Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Handling of Data Using Parallelized Incremental Approach

— Map reduce is one among the necessary functionality of Hadoop tool kit which enables the users to evaluate the large volume of data at run time. Handling large volume of data with less computational cost is the important features of map reduce frame work. In previous system, incremental map reduce was introduced which focus to eliminate the computation cost of users by using already processed input data for the new computation instead of re-computing from scratch. KV pair level is used, in which the input data that might affects the output would be processed. However, this works lacks in reducing the computational cost in the data set which is collected from various sources with different characteristics. To address this limitation, Parallelized incremental clustering is introduced which can process the data that are gathered from multiple sources in run time by using online aggregation. The proposed system is used to support large volume of data in run time further reducing time complexity.
Int J Pharmacogn Chinese Med 2018, 2(2): 000132

Background: The widespread use of herbal medicine has led to its approval by World Health Organization (WHO) as a factor in the attainment of universal health care coverage together with conventional medicine. However, unlike conventional medicine, herbal medicine has many challenges yet to be addressed. Pathogenic microbial contamination has been cited as a serious quality issue in previous studies done in Kenya and other countries with no regulation of herbal medicines. Despite newer techniques of microbial analysis taking shape in routine microbial identification and characterization, quality control laboratories use pharmacopoeal techniques to address the same microorganisms without due regard to possible newer contaminants which may not be detected by the traditional routinely used
Pharmaceutical and phytochemical evaluation of a novel anti – white spot syndrome virus drug derived from terrestrial plants

White spot syndrome virus (WSSV), the most contagious pathogen of cultured shrimp, causes mass mortality, leading to huge economic loss to the shrimp industry. The lack of effective therapeutic or prophylactic measures has aggravated the situation, necessitating the development of antiviral drugs. With this objective, the antiviral activity of the drug, (TP22C derived from the terrestrial plant) in the host, Litopenaeus vannamei was evaluated. The phytochemical and pharmaceutical characterization of TP22C was carried out. The in vivo anlysis of TP22C in the host – pathogen interaction model revealed the efficiency of the drug. The survival percentage of the treated (with TP22C) WSSV infected host was 86 %. Neither the VP 28 gene nor the immediate early genes (ie) were expressed in the host at the 42 nd and 84 th hrs. Significant results were obtained from the toxicity assays of the drug in shrimp model. The phytochemical screening, biochemical constituents assay, elemental analysis, antioxidant property evaluation and phytochemical fingerprint profiling predicts that TP22C can protect L. vannamei from the WSSV infection, at a dose far below the toxicity level. © 2013 Universal Research Publications. All rights reserved
LOW POWER HIGH-PERFORMANCE NON-BINARY LOW-DENSITY PARITY CHECK CODER (FNB-LDPC) OVER GF (2 m ) USING CHECK-NODE UNIT,

An error correction codes are one of important part in channel coding to enhance the performance of communication system. Recently, low-density parity check (LDPC) codes used as the same purpose but hardware design require large resources, which limits the performance of coders. This paper presents a low power, high-performance non-binary LDPC coder (FNB-LDPC) over Galois fields   m GF 2 . The hardware realization of check-node unit (CNU) is a challenging part because it consists of big modules such as FFT/IFFT and multiplier. We overcome these problems by modified CNU structure. The proposed versatile induced flexible LDPC coder supports all field size of suggested Galois fields without the necessity to reconfigure the hardware structure to increase the performance in terms of hardware utilization, power, and delay.
Executive Function Is Related to the Urinary Urgency in Non-demented Patients With Parkinson’s Disease

Introduction: Evidence suggests urinary urgency is associated with cognitive impairment in a subtype of Parkinson’s disease (PD) patients. This study investigates if cognitive impairment independently predicts the presence of urinary dysfunction. Methods: We report data of 189 idiopathic PD patients, excluding those with concomitant diseases or medication interacting with bladder function. A standardized questionnaire was used to define the presence of urinary urgency. All patients underwent a comprehensive motor, cognitive non-motor and health-related quality of life (HRQoL) assessment. Multivariable linear regression analysis was performed to identify independent variables characterizing urinary urgency in PD (PD-UU), which were assigned as discriminant features to estimate their individual contribution to the phenotype of the PD-UU group. Results: Of 189 PD patients, 115 (60.8%) reported PD-UU. The linear regression analysis showed that among cognitive domains, executive function (EF; p = 0.04) had a significant negative association with PD-UU. In a second model, scores of the Montreal Cognitive Assessment (MoCA) significantly differentiated between study groups (p = 0.007) and also non-motor symptom (NMS) burden (p < 0.001). The third model consisted of reports of HRQoL, of which stigma was the only subscale of the Parkinson’s Disease Questionnaire (PDQ-39) differentiating between patients with and without PD-UU (p = 0.02). The linear discriminant analysis provided evidence that the combination of EF, NMS burden, nocturia, and stigma discriminated between groups with 72.4% accuracy. Conclusion: In our large, non-demented PD cohort, urinary urgency was associated with executive dysfunction (EF), supporting a possible causative link between both symptoms. A combination of neuropsychological and non-motor aspects identified patients with PD-UU with high discriminative accuracy.
Review Paper on Identification of Plant Diseases Using Image Processing Technique

— This paper contains the survey of various image processing techniques to detect various plant diseases using machine learning. Now a day’s image processing technique is becoming a key technique for diagnosing the various features of the crop. The diseases can affect any part or area of the crop. This paper mainly focuses detection of various cotton crop diseases and to classify them. There are so many classification techniques such as k-Nearest Neighbor classifier , k-means Classifier, Probabilistic Neural Network, Genetic Algorithm, Support Vector Machine, and Principal Component Analysis, Artificial neural network, Fuzzy logic. Selecting a classification method is always a difficult task because the quality of result can vary for different input data. This paper provides an overview of different classification techniques used for plant leaf disease classification.
One Way Functions –Conjecture, Status, Applications and Future Research Scope

The conjecture that one way function exists is an open problem, the resolution of which holds the key for the solution of many unsolved problems in mathematics and cryptography. This paper presents the introduction of one way functions from complexity & modern cryptography theory viewpoint and their significance in cryptographic applications and research. This paper presents the features and limitations of proposed candidate functions, and the implications of proof of one way functions conjecture.
Effects of vascular nitric oxide bioactivity and vascular ageing on arterial blood pressure and flow waveforms

Analysis of blood pressure and flow waveforms may lead to improved diagnosis of arterial dysfunction and disease. This thesis describes experiments to investigate the characteristic alteration of peripheral waveforms produced by stimulated release of vascular nitric oxide (an effect that is attenuated by endothelial dysfunction) and the changes that occur with age. In vivo experiments were conducted in anaesthetised rabbits and in vitro experiments employed a polyurethane model of the human aorta and its principal branches. Blood pressure, blood flow, pulse wave velocities and vessel diameter were recorded in the rabbit abdominal aorta. Equivalent recordings were obtained from the model aorta. Data were analysed in the time domain using wave intensity analysis after separation of reservoir (Windkessel) pressure and wave pressure. Effects of acetylcholine (Ach) and N-nitro-L-arginine methyl ester (L-NAME) were investigated in vivo. Ach (which promotes endothelial production of nitric oxide) increased wave reflection, whilst L-NAME (which inhibits nitric oxide production) decreased it. These trends were opposite to the expected ones, and do not account for the established effects of nitric oxide on peripheral arterial waveforms. Further work is required to investigate these contradictions. Arterial stiffening in immature and mature rabbits was attempted by supplementing their diet with fructose. Fructose is known to form advanced glycation end-products in arterial walls and hence to stiffen arteries. Unexpectedly, fructose did not affect haemodynamic function. However, immature control rabbits had markedly reduced aortic wave reflection compared to mature control rabbits, indicating that the former have arterial impedances that are better matched for incident wave propagation. Wrapping the model aorta in Clingfilm was used to simulate ageor drug-induced stiffening of the aorta in vivo. Increased pulse pressure was observed, resembling the isolated systolic hypertension prevalent in aged populations. The model has potential for modelling haemodynamic function in health and disease.
SAHS Detection Based on ANFIS Using Single Channel Airflow Signal

The aim of this paper is to present an efficient and accurate detection algorithm for Sleep ApneaHypopnea syndrome (SAHS) based on the single-channel airflow (AF) signal. SAHS is a sleep disorder which happens due to the infrequent breathing during sleep or pauses in breathing. Studies show that 80% of patients remain undiagnosed and untreated, which could lead to stroke, heart attack, hypertension or depression. The nasal airflow signals extracted from polysomnography recordings are obtained from PhysioNet apnea–ECG database. The features of the signals are extracted using wavelet transform method. To derive an optimum set of features with minimum redundancy, a mutual information based feature selection method is applied. The features obtained from 8 recordings are used for classification of SAHS by using two classifiers such as AdaBoost (AB) and adaptive neuro fuzzy inference system (ANFIS). Training and testing process have been repeated by using randomly obtained six sequences of whole data. According to the results, the classification accuracies have been obtained as 98.43% and 98.68% respectively. Therefore ANFIS based classification has increased degree of accuracy hen compared to AdaBoost. As well as the use of single channel input makes the real time SAHS detection easier and less complex. So this method can be a valuable solution for saving undiagnosed SAHS patients without disrupting their daily life activities.
Phase Transition Method: A Novel Technique for Mouth dissolving tablet

The aim of the present study was to assess the properties of Mouth dissolving (MD) tablets manufactured by the phase transition method. MD tablets were produced by compressing powder containing LMP-SA (Low melting point sugar) and HMP-SA (High melting point sugar), and then heating at about 93C for 15 min. The hardness and oral disintegration time of the heated tablets increased with an increase of the LMP-SA content. These results suggested that the heating process and LMP-SA content might influence the properties of MD tablets. Then we evaluated the physicochemical properties of the MD tablets, including the median pore size, crystallinity, hardness, and oral disintegration time of tablets made with and without heating. After heating,the median pore size of the tablets was increased and tablet hardness was also increased. The increase of tablet hardness with heating and storage did not depend on the crystal state of the lower melting point sugar alcohol. It is concluded that a combination of low and high melting point sugar alcohols, as well as a phase transition in the manufacturing process, are important for making MD tablets without any special apparatus.
The Long-Run Dynamic Relationship between Broad Money Supply and the GDP of Bangladesh: A VECM Approach

After commencing the cash economy money appeared as an engine of economic growth. The endeavor has given in this study to uncover out the underlying relationship between broad money supply (M 2 ) and GDP of Bangladesh and ascertain the influence of M 2 on GDP in selected study period. The Johansen Cointegretion test signifies that broad money supply and GDP are close-fitting and moving together in the long run. After fitting the Vector Error Correction Model it is discerned that there is an establishment of long run association between M 2 supply and GDP. The parameters of this model demonstrate that causality is running from broad money supply to GDP, meaning that M 2 manipulates the GDP enduringly. It is originated in the post estimation specification tests that there is no auto-correlation at lag order and residuals are normally distributed. Keywords: Money Supply, GDP, VECM, Forecasting, Impulse Response Function
A Mechanism for Monitoring Database Access Patterns for Anomaly Detection

: Anomaly detection is a critical issue that has been investigated inside various research zones and application areas. Numerous anomaly detection strategies have been particularly produced for certain application spaces, while others are more nonexclusive. This study attempts to give an organized and far reaching outline of the examination on anomaly detection. We have assembled existing methods into various classifications dependent on the fundamental methodology received by every procedure. For every classification we have distinguished key suppositions, which are utilized by the systems to separate among ordinary and odd conduct. While applying an offered procedure to a specific area, these suspicions can be utilized as rules to evaluate the adequacy of the strategy in that space. For every class, we give an essential anomaly detection method, and afterward indicate how the diverse existing procedures in that classification are variations of the fundamental strategy. This format gives a simpler and brief comprehension of the strategies having a place with every class. Further, for each category, we have a tendency to distinguish the focal points and hindrances of the strategies in this classification. we have a tendency to likewise offer an exchange on the machine many-sided nature of the procedures since it's an important issue in real application areas. we have a tendency to trust that this review can provides a superior comprehension of the distinctive headings within which cross-check has been done on this subject, and the way procedures created in one territory will be connected in areas that they weren't planned in any case.
A Distinct Approach to Vein Pattern Recognition An Effective Design for Secure Systems in Developing Nations

Biometric-based identification has steadily gained immense popularity as the need for perfectly secure systems has become a top priority issue these days. Among biometric identifications such as fingerprint, vein pattern, iris, voice, face recognitions, vein pattern recognition stands out as it provides excellent security and further researches are still being conducted to improve the system. This paper introduces the skeleton of a vein pattern recognition system that we have designed using Verilog HDL (Hardware Description Language) keeping FPGA (Field Programmable Gate Array) implementation in mind. Developing nations can greatly benefit from using FPGA-based security systems as FPGAs are reconfigurable, faster but consume lower power and are thus more cost-effective than general purpose processors. We have used slightly modified existing algorithms to program most parts of our system. Our vein pattern recognition system ensures a far simpler but effective pattern extraction using Verilog HDL . Keywords—Vein pattern; Verilog HDL; FPGA
Performance Evaluation of Spectrum Sensing and Channel Access in Cognitive Radio Networks

— Spectrum sensing is an essential functionality of cognitive radio networks. In the existing Cognitive Radio spectrum detection techniques secondary nodes base their channel access decisions solely on the outcome of the spectrum sensor without taking into consideration the possibility that those outcomes are incorrect. To alleviate these negative effects a combined design is proposed for the secondary nodes to have better channel access where the spectrum sensor outcome and reliability measure of spectrum sensor decisions are considered. Simulation for characterizing the detrimental effects of spectrum sensor errors and effectiveness of combined design is done using binary hypothesis condition. Results show considerable increase in secondary access probabilities which eventually increases the throughput and decreases the delay of both primary and secondary networks.
Improving Digital Image Forgery Detection Using MIFT Features and Adaptive Over Segmentation

- A novel copy–move forgery detection method using adaptive over segmentation and feature point matching is proposed in this paper. The proposed method integrates both block-based and key point-based forgery detection methods. First, the adaptive over segmentation algorithm divides the host image into non-overlapping and irregular blocks adaptively. Then the features points are extracted using SIFT and matched with each other to locate the labeled feature points which can almost show the suspected forgery regions. To find the forgery regions more precisely, we propose the forgery region extraction algorithm, which substitutes the feature points with small super pixels as feature blocks and then merges the adjacent blocks that have similar local color features into the feature blocks to generate the merged regions. Finally, this method applies the morphological operation into the merged regions to generate the detected forgery regions. In this paper, our importance is on improving the detection and localization of duplicated regions using more powerful keypoint-based features. In this context, we have also adopted a more powerful set of keypoint-based features, called MIFT, it shares the properties of SIFT features but also are invariant to mirror reflection transformations. Experimental results show the good performance of the proposed copy-move forgery detection.
DESIGN OF A LOW POWER LOW VOLTAGE FULL ADDER

: In this paper, 1 bit full adder is built under a new hybrid logic (combination of PTL and CMOS logic) style, using 14 MOSFETs. Here we use 6transistor XOR-XNOR circuit to implement the full adder. This full adder offers full voltage swing at every nodes, higher density and high speed than the conventional CMOS design style. TSPICE is the simulator used for the simulation and bsim3v32 technology is used with supply voltage=1V and 10MHz frequency. Dual threshold model file (version 49) is used to observe the o1utput.
EXPLOSIVES DETECTION PERFORMANCE OF -RAYS INTERROGATION FOR ROBOTS AND VEHICLES

The performance of a explosives detection system based on the pulsed fast/thermal neutron analysis technique was assessed using Monte Carlo simulations. The aim was to develop and implement simulation methods, to support and advance the data analysis techniques of the characteristic -ray spectra, potentially leading to elemental characterization of innocuous objects using the full spectrum analysis (FSA) approach. Several different neutron based techniques are being studied for the detection of contraband substances in luggage and cargo containers. The pulsed neutron generator is easy to transport and radiation protection is only needed during analysis time. This paper discusses accelerator requirements for fast neutron transmission spectroscopy (FNTS), pulsed fast neutron analysis (PFNA), pulsed thermal neutron analysis (PTNA), fast neutron scattering analysis (FNSA), delayed fission analysis (DFA).
Noise Reduction from Ultrasound Medical Images using Rotated Wavelet Filters

Noise is an unwanted signal, which affect the images and degrade its quality. Different images suffers from different types of noises whose effect can be minimize or rather these noises can be remove by using certain transforms or using certain spatial domain filters. However, use of the spatial domain filters leads to loss of some useful information from the images. In this paper, we proposed a transform domain denoising technique. We have used rotated wavelet filters to improve the denoising results. We are mainly focusing on the additional directional information, which we are getting by the use of rotated wavelet filters. We have compared the results obtained using rotated wavelet filters with existing methods and results obtained with our method are found very exciting. SSIM and PSNR used as quality measures to compare denoised and original noisy images.
Cloud Data Center's Resource Provisioning With Secured Mining In Distributed Mechanism

: Data center have the largest consumption amounts of energy in power sharing. The public cloud workloads contain different priorities and performance requirements of various applications [4] . Cloud data center have capable of sensing an opportunity to present the different programs. The proposed construction and the security level of self-possessed privacy leakage rarely distributed cloud system to deal with the persistent characteristics there is a substantial increases and information that can be used to an enhance the profit, downsizing overhead or both. The mining process of data analysis from different perspectives and summarize it into useful information. Three demonstrable algorithms have been proposed task evaluate the ratios are dissected theoretically and compared using real Internet latency data recital of testing methods.
COMPARISON OF SINGULAR VALUE DECOMPOSITION, PRINCIPLE COMPONENT ANALYSIS, INDEPENDENT COMPONENT ANALYSIS FOR AN IMAGE

It is well known that the images, often used in variety of computer applications, are difficult to store and transmit. One possible solution to overcome this problem is to use a data compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. Image compression is achieved by using Singular Value Decomposition (SVD) technique on the image matrix. PCA has been widely applied in the area of image compression in various forms. PCA has been applied as standalone image compression technique as well as pre-processing or post-processing step in combination To apply ICA to images, each sample of X usually contains the pixels in an image block. Independent component analysis (ICA) considers a class of probabilistic generative models in which a random vector X is obtained according to X = AS, where A is an NXM unknown mixing matrix and S is a vector of independent sources. The comparative study is conducted with the help of Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), compression ratio.