Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Reconfigurable Optimal Decimal Multipliers: An Overview

: The realization of Multiplication operation is essential for most of the scientific applications as well as in commercial applications like banking, accounting, financial analysis, tax calculation, currency conversion, and insurance etc. Multiplier is a key building block and almost obligatory component in all such applications. That is why reconfigurable PLDs are equipped with dedicated embedded multipliers. The prerequisite of the multiplier implementation is that it should be primarily fast and secondarily efficient in terms of power consumption and chip area. The multiplication involves two basic operations viz. generation of partial products and their accumulation. To speed up the multiplication process, one can reduce the number of partial products to be generated and later, accelerating their accumulation. The design of multiplier depends upon the type, range and precision of data to be processed by the multiplier block viz. fixed point and floating point numbers represented in binary and decimal format. Since, in electronic computers, binary data can be stored more efficiently and processed faster than decimal data, binary multiplication is suitable for scientific applications due to its mathematical properties and performance advantage. However, the decimal format is preferred for many non-scientific applications because of greater precision and decimal rounding. Thus, current financial, e-commerce and user-oriented applications make an intensive use of integer and fractional numbers represented in decimal radix. This paper presents an overview of the development of reconfigurable decimal multipliers. The multiplication can be realized using sequential technique where partial products are generated sequentially and each newly generated product is added to previously accumulated partial product. The second method is a parallel multiplier in which partial products are generated in parallel and accumulated using a fast multi-operand adder. The third method is an array multiplier, where array of identical cells are used for generating new partial products; accumulating them simultaneously. In this method, no separate circuits are required for generation and accumulation of partial products which reduces execution time but increases hardware complexity. There are several designs of decimal multipliers which are implemented and synthesized by researchers with improvement in one or more design parameters viz. speed, power, and area. In this paper, the module functionality and performance issues of several designs of decimal multipliers are compared.
Load Measurement Issues in Dynamic Load Balancing in Distributed Computing Environment

— In this paper, the issues in load measurement in dynamic load balancing (DLB) algorithms have been explored. We have analyzed various load indices used to estimate the load on the nodes in the system for load balancing algorithms. The simulation model has been used to address performance issues associated with load balancing. The architecture for implementation and performance evaluation of indices used for capturing and distributing load has been proposed.
A NOVEL HYBRID AGGREGATED CLASSIFIER FOR INTERNET TRAFFIC CLASSIFICATION

: The classification and identification of network application from network traffic flow provides various advantages to a number of fields such as security monitoring, intrusion detection and to tackle a number of network security problems including lawful interception. In this paper traffic flow is described by using the discretized statistical features. The flow correlation information of the network traffic flow is modeled by Flow Container (FC). In this paper novel hybrid aggregated classifier is proposed. First, low density flow and high density flow is analyzed. For Low density flow C4.5 classifier is used and high density flow Naïve Bayesian classifier is used and finally aggregated result is provided. The aggregated result is compared with machine learning algorithm such as Single Naïve Bayesian predictor. The proposed system enhances the accuracy rate as well as improves the performance of the system.
ANALYSIS OF PMSG BASED WIND ENERGY CONVERSION SYSTEM OPERATING UNDER DIFFERENT GRID FAULT

---In the field of renewable energy generation has been observed wind energy. Where the technology is more rapid growth. It attracts attention as one of the most effective ways in terms of the cost of generating electricity from renewable energy sources. Voltage of the wind generator permanent magnet synchronous generator (PMSG) is directly driven by a variable due to the sporadic nature of wind energy. Voltage fluctuation and power of major concern in the connected network systems generate electricity using a wind converter list. Inverter is essential for interaction of from wind sources with Ac network. Synchronous generators used a variable speed the permanent magnet to extract the utmost of energy from wind energy conversion system. The is suggested common strategy for power control the permanent magnet synchronous generator a system based on wind energy conversion (WECS) operating under different the network conditions A unified power control strategy is proposed for the permanent magnet synchronous generator-based wind energy conversion system (WECS) operating under different grid conditions. In the strategy, the generator-side converter is used to control the dc-link voltage and the grid-side converter is responsible for the control of power flow injected into the grid. The generatorside controller has inherent damping capability of the torsional oscillations caused by drive-train characteristics. The grid-side control is utilized to satisfy the active and reactive current (power) requirements defined in the grid codes, and at the same time mitigates the current distortions even with unsymmetrical grid fault. During grid faults, the generator-side converter automatically reduces the generator current to maintain the dc voltage and the resultant generator acceleration is counteracted by pitch regulation. Compared with the conventional strategy, the with and without dc chopper, which is intended to assist the fault ride through of the WECS, can be eliminated if the proposed scheme is employed. , the proposed strategy has quicker and more precise power responses, which is beneficial to the grid recovery The simulation results CHECK the effectiveness of proposed strategies. the power output of the permanent magnet synchronous generator (PMSG) of wind turbine systems.
Copy-Move Forgery Detection Based on Enhanced Patch-Match

Image forgery detection approaches are varied and serve same objectives. However, the difference in image properties causes some limitations of most of these approaches. Integrate multiple forensic approaches to increase the efficiency of detecting and localize the forgery was proposed based on the same image input source. In this paper, we propose a new detector algorithm based on different image source format. We propose approach to detect a copy-move forgery based on PatchMatch enhanced by the dense field technique. The F-measure score used same evaluation function to make the system more robust. The output result shows high efficiency of detecting and localizing the forgery in different image formats, for passive forgery detection.
Comparative Study of Data Mining Classification Techniques over Soybean Disease by Implementing PCA-GA

— Data mining is a relatively new approach in the field of agriculture that can be used in the extraction of knowledge and discovery of patterns and relationships in agricultural data. Classification techniques in data mining are used to discover patterns and knowledge agricultural datasets, however, the accuracy of these classification techniques depends on the quality of data that are used as inputs in the data mining process. In this paper, an efficient data mining methodology based on PCA-GA is applied as a data pre processing technique, to reduce the dimensionality of the soybean dataset. The mechanism draws improvements to classification problems by applying Principal Components Analysis (PCA) and subsequently applying Genetic Algorithm (GA) to further reduce the dimensionality of the dataset, and selecting the best representative subsets, thereby improving the performance of classifiers. Different data mining classification techniques are applied to the resulting reduced dataset and classification metrics are compared. This approach is to asses classification rates on the PCA-GA reduced soybean dataset. The learning and validation experiment was performed using WEKA, a workbench containing implementations of the k-NN, Naïve Bayes, J4.8 and MLP classification algorithms, including the PCA and GA. Classification accuracy was validated using 10-folds cross validation.
EXPLORING HUMAN RESOURCE MANAGEMENT PRACTICES IN SMALL AND MEDIUM SIZED ENTERPRISES WITH SPECIAL REFERENCE TO BANGALORE AND MYSORE REGION

Human resource is required for an organization to conduct different business activities. Without the support of human resource the organization cannot exist or operate effectively. Success of any organization depends on the effective use of human resources. This is true in the case of small industry where the owners have a close and more personal association with their employees. Human resource management includes different practices such as Recruitment and Selection, Training and Development, Compensation and Rewards, Performance Appraisal and Welfare Measures. The small and medium sector has emerged as a dynamic and vibrant sector of the Indian economy. A small and medium sized enterprise is characterized by abundant labour supply and reduces unemployment and so on. In this paper an attempt is made to bring out the work carried out by different authors. A pilot study is carried-out to test the internal consistency of the questionnaire. In this study Human resource practices considered are Recruitment and Selection, Training and Development, Compensation and Rewards, Performance Appraisal and Welfare Measures. The Cronbach's alpha values obtained are well above the level of 0.7, thus are acceptable for the analysis purpose.
PARAMETRIC OPTIMIZATION ON PLASMA ARC CUTTING MACHINE FOR AISI 1018

In this study we choose plasma cutting machine as our main machine tool and AISI1018 material also used . with the start of globalization there are many company emerges. So, there are more than one compa ny make similar product to sustain this competitive market we must make product which quality is good and must have low price.so with the use of optimization technique we must make our product more economical and also save time coast.so that’s why we consider GRA and some other optimize technique issued to find out optimum solution for the machine where it give its best performance.
Development and characterization of albumin nanoparticles for pulmonary drug delivery

Pulmonary drug delivery is a non-invasive, non-systemic delivery approach for both local and systemic drugs and a method to directly target disorders of lung. The albumin nanoparticles were prepared by modified desolvation method using different concentration of albumin as biodegradable polymer for lungs. The prepared albumin nanoparticles were evaluated for entrapment efficiency, particle size, polydispersity index, zeta potential, transmission electron microscopy, in-vitro drug release, stability study and in-vivo study. The entrapment efficiency of all albumin nanoparticles formulations were found to be in the range of 61.74 % 73.45 %. The particle size of albumin nanoparticle formulations were found to be in range 81.6 nm 148.4 nm. The zeta potential of albumin nanoparticles found to exhibit stability due to negative charge on the surface. The transmission electron microscopy indicated the spherical surface of the albumin nanoparticles. The in vitro release was found to follow higuchi plot as compared to zero order plot, first order plot and krosmeyer peppas plot. Stability studies showed that albumin nanoparticle formulation ANps5 was stable according to ICH guidelines for 6 months. In-vivo study using rat model indicated the localization of albumin nanoparticles in the lungs of rat.
Int. J. Biosci

The objective of this study is to characterizethe structure of populations associated with cowpea in several agroecological zones of Senegal, using genetic markers (sequencing) associated with Bayesian approaches such as Appoximated bayesian computation. Portions of the Cytochrome b gene of Callosobruchus maculatus L. were sequenced, using samples from agro-ecological areas in Senegal.Sequences show a rather high degree of polymorphism (hd = 0,920±0,00054; Pi= 0,06±0,00021). Results from genetic diversity analysis reveal a higher value of variable sites, number of mutations, haplotypic diversity, nucleotide diversity and number of nucleotide differences in agro-ecological zones of North Peanut Basin (hd =0.978 ± 0.054 ; Pi=0.13825 ± 0.02291) and Senegal River Valley (hd =1.000 ± 0.052 ; Pi=0.03372 ± 0.00777), areas where cowpea is the most widely cultivated in Senegal.The largest number of mutations (134) is observed in the NBA while the lowest value is obtained from SBA (3). Fst value reveals that the more genetically differentiated populations are those of the SBA and HCSO with a very high Fst value (0.75) whereas the minimum value is encountered between the individuals of the river valley and those South Peanut Basin. Recent studies increasingly highlight the effect of climate change in agro-ecological zones on the structure and dynamics of phytophagous insect populations. * Corresponding Author: Mbacké Sembene  mbacke.sembene@ucad.edu. sn International Journal of Biosciences | IJB | ISSN: 2220-6655 (Print), 2222-5234 (Online) http://www.innspub. net Vol. 11, No. 6, p. 116-129, 2017
Effect of Pectin Extract of Date (Phoenix Dactylifera L) on Erythrocytes Oxidative Damage and Hematological Parameters Induced by Lead in Males Rats

Lead is a non-essential element for human body and can caused a several damage in all metabolic and structural function, especially on hematological system. The aim of this study was to evaluate the effects of pectin extract from date (Phoenix Dactylifera L) on hematological and biochemical alteration in red blood cells (RBC) induced by lead, and determination of lead burden in blood. Rats were exposed to lead acetate (350mg/Kg) for 4-weeks and treated during 4-weeks with pectin extract at 3%. Orally administration of pectin after intoxication with lead acetate increased significantly the red blood cells count (RBC), hemoglobin (Hb), hematocrit (Ht), means corpuscular hemoglobin (MCH) and decreased significantly white blood cells count (WBC) in intoxicated group vs. control. Moreover, pectin extract of date improved δ-aminolevulinic acid dehydratase (δ-ALAD) activities in rats treated compared with the intoxicated rats, and reduced blood lead level. Therefore, pectin provided a significant protection to Thiobarbituric acid reactive substances (TBARS) level in erythrocyte whereas caused an increase in superoxide dismutase (SOD) and glutathione reductase (GSSH-Red) activities with a decrease of glutathione peroxidase (GSHPx), glutathione transferase (GST) and Glutathion reduced (GSH) level in red blood cells. In conclusion, the data suggests that pectin may have the ability to chelating lead and reducing oxidative stress in erythrocyte.
Investigating the Effectiveness of the Group Instruction of the Healthy Lifestyle on Stress Management and Emotion Regulation by Using Psychodrama in Students

This study aimed at investigating the effectiveness of the group instruction of the healthy lifestyle on stress management and emotion regulation by using psychodrama in female dormitory students of the University of Isfahan in the first semester in 2013. The statistical population includes all newly-arrived female undergraduate dormitory students. 32 subjects were selected among the students with high score in Difficulties in Emotion Regulation Scale and low score in Stress Management Questionnaire; they were randomly categorized into the experimental group and control group (16 subjects per group). The study was quasi-experimental with pre-testpost-test and control group. The experimental group was instructed for eight 90-minute sessions. Stress management questionnaire of Melekpour and Difficulties in Emotion Regulation Scale (DERS) were used to collect data. The results of post-test by the analysis of covariance suggested that the instructional intervention of the healthy lifestyle using psychodrama significantly increased ability of stress management and emotion regulation in female dormitory students participating in the study compared with control group (p<0.01). Therefore the results of the study recommend instructing the healthy lifestyle in order to manage stress and Difficulties in Emotion Regulation.
Emotional Controller based Torque Ripple Reduction of Switched Reluctance Motor (SRM)

This paper presents a modern control system for switched reluctance motor (SRM) drives. The control system is based on computational model of mammalian limbic system and emotional processes (BELBIC) which is presented as speed controller of the motor drive with attention to torque ripple decrease. In this work, a novel and simple model of SRM drives control plant is achieved by using the intelligent control system, which controls motor speed accurately and directly, without needing to use any conventional controllers and also, quite independent of the motor parameters. Then, proposed method is compared with a conventional PI controller and sliding mode as a nonlinear approach, which shows its advantages than both of them. The performance of the proposed controller is demonstrated by simulation and experimental results using a 4kW, four-phase, 8/6 pole SRM DSP-based drive system. This generation of the intelligent controllers that has high auto learning speed with simple structure shows excellent praxis for industrial scale utilization truly. *Reviewed by ICETSET'16 organizing committee
Amplifying Statistical Machine Translation (SMT) Model Using Graph-Based Approach: A Novel Idea

The Statistical machine translation system arises in the India to translate the source language text to target language text for the better communication. In the previous system, Rule-based English to Hindi Translator translates English affirmative sentences in Hindi. During this analysis, a system has a tendency to convert the simple English affirmative sentences to Hindi sentences. The Hindi language is still unfocused. In this system, English sentences will be taken as an input and output will be given as Hindi Sentences. To enhance the process of Machine Translation graph based pruning approach is introduced to achieve optimized results, better accuracy and efficient translation for English to Hindi Language Translation.
Formal Verification of Conditionally Evolving Memory

In Von Neumann architecture (VNA) and in many of the computing models based on VNA, the memory is separated from the processor. Conversely, the human memory is an evolving result of continuous processing. Therefore, the processing in human mind become efficient over subsequent processing cycles. As such, a six-state continuous processing model has been introduced to the conventional computers imitating this evolving memory to enhance the performance of computing. Further, this model has been implemented in a Fraction Calculator and a Quadratic Equation Solver. With the experiments conducted over these applications, it could prove that the accurate solutions can be provided faster over subsequent execution cycles with an evolving smaller memory. Moreover, this paper presents the formal verification of the model by simulating it with a non-deterministic Turing machine. Then, its satisfiability and the NP-completeness have been proved using Cook’s theorem, hence proving its real-world applicability in theoretical level.
Complications of intestinal stomas – A Descriptive study

Intestinal stoma is a very commonly performed procedure with a high rate of complications. This study was undertaken to study the various types of complications in different types of intestinal stomas and their management. To study the various complications associated with the intestinal stomas. This was a prospective study involving 40 patients underwent stoma formation and its complications at Victoria hospital attached to Bangalore Medical College and Research Institute, Bangalore. Both elective and emergency procedures were included in the study. Data was collected by following up the patient postoperatively either by phone or in person. A total of 40 patients were included in the study who underwent stoma formation at this hospital from October 2010 to September 2012. The study include both emergency and elective stoma formation. The most common indication for stoma formation was malignancy (n=14) followed by Bowel perforation(n=12). Complications were seen in 20 of the patients undergoing stoma formation. Local sepsis was seen in 10 patients stenosis was seen in 2 patients. Stoma formation is associated with a high rate of complication. Loop Colostomy is associated with highest rate of complications. Complications were more during emergency settings. Local sepsis was the most common complication. Parastomal hernia was a difficult complication to treat. Loop ileostomy seemed to have a lesser complication rate as a defunctioning stoma as compared to loop colostomy. KEYWORDS
Semi Supervised Approach Based Brain Tumor Detection with Noise Removal

:- Brain tumor detection and segmentation is the most important challenging and time consuming task in the medical field. In this paper, Magnetic Resonance Imaging (MRI) sample image is considered and it is very useful to detect the Tumor growth. It is mainly used by the radiologist for visualization process of an internal structure of the human body without any surgery. Generally, the Tumor is classified into two types such as malignant and benign. There are many variations in tumor tissue characteristics like its shape, size, gray level intensities and its locations. In this paper, we propose a new cooperative scheme that applies a semi-supervised fuzzy clustering algorithm. Specifically, the Otsu (Oral Tracheal Stylet Unit) method is used to remove the Background area from a Magnetic Resonance Image. Finally, Semi-supervised Entropy Regularized Fuzzy Clustering algorithm (SER-FCM) is applied to improve the quality level. The intensity, shape deformation, symmetry and texture features were extracted from each image. The usefulness and significance of this research are fully demonstrated within the extent of real-life application
Fuzzy Multi-Objective Supplier Selection Problem for Multiple Items in a Supply Chain

Today’s market is highly competitive. The role of supply chain managers is to select best suppliers because major part of the capital is spent on purchasing raw material/semi finished items. The strategic decision of supply chain is to minimize the expenses on the purchase of items. There are several criteria involved in this problem; such as cost, quality, on-time delivery and long term relationship. Some of the criteria are quantitative in nature and some the criteria are qualitative in nature. Qualitative criteria are expressed in triangular fuzzy numbers. It requires defuzzification; the graded mean integration (GMI) representation method is used. Again all of these criteria are conflicting in nature that’s why fuzzy programming is used. For formulating the crisp model, it requires defuzzification; fuzzy compensatory operator is applied. This model gives us the idea about supplier selection as well as order quantity from each selected suppliers. Also, the numerical example is given to illustrate the above methods.