Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Simulation of Solar PV DC Microgrid for Rural Electrification

In this paper We present the analysis and design of the e dc microgrid system for electrification. The microgrid configuration has been driven by field information gathered from India. The important parameter of such system depends on the Microgrid capacity of the transmission network which overflows the value of the voltage and the current from the main grid, which power the cost matrix analysis of the overall system which has to be equal. In this paper, we compute that the excessive cost of power (COE) for the proposed dc microgrid framework will be under minimal charges as put forth by the electrification governing agency according to the per kW-hr. We additionally present test results from a privately introduced dc microgrid model that exhibit the consistent state conduct, the bother reaction, and the general efficiency of the framework. The results show the reasonableness of the introduced dc microgrid design has totally inflicts with the main grid feasibly and found out to be very easy to implement without any extra cost to the system as far as the rising districts and the number of population in such districts are concerns.
Performance Analysis of Data Mining Techniques over Sleeping Problem Dataset

: Based upon the various classification algorithms such as C4.5, CHC Adaptive, steady state genetic algorithm and Generational Genetic Algorithm, the efficiency of various data mining techniques on sleep habits dataset was analyzed and compared using Euclidian Distance, HVDM, K-fold validation and 5-fold validation. The classification Techniques were evaluated with the help of various data mining tools such as WEKA,KEEL etc, which consist of machine learning language that provides the mechanism for classifying the data through the use of different algorithms. Further, using different classification algorithm, the time taken metrics were observed, analyzed and summarized to the relationships which had been identified. During the research Euclidian distance in CHC preprocessing Technique was found to be most efficient with time taken 27.89 seconds and K-fold validation with Genetic Genrational algorithm was least efficient with 107.64 seconds.
SEMI-AUTOMATIC GENERATION OF MOSAIC FROM OVERLAPPING IMAGES USING MATLAB

: Construction of Mosaic from overlapping images is a crucial issue in change detection and other applications. Image registration which seek to fuse images acquired in patches together is a laborious and computationally intensive task. This study presents a user-assisted (Geometric based) image registration algorithm using the Image Processing toolbox of MATLAB. Orthogonal Transformation, Affine and Projective Transformation functions were applied and Root Mean Square Deviation was used for the evaluation of mismatch (errors). The results proved that Registration based on Projective Transformation function was of better accuracy than the Affine Transformation function while Orthogonal Transformation based registration gave the poorest result.
Prevalence and spectrum of helminths in free-ranging African buffaloes

Emanuel Senyael Swai, Deogratius Mshanga1, Robert Fyumagwa2, Deogratius Mpanduji3, Idrisa Chuma4, Sayael Kuya5, Ernest Eblate2, Zablon Katale2, Julius Keyyu2 Veterinary Investigation Centre (VIC), PO Box 1068, Arusha, Tanzania Tanzania Wildlife Research Institute (TAWIRI), PO Box 661, Arusha, Tanzania Sokoine University of Agriculture (SUA), Faculty of Veterinary Medicine,PO Box 3020, Morogoro, Tanzania Tanzania National Parks, Ecological Monitoring Department, PO Box 3134, Arusha Ngorongoro Conservation Area Authority, PO Box 1 Ngorongoro Crater, Arusha Journal of Coastal Life Medicine 2013; 1(2): 145-150
A Novel Framework for Fast Video Inpainting

: Video inpainting is considered as a complex problem in the current literature. This paper proposes a fast, efficient and automatic method of video inpainting to inpaint moving objects in the video. The presented algorithm employs the spatiotemporal coherency present in the video frames for inpainting while considering the fact that the background either has periodic motion or it remains stationary. The algorithm does not require any manual generation of the mask. Batch frame based inpainting is proposed to maintain motion information in case of background having periodic motion. A new dissimilarity measure; 3D N-SSD is introduced to find similar frames for frame-based video inpainting algorithms. The proposed algorithm is tested for different background and illumination conditions. We have done speed and quality test analysis by inpainting videos of different backgrounds. Quick execution times and high PSNR values for inpainted videos show effectiveness of our algorithm.
HRM Efficiency and Limitations for High-Throughput SSR Genotyping: A Case Study Using Grapevine Flavor-Linked Markers

Genetic diversity studies based on variation of simple sequence repeats (SSRs), have been greatly relied on easy to use gel-based techniques which, however, can be both time-consuming as well as inefficient for accurate genotyping [1]. Other techniques, like capillary electrophoresis (CE) requires post-PCR handling and is expensive. As an alternative, high resolution melting (HRM), a technique that monitors the decrease of fluorescence of a DNAbinding dye during the dissociation of doublestranded DNA [2], can provide an efficient solution for SSR genotyping at a reasonable cost. This measurement occurs immediately after PCR in the same tube at one-step. It is a rapid, simple, closedtube, homogenous, and cost-efficient approach, that has high specificity and sensitivity, while allowing transition to high-throughput scale [3]. It has been widely applied in sequence polymorphism identification, as well as in the studies of genetic variability and genotyping [4-9]. However, its application, efficiency and limitations for high-throughput SSR genotyping have not been tested, yet.
Android Malware : Study and Analysis for Privacy Leak in Ad-Hoc Network

Summary Smartphone’s users has been increasing since last few years which provides numerous operations like accessing information through online mode, payment options, using utility applications, playing games. Smartphone’s have become so powerful these days that tends to play the role of PC’s. The basic operation of any mobile phone calling, storing personal details like contact information in contact book, business data, text messages etc. Since we are in new generation, where so many different varieties of devices connect together with each other giving way for security concerns. With the huge and tremendous uprising Smartphone sales in market, the chances of malicious attacks became a trouble. As malware developers tries to steal information from such devices. This paper provides a study of analyzing malware through static and dynamic means. In static analysis we are performing reverse engineering to detect malicious code and in dynamic analysis we are using tools to identify the packet structure. Further we perform white listing for safe destination address. In this paper we are highlighting the aspects of mobile malware when compared with third party applications like Lookout etc.
Chronic cannabis use and attention-modulated prepulse inhibition of the startle reflex in humans

Background. Various studies show that cannabis use alters attention and cognitive functioning in healthy humans and may contribute to development of schizophrenia or worsening of pre-existing psychosis. However, the impact of cannabis use on brain function in humans is not well understood. Schizophrenia is associated with a deficit in prepulse inhibition (PPI), the normal inhibition of the startle reflex by a nonstartling stimulus (prepulse), presented before the startle stimulus at short time intervals (lead-time intervals). Such PPI deficit is thought to reflect a sensorimotor gating dysfunction in schizophrenia. PPI is also modulated by attention and PPI reduction in schizophrenia is observed when patients are asked to attend to, not ignore, the stimuli producing PPI. The aim of the current study was to investigate the association between self-reported chronic cannabis use and attentional modulation of PPI in healthy controls and in patients with schizophrenia. Furthermore, the association between cannabis use and other startle reflex modulators, including prepulse facilitation (PPF) of the startle reflex magnitude at long lead-time intervals, prepulse facilitation of the startle reflex onset latency and habituation of the startle reflex magnitude, were examined. Method. Auditory-evoked electromyographic signals were recorded from orbicularis oculi muscles in chronic cannabis users (29 healthy controls and 5 schizophrenia patients) and non-users (22 controls and 14 patients). The data for 36 participants (12 non-user controls, 16 healthy cannabis users, and eight non-user patients) were used in the final analyses and the patient data were used as a pilot study, because relatively few participants met the rigorous exclusionary criteria. Participants were instructed to attend to or to ignore either the startle stimuli alone (70 – 100 dB) or prepulse (70 dB) and startle stimuli (100 dB) separated by short lead-time intervals (20 – 200 ms) and long lead-time intervals (1600 ms). In order to ignore the auditory stimuli the participants played a visually
SPARSE MIMO OFDM CHANNEL ESTIMATION AND CHANNEL CAPACITY MAXIMIZATION USING OPTIMAL LMMSE

– The sparse channel estimation is first introduced in Orthogonal Frequency Division Multiplexing systems. This project proposes a parametric Sparse Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) channel estimation scheme. Optimal LMMSE scheme, whereby super-resolution estimates of path delays with arbitrary values can be achieved. Meanwhile, both the spatial and temporal correlations of wireless MIMO channels are exploited to improve the accuracy of the channel estimation. The parametric sparse signal maximum achievable channel gain for MIMO OFDM systems with temporal and spatial correlation is achieved by the proposed correlation system with equalizer. The proposed MIMO OFDM operating in time variant frequency selective channel, AWGN and Rayleigh channel. In multiantenna systems, this project investigates by sensing throughput in terms of capacity. The capacity in Mbps is increased while increasing the signal channel gain. For outdoor communication scenarios, where wireless channels are sparse in nature, path delays of different transmit-receive antenna pair share a common sparse pattern due to the spatial correlation of MIMO channels. Meanwhile, the channel sparse pattern is nearly unchanged during several adjacent OFDM symbols due to temporal correlation of MIMOchannels.
Study on Melanized Shrimp Reveals Bacillus sp and Acinetobacter sp as Potential Sources for Bacterial Tyrosinase

Invertebrates such as shrimp lack advanced immune system and the immunity is dominated by innate immune responses. Prophenoloxidase system plays a major role in identification, sequestration and elimination of invading pathogens. Melanization, which is performed by phenoloxidase (PO) and controlled by the prophenoloxidase (proPO) activation cascade, plays an important role in the invertebrate immune system in allowing a rapid response to pathogen infection (Amparyup et al., 2013) International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 8 Number 12 (2019) Journal homepage: http://www.ijcmas. com
Improved FP-Growth Algorithm Based on Top Down Approach in Mining Frequent Itemsets

- In this research paper, the proposed improved FP-Growth algorithm based on top down approach (TD-IFP-Growth) aims to provide solution for efficient mining of frequent itemsets. In the existing FP-growth algorithm, searching of FP-tree adopts top down approach which generates conditional pattern base and sub-FP-trees. Bottleneck of FP-growth algorithm is the requirement of large amount of time and memory in generation of frequent itemsets. The proposed TD-IFP-Growth algorithm overcomes the problem of existing FP-Growth algorithm by searching the IFP-tree in top down approach which is opposite to FP-Growth algorithm. From the experimental results it is observed that the proposed TD-IFP-Growth algorithm consumes lower amount of time and memory as it does not generate conditional pattern base and sub-FP-tree.
Review on antifungal activities of Ayurvedic Medicinal Plants

Infectious diseases represent a critical problem to health and they are one of the main causes of morbidity and mortality worldwide. The resistance to antibiotics and with the toxicity during prolonged treatment with several drugs due to this medicinal plants are widely used by the traditional medical practitioners for curing various diseases in their day to day practice. Since ancient times, plants have been an exemplary source of medicine. During the past several years, there has been an increasing incidence of fungal infections due to a growth in immunocompromised population such as organ transplant recipients, cancer and HIV/AIDS patients. The presented review summarizes the information concerning the new profile of antifungal drugs obtaining from medicinal plants.
SURVEY ON IMPROVE JOB PERFORMANCE USING MAPREDUCE IN HADOOP

— In recent years the different scheduling technique became a more attractive point mark to many researchers, but even though many achievement that have been made, then also still many trouble in this field. The main goal of this paper is to provide a better understanding of scheduling technique in MapReduce and analyze very important research directions in this field. There are lots of key techniques in MapReduce to improve the job performance in open source platform to choose as Hadoop. To address it, analyze and optimize the resource allocation in different aspect. The performance of Hadoop can be increased by proper resource management to the task in default scheduling technique. In Hadoop a program called map reduce is used for gathering data according to query. As use Hadoop is used for large amount of data therefore scheduling in Hadoop must be effective for better performance. So objective is to study and identify various scheduling technique, which are used to maximize job performance in Hadoop.
ALTERATION IN PROTEIN EXPRESSION OF AURORA A, FHIT AND IGF2 IN ESOPHAGEAL CANCER

Evaluating protein levels, especially of those related to cell cycle and mitotic machinery, can be effective in cancer detection and therapeutics. The protein expression of Aurora A, FHIT, and IGF2 were evaluated in esophageal cancer. 51 subjects were included: squamous cell carcinoma (n=40), adenocarcinoma (n=8) and normals (n=3). Immunohistochemistry was performed on tissue sections obtained from archival esophageal tissue blocks to evaluate protein expression. Immunohistochemistry with active Aurora A (phosphoT288) showed moderate-high cytoplasmic expression in 100% normal cases [mean:2.16(±0.28)], whereas only 37.5% of cancers showed mild-moderate Aurora A expression [mean:0.51(±0.70)]. Aurora A expression showed four-fold decrease in cancer when Vol-6, Issue-8 Global Journal of Advanced Research 276| P a g e 3 0 A u g 2 0 1 9 w w w . g j a r . o r g compared to normal esophageal tissue. IGF2 (cytoplasmic) expression was observed to be mild-moderate in all normal samples. Of the cancers, 81.2% showed IGF2 expression where mean expression of IGF2 in normal tissue was 0.57(±0.28), while in cancer, it was 1.29(±0.77). IGF2 expression showed a two-fold increase in cancers when compared to normal tissue. This could be attributed to loss of imprinting, which was however not investigated. FHIT expression showed mild (0.4-fold) decrease in cancer tissue when compared to normal; however this did not seem significant. Our results show that reduced active form of Aurora A expression was significantly associated with esophageal cancer. It maybe a good marker to predict cellular progression to cancer in the esophagus. Active form of Aurora A expression should be taken into account before the use of kinase inhibitors in esophageal cancer therapy. Loss of FHIT expression and increased IGF2 may also contribute to cancer; FHIT expression did not seem significant.
Biosynthesis of Silver Nanoparticles by Plumeria rubra Flower Extract: Characterization and Their Antimicrobial Activities

The main objective of this work is focused on to propose a simplified and efficient green synthesis of silver nanoparticles with proven antibacterial properties. In the present study silver nanoparticles were biosynthesized by the biological approach using Plumeria rubra (red frangipani) flower extract at room temperature. AgNPs were rapidly synthesized from bio-reduction of silver ions using aqueous extract of Plumeria rubra flower and was observed when the light yellow coloured flower extract solution turned to brown colour with the addition of silver nitrate solution. The biosynthesized AgNPs were characterized by ultravioletvisible (UV-Vis) and transmission electron microscope (TEM). The UV spectra showed the characteristic surface plasmon resonance band for AgNPs in the range of 425–465 nm. The prepared AgNPs were effective broad spectrum antimicrobial agent, which exhibited an effective inhibitory activity against Escherichia Coli and Bacillus sp. Therefore synthesis of AgNPs using environmentally benign resources such as flower extract suggests a potential tool to combat against increasing antibiotic resistance.
DBSCAN APLLY In Weighted Clustering Algorithm for MANET

– In this paper, we propose a mobile ad-hoc network, an emerging type of wireless networking, from which mobile nodes associate extemporaneous or ad-hoc basis. Nowadays due to on – demand, mobile node is a collection of multi-node. The mobile ad-hoc network is a wireless communication technology, which do not have any fixed infrastructure in network domain. In network architecture, nodes move dynamic in nature. In Network architecture nodes have dynamic mobility resulting network faces break down issues. Mobile ad-hoc network have less stable, so to improve stability it requires large transmission area. We designed density based clustering algorithm to improve the stability and efficiency in mobile network. In our network architecture we have number of domain to choose cluster to manage all information in that domain cluster head. Election is involved on on-demand procedure, To reduce the computation , communication and communication cost mobile node chooses on the basis of its neighbor’s density, so we apply density based clustering algorithm at mobile ad-hoc network and selected cluster head node in cluster. For  -neighboring, min-pts based weighted cluster algorithm We propose DBSCAN from which it take into parameter gets mobility and battery power of mobile nodes. As a result, of cluster head selection the cluster formation approaches to show the constant rate of head selection and reasonable amount of computation time.
A COMPARATIVE EVALUATION OF SOCKET PRESERVATION USING BONE GRAFT PLUG (SYBOGRAF-T)R COMBINED WITH PLATELET RICH FIBRIN AND EXTRACTION ALONE – A CLINICO-RADIOGRAPHIC STUDY

Aim: the present study was done to compare the efficacy of beta tricalcium phosphate bone graft plug (SYBOGRAF-T)R along with PRF membrane for purpose of post extraction socket preservation. Materials and methods: this was a randomized controlled trial done in total of 34 sites with class II extraction sockets in 33 patients. In Test group, beta tricalcium phosphate bone graft plug along with PRF membrane was used whereas Control group consisted of extraction alone sites. Results: Test group sites showed significant reduction in bone loss after extraction and socket preservation when compared with extraction alone sites. Conclusion: Results of this study indicate that alveolar bone resorption following tooth extraction may be prevented or reduced by the use of β-TCP plug (SYBOGRAF-T) with PRF membrane.
Review of Literature on Heat Transfer Enhancement in Heat Exchangers

This paper features a broad discussion on the enhancement of heat transfer through heat exchangers. The use of Process Integration in heat transfer enhancement has many benefits. First, enhanced heat exchangers require less heat transfer area for a given heat duty because of higher heat transfer coefficients. Second, the heat transfer capacity for the given heat exchanger can be increased without changing physical size of the exchanger. This paper provides some methods for increasing shell and tube and compact exchanger’s performance. The methods consider whether the exchanger is performing correctly to begin with, excess pressure drop capacity in existing exchangers, there-evaluation of fouling factors, and the use of augmented surfaces, and enhanced heat transfer. Also the Nano fluids possess immense potential to improve heat transfer and energy efficiency in heat exchangers. Finally, the following enhancements in geometries are discussed: tube inserts, tube deformation, baffles, finning.
Outlier Detection Using Unsupervised and Semi-Supervised Technique on High Dimensional Data

: Outlier detection is useful for credit card fraud detection. Due to drastic increase in digital frauds, there is a lot of financial losses and therefore various techniques are developed for fraud detection and applied to diverse business fields. In high-dimensional data, outlier detection presents some challenges because of increment of dimensionality. In this paper, the proposed model aims to implement unsupervised outlier detection technique using KNN, AntiHub and AntiHub2 algorithm and semi-supervised outlier detection technique in which first extracting negative instances by KNN and then with fuzzy clustering of both positive and negative example with distributed approach to find credit card fraud. Hence this method will provide more accurate results as compared to other methods.
Multi-Agent Based Traffic Signal Optimization under Fully Actuated Control

This paper presents a multi-agent based distributed traffic control model to optimize the traffic signal for multiple intersections. Previous works in the area of traffic signal control suffer from a number of inadequacies, including the use of fixed cycle length, centralized mode of operations and dependency on historical data. Considering these, the aim of this work is to control the traffic signal timings by adjusting the phase sequence in order to minimize the delay in traffic at the intersections. To model the traffic network, a three-tier multi-agent system has been adopted in distributed mode. In addition, a fully actuated signal control algorithm is designed and it utilizes state-space equations to formulate the queue length at the green light phase and red light phase. The proposed model is simulated with SUMO simulator and a comparative analysis has been made between adaptive control method, multi-agent method based on collective learning and multi-agent based fully actuated control method on a similar platform. The results spectacle the proposed traffic control model outperforms that of other existing control methods in all condition; hence it can be deployed to control the tremendous traffic on the road network and to optimize the traffic signal in more effective manner.