: The demand for low power implementations of complex signal processing algorithms is increasing. For this purpose, Co-Ordinate Rotate Digital Computer (CORDIC) based 2-Dimensional Discrete Cosine Transform (2-D DCT) is used. In DCT all the computations are not equally important in generating the frequency domain outputs, by considering the importance difference in the DCT coefficients, the number of CORDIC iterations can be dynamically changed to efficiently balance the image quality and for low power consumption. Thus, the computational energy can be reduced without seriously compromising the image quality. The 2-D DCT process is decomposed into an 1-D DCT (row DCT) followed by another 1-D DCT (column DCT). The conventional CORDIC algorithm is designed to calculate cosine functions for the given angle and it is implemented in the reconfigurable architecture. The unique feature of this reconfigurable architecture is that it could be configured for the computation of a 32-point DCT or for parallel computation of two 16-point DCTs or four 8-point DCTs with a marginal control overhead. The reconfigurable architecture using CORDIC based 2D DCT can be constructed using HDL and the reconfigurable architecture is found to offer many advantages in terms of hardware complexity, regularity and modularity.
Advanced Modified BPANN Based Unsymmetric Trimmed Median Filter to Remove Impulse Noise

— Removing or reducing impulse noise is a very active research area in image processing. Removing Salt and Pepper noise is considered to be very important in the domain of image restoration, but it is a somewhat more challenging topic than removing pure noise. Therefore, relatively fewer works have been published in this area. In this paper the BPANN based novel approach has been presented for removal of salt and pepper noise from the high density salt & pepper noisy images, using Advanced Modified Back Propagation Artificial Neural network based Unsymmetric Trimmed Median Filter. The existing MDBUTMF is unable to restore the original image from the noisy one if noise density is more than 70%. The performance of the proposed method is analyzed by using various qualities of metrics, such as Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR). Simulation results clearly show that the proposed method performs better both in qualitative as well quantitative fidelity criteria, when it is compared with MDBUTMF.
DETERMINANTS OF USE OF ELECTRONIC WALLET SCHEME BY FARMERS IN IMO STATE, NIGERIA

The study investigated determinants of use of e-wallet scheme among farmers in Imo State, Nigeria. It specifically identified the farmers’ sources of information on e-wallet, determined the inputs supplied through e-wallet, ascertained the farmers’ perceived effects of e-wallet and determined constraints to the use of e-wallet. Data were collected from a sample of 240 farmers with the aid of structure questionnaire and were analyzed using mean statistic, percentages and bar chart. The hypothesis was tested using ordinary least square regression analysis. Results showed that radio (100%), mobile phones (100%) and newspapers (66.7%) were the major sources of information on e-wallet; inputs supplied through e-wallet included fertilizers (X = 2.9), maize seeds (X = 2.5), cassava cuttings (X = 2.3), fingerlings (X = 2.1) and agrochemicals (X = 2.0); perceived effects of use of e-wallet included increased income (90.00%), exposure to more agricultural enterprises (85.00%), increase productivity (85.42%) and timely access to inputs (64.56%). It was further revealed that high cost of inputs (89.58%), poor transportation network (87.50%) and bureaucratic bottlenecks were the major constraints facing the scheme. It was recommended that innovative strategies for financing agricultural projects be introduced so that farmers could afford required quantities of inputs. Also, the input distribution system should be decentralized to reduce bureaucratic bottlenecks.
Mining Frequent Itemsets Using Apriori Algorithm

- Mining required data from voluminous Data has been recognized as one of the most challenging problems in data mining approach. In many real world scenarios, the data is not extracted from single data source but from distributed and heterogeneous data sources. The discovered knowledge is expected comprehensive so that it can better fit in business environment Enterprise data mining applications involve dealing with complex data such as data from multiple heterogeneous data sources, extracting data in single step from such data sources such data sources is time and space consuming. So effective approaches are needed to decrease the time as well as space. Here we use Apriori Algorithm for discovering informative patterns in complex data sets.
THE MEDIATING ROLE OF SCHOOL CLIMATE ON THE RELATIONSHIP BETWEEN COGNITIVE EMOTIONAL REGULATION AND CLASSROOM DISPOSITION OF RETIRABLE PUBLIC SCHOOL TEACHERS

This study aimed to investigate the mediating effect of school climate on the relationship between cognitive emotional regulation and classroom disposition of teachers among the 400 teachers in Davao Region. This study employed non-experimental design utilizing descriptive correlation technique. The statistical tools used were mean, pearson-r, regression technique, and medgraph using Sobel z-test. Research instruments on school climate, cognitive emotional regulation of teachers, and classroom disposition of retirable public school teachers which were validated were used as sources of data. Using pearson-r, the results revealed that there is a significant relationship between school climate and cognitive emotional regulation, there is a significant relationship between school climate and classroom disposition of public school teachers, and there is a significant relationship between cognitive emotional regulation and classroom disposition of public school teachers. Utilizing megradph Sobel z-test, the results of the study also suggest that there is also a partial mediation on the effect of school climate on the relationship between cognitive emotional regulation and classroom disposition of public school teachers.
Virulence Diversity of Leishmania Tropica Strains Isolated from Human Lesions in Syria

Virulence variability was investigated by analyzing the experimental pathogenicity of seven Leishmania tropica strains isolated from human lesions in Syria, through the evaluation of the infective ability, growth pattern and pathogenicity. Two of the strains presented higher levels of macrophage infection, increased promastigote replication in culture medium and as well as amastigote multiplication within macrophages were classified as the most virulent. The other strains exhibited either low virulence, with reduced infective capability and low replication levels, or an intermediate virulent phenotype showing mixed features similar to low and high virulent phenotypes. A correlation between the infectivity and growth dynamics of each strain and NO production was demonstrated. Strains with accentuated virulent phenotype induced lower levels of NO production and parasite killing. These results suggest that L. tropica isolates from human lesions may differ in Virulence phenotype which seems to be a characteristic of each strain.
Review on Uro-Lithiasis Pathophysiology and Aesculapian Discussion

Nephroliths are a common trouble worldwide with substantial morbidities and economic costs. This review describes focusing on update about the Pathogenesis formation of renal stone epidemiology. The most common adventure factors or aesculapian conditions associated with formation of renal stone, the current methods available for metabolic probe, dietary recommendations and medical treatment. Over the past 10 years, major progress has been made in the pathogenesis of renal stone. The incidence of nephrolithiasis (kidney stones) is rising worldwide, particularly in adult female and with rising age. Preventing recurrence is predominately specific to the character of stone (e.g., calcium oxalate, calcium phosphate, cystine, and struvite and uric acid stones); however, even when the stone cannot be retrieved, Managing diet, medication use, and food consumption can help prevent the organisation of kidney stones.
Exfoliated Graphite/Tungsten Trioxide Nanocomposite Electrode for the Photoelectrochemical Degradation of Eosin Yellow and Methylene Blue in Wastewater

The exfoliated graphite /tungsten-trioxide (EG-WO3) was prepared by incorporating WO3 into EG by wet solution method. The materials were characterized using Scanning Electron Microscopy (SEM), Thermogravimetry, Differential Thermal Analysis (TGA), Brunauer-Emmett-Teller surface area analysis (BET), Infrared (IR) spectroscopy and X-ray Diffraction (XRD). These techniques confirmed the synthesis of EG-WO3 nanocomposite. The EG-WO3 was fabricated into a photoanode and applied to the photoelectrochemical degradation of eosin yellow dye as a model for organic pollutants in water at a current density of 7.2 mA cm -2 with Na2SO4 as supporting electrolyte. Was studied as a model material by photocatalytic and photoelectrochemical methods in order to evaluate the photoactivity of EG-WO3 materials and the possibility of their applications in solar simulator photocatalysis. With the EG-WO3 photoanode showed a significant decrease in the dye concentration (20 ppm). This shows that the WO3 nanoparticle in the EG-WO3 composite enhanced the degradation efficiency of the eosin yellow. Thus, the EG-WO3 electrode is applicable for the photoelectrochemical oxidation of organic pollutants, specifically in synthetic dyes in water. O. M Ama
Optimal Adsorption Parameters of Banana (Musa paradisiaca) Stalk based Activated Carbon for removal of Lead (II) from Aqueous Solution

The present study investigated the effect of operating parameters on the adsorption process of lead ion from aqueous solution using Banana Stalkbased Activated Carbon (BSAC). A five factor, five levels Central Composite Design (CCD) was applied to determine the effects of five independent variables (initial metal concentration, contact time, temperature, adsorbent dosage and solution pH) on adsorption capacity of BSAC. Response Surface Methodology (RSM) was employed to optimize the parameters in the experiment. Data analysis showed that all the variables significantly affected the adsorption capacity at p < 0.05. The square of the adjusted coefficient of determination for regression model of adsorption capacity is 0.9577. Optimum adsorption capacity of 85.15mg/g was obtained when the initial metal concentration, contact time, temperature, dosage and solution pH were 200g/mL, 140minutes, 50C, 0.15g and 8.00, respectively. There absolute error between the experimental and the predicted optimum adsorption capacity values was less than 1%.
Investigations of Formant Extraction of Male and Female Speech Signal Via Cepstral De-convolution Method

- The capability of speaking the language is one of the most amazing skills human possess. It serves as a very effective way of communication, sharing experiences, thoughts, ideas among the people. In this research work, cepstral analysis of sentence level speech signals of male and female speakers is carried out. Spectrogram analysis of segmented speech is carried to determine various speech parameters. The Cepstral analysis shows the unique trait between male and female speakers in terms of low time liftered speech processing.
A Survey on Tag Based Image Search Using Various Aspects

Day by day the amount of mobile devices and web services are increasing rapidly and the success of many online social media websites, which allow users to create and share media information such as images and videos as well as describe the media content with tags. Social media sharing websites like “Flickr” allow users to annotate images or pictures with free tags, which significantly support to the development of the web image retrieval and organization. Tag-based image search is an important method to find images contributed by social users in such social websites. However, how to make the top-high ranked result relevant and with diversity is challenging. In this project, we propose a social re-ranking system for tag-based image retrieval with the consideration of image’s relevance and diversity. We focus at re-ranking images according to their visual and semantic information and social clues. The initial results include photos contributed by different social users. Usually each user contributes several images. First we sort out these images by inter-user re-ranking. Users that have higher contribution to the given query rank higher. Then we gradually implement intra-user re-ranking on the ranked user’s image set and only the most relevant image from each user’s image set is selected. These images compose the final retrieved results. We make an inverted index structure for the social image dataset to accelerate the searching process. Experimental results on “Flickr” dataset show that our social re-ranking method is effective and efficient .
An Energy Efficient and Delay Aware Data Collection Protocol in Heterogeneous Wireless Sensor Networks – A Review

-The various researches on open vehicle routing (OVR) problems endeavour that it is based on same assumptions and constraints as that of sensor networks. Thus, it may be feasible to adapt these techniques so that they will provide valuable solutions to certain tricky problems in the wireless sensor network (WSN) domain. To demonstrate that this approach is feasible, one data collection protocol called EDAL, which stands for Energy-efficient Delay-aware Lifetime-balancing data collection, is defined. Therefore, both a centralized heuristic to reduce its computational overhead and a distributed heuristic to make the algorithm scalable for large-scale network operations is defined. The applications in WSN are evolving, so congestion control remains an open and, in several cases, a critical problem. Two general approaches seem to be the most prominent for its solution: traffic control and resource control. A dynamic scheme capable of bridging these two methods for congestion control and provide the best solution
Analysis of Face Recognition using Manhattan Distance Algorithm with Image Segmentation

: Segmentation is one of the important concepts in Face Recognition. Based on the segmentation, the image is to be identified by different algorithms such as Euclidean distance, Manhattan distance, Chebyshev distance and other methods. In this paper, the segmentation concept with Manhattan algorithm to produce the visible image and focus on the exact segmented image with Manhattan distance algorithm. This algorithm compares the given face with a database of faces of ORL2. It recognizes the particular face and then the segmented part of the image to be produced, depends on the users choice. The recognition rate of the image segmentation shows the result accurately with 97% compared with Euclidean distance. It also produces the FAR and FRR of the given image.
REDUCED RATING DYNAMIC VOLTAGE RESTORER WITH ENERGY OPTIMIZED BY USING FUZZY LOGIC CONTROLLER

— In this paper, reduced rating dynamic voltage restorer(DVR) with the fuzzy logic controller is analyzed by using Tolal Harmonic distortions (THDs) . Different voltage injection schemes are used to reduce the rating of voltage source inverter(VSC)used in DVR. The reference load voltage is assessed utilizing the unit vectors. Synchronous reference frame theory is used for transformation of voltages. A battery storage system is used for energy optimization. The problem associated with conventional PI controller is eliminated by the fuzzy logic controller. voltage sag, swell, and harmonics are compensated using a reduced rating DVR. This paper presents the modeling and simulation of DVR using MATLAB/SIMULINK.