Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Indian Classical Dance Steps using HOG Features

In this paper Histogram Oriented Gradient (HOG) features are extracted to classify the postures in a Indian classical dance video dataset. The aim is to design an automated system that can recognize the steps of Indian classical dance in a video. As a video consists of frames of different actions, so features representing shapes can be used to interpret the dance steps. HOG based features are capable of representing the shape in varying background conditions. The proposed system performance is analyzed for total number of 50 poses taken from 9 different Bharatanatyam videos in varying background conditions. To find an optical size of HOG based features Taguchi analysis for L-9 orthogonal array is implemented
Morphological Study of Acacia senegal (L.) Willd. from Borno and Yobe States, Nigeria

Morphological and Reproductive characters of Acacia senegal (L.) Willd. trees were assessed for variation. The morphological characters measured were: Tree Height (TH, m), Bark Thickness (BT, cm), Canopy Cover (CC, m) and Diameter at breast height (DBH, m). Pods and seeds parameters were measured as reproductive characters. These include: Pod length (PL, cm), Pod Width (PW, cm), Seed Diameter (SD, cm), Seed Thickness (ST, cm) and Seed Weight (SW, g). Gum yield (GY, g) was also assessed. The results show that morphological and reproductive characters observed differed significantly (P < 0.05) among the trees. Performance of trees from Yobe State is significantly higher than those from Borno for all the parameters measured which include; Tree Height (5.64m), Bark Thickness (0.53cm), Canopy Cover (7.01m), Diameter at breast height (8.210cm), Pod width (2.96cm), seed diameter (1.11cm), seed thickness (0.387cm) seed weight (24.10g) and gum yield (216.50g). The variation observed may provide bases for genetic improvement of this important multipurpose leguminous tree.
Survey of Service Identification Methods into Service-oriented Modeling Phase

Recent changes in client and business requirements are major challenge for development of large-scale systems. There are different methods to deal with that problem as one of them is service-oriented architecture. Service oriented architecture comprises various methodologies and life cycles that the first phase is focused on service modeling in all of them. The phase is consisted of three steps including service identification, service specification, service realization. Among these steps, service identification should be placed particular importance due to priority for the application. The reason is that the output of other steps depends on the output of service identification. The given methods are categorized into three parts including prescriptive, semi-automated and automated parts in terms of automation. On the other hand, the existing semi-automated and automated methods are encountered by some problems such as regression performance. We will discuss the existing methods of service identification and its weakness and strength in order to identify services.
MITIGATION OF EARLY DELTAMETHRIN INDUCED HEPATOTOXICITY IN MALE MICE OF SWISS STRAIN BY ALLIUM SATIVUM

The importance of Allium sativum as herbal remedy in the system of Indian traditional medicine and its prime position in Ayurveda with other great herbs is unquestionable. Though extensive research has been carried out by number of researchers on its medicinal properties, there is still paucity regarding its ameliorative efficacy. Hence, the present study focuses to evaluate the potential ameliorative effects of Allium sativum (AS) against Deltamethrin (DLM) induced toxicity in hepatic tissues of male mice of Swiss strain (Mus musculus). Animals were divided into seven different experimental groups viz. Control, Vehicle treated (peanut oil), DLM low dose treated (3 mg/kg b.wt.), DLM high dose treated (6 mg/kg b.wt), control + AS, DLM low dose + AS and DLM high dose + AS. Various bio-chemical indices and gravimetric parameters were assessed at durations of 14 and 21 days. Results revealed that in experimental (DLM treated) groups parameters like total body weight, liver weight, protein content as well as the activity of enzymes like SDH, ALKpase, ACPase and ATPase were found to be reduced in a dose and duration dependent manner, whereas cholesterol level in the hepatic tissue was found to be elevated. Moreover, these altered parameters were significantly recovered when AS (200mg/kg body weight) was supplemented along with DLM and the observed recovery was comparable to control values.
A Survey on “Combination Strategies in Abdominal Multi-Atlas Image Segmentation”

-The segmentation of organs like the liver, pancreas, and kidneys on abdominal computed tomography (CT) scans can form an input to computer aided diagnosis (CAD) frameworks and laparoscopic surgery help. We show a typical, completely computerized procedure for multi-organ division of stomach figured tomography (CT) checks. Many existing techniques are particular to the segmentation of individual organs and fight to deal with the inconstancy of the shape and position of stomach organs. The strategy depends on level set registration, a system broadly utilized in brain imaging. The acquired probabilistic atlases are used in a graph-cuts based model to obtain a final segmentation of a structure of interest that incorporates high-level spatial requirements.
in Computer

-Document clustering, one of the traditional data mining techniques, is an unsupervised learning paradigm where clustering methods try to identify inherent grouping of the text documents.The importance of document clustering emerges from the massive volumes of textual documents created. Also, with more and more development of information technology, data set in many domains is reaching beyond peta-scale; making it difficult to work with the document clustering algorithms in central site and leading to the need of increasing the computational requirements. The concept of distributed computing thus; is explored for document clustering giving rise to distributed document clustering. Here, we propose distributed document clustering usingHadoop and MapReduce. We implemented K-means and tested on single node and then modified the map, reduce functions to run over cluster of three machines. We tested on two datasets consisting of 20000 documents (20-NewsGroups) and 21578 documents (Reuters-21578). The results show that timing requirement for clustering reduces with addition of nodes in the cluster .
Development of an acidic / neutral antibody flow-through polishing step using salt-tolerant anion exchange chromatography

2015 For ‘acidic’ (pI < 7.0) or ‘neutral’ antibodies (pI: 7.0–8.0), it is challenging to operate traditional anion exchange chromatography in a product flow-through mode to achieve adequate clearance of HCP, DNA, leached ProA, HMW and viruses while maintaining high process yield. In this study, the authors developed a scalable mAb polishing step using a new salt tolerant chromatographic resin. Utilizing a combination of high-throughput condition screening in 96-well plates and optimization in smallscale column models, a polishing step was developed that demonstrated high process yield and efficient clearance of impurities for multiple acidic or neutral antibodies. Pilot scale production demonstrated scalability of the step. This polishing step can be easily integrated into most current Protein A/AEX two-column antibody purification platforms.
Improved Autonomous Network Reconfiguration System

— Wireless mesh networks (WMNs) are new developing technology in wireless networks and has a variety of applications. However during their life period, multi-hop wireless mesh networks which experience frequent link failures caused by channel interference from other collocated wireless networks, dynamic obstacles like Bluetooth, and/or application bandwidth demands . By this link failures the information transfer can be lost so the quality of communication cannot be achieved and cause severe performance degradation in WMNs. Sometimes for their permanent recovery, it requires expensive manual network management . This paper presents an improved autonomous network reconfiguration system (IARS) that enable a multi-radio WMN to autonomously recover from local link failure to preserve network performance. Based on current channel assignment and radio association, IARS first create some feasible local reconfiguration plans to recover from link failure. Next, based on that plans the system cooperatively reconfigures network setting among local mesh router. In addition, to strengthen WMNs performance, IARS decouples network reconfiguration from flow assignment and routing. In WMNs a threshold value is set for every node. When a node want to transmit data in the form of a packet from source to destination, it verify threshold value of each node, whether it reach its limit or not. When it reaches its limit, node choose another node to send data . It choose it route with minimum path cost value and minimum delay time, higher throughput. With this consideration, packet loss will be less when compared to ARS system.
Finding Optimal Attack Path Using Attack Graphs: A Survey

— As the traditional methods, the result of vulnerability scanning can’t directly reflect complex attack routes existing in network, so the concept of attack graph comes. After analyzing host computer, devices link relation and the characteristic of attack, the model of network security status was built. Attack graphs are one of the important tools for analyzing security. A lot of research has been done on issues such as scalable and time efficient ways of generation of attack graphs. The intent of this paper is to study different ways to generate an attack graph and to provide future scope for research on these attack graphs.
A Comparative study of Proximity-Coupled Multiband Microstrip Antenna and Multimode Reduced Surface Wave Antenna

This paper shows the comparative study of proximity-coupled feed, used for a multiband microstrip antenna (MMA) and multimode reduced surface-wave antenna based on the shorted-annular-ring reduced-surface-wave (SAR-RSW) element and the inverted-SAR-RSW ((ISAR-RSW) element. Microstrip antenna operates in four bands WiMAX (3.3–3.7 GHz), LTE2300 (2300–2400 MHz), Bluetooth (2400–2485 MHz), and WLAN (5.15–5.35 GHz, 5.725–5.825 GHz). Microstrip antenna has excellent radiation features along with a steady gain over the operating bands. Multimode reducedsurface-wave antenna has a reduced return-loss bandwidth of less than 10-dB. Its range of operation is 1.164–1.255 and 1.552–1.610 GHz, a 3-dB axial-ratio bandwidth from 1.16 to 1.26 GHz and from 1.54 to 1.61 GHz. It produces a larger than 7-dBi gain in the entire operating band. To increase the impedance bandwidth, the multimode reduced-surface-wave antenna implements the proximity-coupled probe feeds. In order to restrain the mutual coupling between the SAR-RSW and ISAR-RSW elements, the defected ground structure bandrejection filters are implemented.
Do non-clostridial anaerobic bacteria cause of acute pyelonephritis in ureter obstruction?

The problem of etiology and pathogenesis of acute obstructive pyelonephritis remains an outstanding issue in modern urology. The infectious nature of acute destructive renal processes presently remains disputed. Etiologic agents of pyelonephritis may be both gram-negative and gram-positive opportunistic bacteria, the majority of which is part of normal human microflora. Presently, several publications delegated that role to non-clostridial anaerobic microorganisms, found in tissue substrates in as much as 99.0 % of cases. But their contribution to the etiology and pathogenesis of urinary tract infections is presently not sufficiently investigated. The experiment studies the morphologic specifics of acute obstructive pyelonephritis caused by various taxa of non-clostridia anaerobic bacteria. The data obtained changed the existing views on the detection and influence of said group of microorganisms upon the course of acute pyelonephritis in ureter obstruction.
Performance Evaluation using Adaptive Playout Buffer Algorithm in Voice Communication Over IP (VOIP)

— Real time voice communication is a major challenge in today’s internet demand for better Quality of Service. The communication quality is reduced by unnecessary delay and jitter. This paper describes an understanding of threats in Voice communication over IP (VOIP) and how Real Time Protocol (RTP) works in conjunction with Real Time Control Protocol (RTCP). RTCP packet header and delay measurement issues are analyzed with transmission interval and delay of the packets at the receiver end. Further, the end-to-end control of the timestamp in RTP and RTCP is evaluated. An adaptive playout buffering scheme is proposed to improve real-time voice communication over IP networks. Simulation results shows that the tradeoff between buffering delay and late loss can be improved significantly.
Design and Development of Perturb & Observe MPPT Technique for Solar PV based Energy Conversion System

The use of solar PV based energy conversion system is becoming very common. This energy conversion system still faces the challenge of low efficiency. It becomes essential to extract maximum power from solar PV (Photovoltaic) under all ambient conditions. Perturb & Observe (P&O) is one of the Maximum Power Point Tracking (MPPT) technique is used to achieve this task. The main objective of this work is to design and develop P&O mppt for solar PV system and check its performance under change load condition. The simulation work is done using PSIM simulation software. A prototype hardware is made in the lab. A buck DC – DC converter is used to implement P&O MPPT technique. The convergence time and tracking factor is evaluated and compared with simulation result.
Volatile Organic Compounds as Novel Markers for the Detection of Bacterial

Bacterial volatile organic compounds (VOCs) have been considered as sensitive and specific biomarkers for bacterial detection in human specimens and culture media. The possibility of using VOCs markers as one of the largest groups of bacterial metabolites would open a new frontier for developing more efficient techniques in the diagnosis of bacterial infections. This review will discuss the current published theory and data regarding the use of bacterial VOCs as markers in bacterial infections.
Changes of Neurofilament Content of Neurons as Consequences of Double- Strand DNA Breaks in Aging

Neurofilaments are the major structural proteins of neurons. Since DNA damage and repair are important factors in the transcriptional process the present study was aimed to examine age-related changes of Neurofilaments and double-strand DNA breaks in the neuronal preparations from 3 days, 3 months and 30 months rat brain. The relative integrity of the cells was confirmed by lactate dehydrogenase activity. The concentrations of neurofilament in the frozen-thawed cells were measured by enzyme-linked immunosorbent assay. The rate of double-strand DNA breaks was determined directly using an ethidium bromide solution as a binding fluorescent dye. The activity of neuronal lactate dehydrogenase activity was similar for all ages. The neurofilament content of neurons increased during development of rat brain and decreased in the neuronal preparations of aging rats, whereas the amount of double-strand DNA breaks increased only in the neurons of aging animals. The opposite relationship between the amount of doublestrand DNA breaks and the neurofilament content of the neurons in aging is consistent with the susceptibility of the neuronal DNA integrity in aging brain. It is suggested that the decrease of the neurofilament content of the neurons may be a causative factor of neuronal DNA damage in aging.
Quantitative Structure Activity Relationships for Carboxamides and Related Compounds Active on Aedes aegypti Adult Females

Aedes aegypti mosquitoes are important vectors in the transmission of severe diseases responsible for million deaths per year. Intensive use of insecticides results in environmental damages and induced resistance in mosquitoes. Search for new molecules devoid of detrimental side effects is therefore an urgent need. In this context, we derived QSAR models for evaluating the acute toxicity of 74 carboxamides and related chemicals to females of Ae. aegypti. These models based on PaDEL, 2D topological descriptors or CODESSA, 2D/3D geometrical and quantum variables, involved multilinear regression (MLR), and various machine learning methods namely support vector machine (SVM), projection pursuit regression (PPR) and artificial neural network (ANN). We considered first the full dataset, and then, a more homogeneous, reduced set of 50 compounds with non-conjugated carbonyl. In all cases, for data fitting and leave-one-out cross-validation, satisfactory results were attained. Good performance was also obtained for extended validation sets. Generally speaking, the modeling methods were broadly equivalent. PaDEL 2D descriptors worked better than 2D/3D CODESSA descriptors. A hybrid model combining the two descriptor sets gave improved results. Setting such QSAR models, linking activity to structural features of examined chemicals, will be of interest for prioritizing experimental tests on new candidates, and evaluate their toxicity and potential synergist effects.
PHOSPHODIESTERASE INHIBITORS: THEIR ROLE AND IMPLICATIONS

Phosphodiesterase (PDE) isoenzymes catalyze the inactivation of intracellular mediators of signal transduction such as cAMP and cGMP and thus have pivotal roles in cellular functions. PDE inhibitors such as theophylline have been employed as anti-asthmatics since decades and numerous novel selective PDE inhibitors are currently being investigated for the treatment of diseases such as Alzheimer’s disease, erectile dysfunction and many others. This review attempts to elucidate the pharmacology, applications and recent developments in research on PDE inhibitors as pharmacological agents.
Elliptical Iris Detection using Morphological Operations

— This paper presents a method to detect an iris to operate in 3D coordinate system. As per projective geometry, circle in 3D is projected as an ellipse in 2D. Hence, iris is detected as an ellipse instead of a circle. Morphological operations of light computations are used to detect an iris, which reduces time to detect an iris. Eye images with high resolution provide more number of pixels giving accuracy. Such detected ellipse can be further used to map to a circle in 3D using calibrated camera.
Distribution of P16 Promoter Hypermethylation in Male/Female Colorectal Cancer Patients of Kashmir Valley

Colorectal cancer (CRC) being the commonest cancer is the major cause of mortality and morbidity worldwide. It is commonly known as bowel cancer and is the third most common cause of cancerrelated deaths in the western world. Colorectal cancer has been reported to show geographical variation in its incidence, even within areas of ethnic homogeneity. Colorectal cancer development and progression is dictated by series of alterations in genes such as tumor suppressor genes, DNA repair genes, oncogenes and others. The aim of this study was to analyse the distribution of promoter hypermethylation of CpG islands of p16 gene in male/female colorectal cancer patients of Kashmiri origin. The study was a case-control study. DNA was extracted from all the samples and was modified using bisulphite modification kit. Methylation-specific polymerase chain reaction was used for the analysis of the promoter hypermethylation status of p16 gene. The epigenetic analysis revealed different p16 promoter hypermethylation profile in male and female colorectal cancer patients of Kashmir Valley. However, in both cases association of promoter hypermethylation with colorectal cancer was found to be significant. Occurrence of p16 promoter hypermethylation was found to be unequally distributed in males and females with more frequency in males than in females but the difference was not statistically significant(P =0.7635).
Spatial Item Recommendation using collaborative filtering

: In the development of location-based social networks (LBSNs), spatial items have recommended and that has become an important way of helping users discover interesting locations to increase their engagement with location-based services. Although human movement exhibits sequential patterns in LBSNs, most current studies on spatial item recommendations do not consider the sequential influence of locations. we propose a sequential personalized spatial item recommendation framework (SPORE) which introduces a novel latent variable topic-region to model and fuse sequential influence with personal interest in the latent and exponential space. The advantages of modeling the sequential effect at the topic-region level include a significantly reduced prediction space, an effective alleviation of data sparsity and a direct expression of the semantic meaning of users’ spatial activities. We evaluate the performance of SPORE on two real datasets and one large-scale synthetic dataset. The results demonstrate a significant improvement in SPORE’s ability to recommend spatial items, in terms of both effectiveness and efficiency, compared with the state-of-the-art methods.
Artificial Neural Network-Based Classification System for Lung Nodules on Computed Tomography Scans

: The paper describes a neural-network-based system for the computer aided detection of lung nodules in chest radiograms. In recent years the image processing mechanisms are used widely in several medical areas for improving earlier detection and treatment stages, in which the time factor is very important to discover the disease in the patient as possible as fast, especially in various cancer types such as the lung cancer, breast cancer. Lung cancer is the second most commonly diagnosed cancer in world. Our approach is based on multiscale processing and artificial neural networks (ANNs). The automated Computer Aided Diagnosing (CAD) system is proposed in this paper for detection of lung cancer form the analysis of computed tomography images. In this paper we represent artifial neural network based lungs cancer detection system using CT images.
Face Recognition System Using Wavelet Normalization

: Facial recognition is an approach or a system to identify any individual. It can done by analysing and pattern comparison. It is mainly used to provide the security for an individual. It faces some difficulty in case of different illumination. To overcome this, invariant illusion algorithm is used in this paper. Due to this,our system can work well under a different circumstances. It followed by three stages; preprocessing, a feature extraction, and recognition. Wavelet-based normalisation technique lightens the dark and highlight areas of the face image. To imitate the human visual system and examine a face image from the internal facial features to the external facial shapes, multiple face models along with complementary features are used. Features are extracted using Fourier transform. To classify the image, a simple metric Euclidean Distance is used.
Text Summarization Using Fuzzy Logic

— In this new generation, where the tremendous information is available on the internet, it is difficult to extract the information quickly and most efficiently. There are so many text materials available on the internet, in order to extract the most relevant information from it, we need a good mechanism . This problem is solved by the Automatic Text Summarization mechanism. “Text Summarization” is a process of creating a shorter version of original text that contains the important information. Text summarization can be broadly classified into two types: Extraction and Abstraction. This paper focuses on the Fuzzy logic Extraction approach for text summarization