Miracle-dz/UniFAR-FTUs huggingface dataset:
Static Hand Gesture Recognition based on DWT Feature Extraction Technique

Every day number of images are generated which implies the necessity to classify, organise and access them using an easy, faster and efficient way. The classification of images into semantic categories is a challenging and important problem now days. Thus hand gesture image detection and recognition is also difficult task. In this paper a novel system which can be used for sign language recognition and interaction with an application or videogame via hand gestures is introduced. This proposed system elucidate framework for vision based recognition of American sign language alphabets from static hand gesture images using Discrete Wavelet Transform based feature extraction technique and Minimum distance vector classifier Daubenchies Wavelet basis function is selected for performing three level two dimensional wavelet decomposition of input static hand gesture image and 7 features are extracted for each image. In the training stage feature vectors are calculated for every training images creating database for classification. In the testing stage input image features are compared with stored trained image features using minimum distance vector classifier.
Generic System Forensics Investigation Model

: The increasing criminal activities exploitation digital data because the suggests that or targets warrant for a structured manner in addressing them. Since 1984 once a formalized method been introduced, a good variety of recent and improved System rhetorical investigation processes are developed. during this paper, we tend to reviewed some designated investigation processes that are made throughout the years and so known the usually shared processes. Hopefully, with the identification of the usually sherd method, it'd build it easier for the new users to know the processes and conjointly to function the fundamental underlying construct for the event of a brand new set of processes. supported the usually shared processes, we tend to planned a generic System forensics investigation model, referred to as GCFIM.
3D Convolutional Neural Network for Object Recognition

3D Object recognition is an important task in computer vision applications. After the success of convolutional neural networks for object recognition in 2D images, many researchers have designed convolution neural network (CNN) for 3D object recognition. The state of art methods provide favourable results. However, the availability of large/dynamic 3D dataset and computational complexity of CNN are the biggest challenge in 3D CNN. In this paper, a model for object recognition problem using volumetric data representation has been proposed. The aim of this paper is to improve CNN architecture for volume based 3D objects. We implemented two separate CNN architectures and tested them on ModelNet datasets, which represent data in the form of CAD models. We compare our results with VoxNet, which is a state-of-art recognition method.
Sequential feedback from user session for finding effective personalized user search.

: In the recent scenario data searching on the web and extracting searching on the web is more tedious to find the best match and appropriate results. The organization of user results and navigations may help to improve the searching results. But the difficulty is the storage and arrangement of query clusters based on the semantic nature. The extracted data could be fine when the input query was matched with the web log and existing cluster. The problem in data retrieval is web content may specify with different meaning for a single word. To overcome the problems in existing user search goal analysis and data extraction, the proposed system provides an effective data extraction and log clustering and sequence identification based on the semantic modal. In order to provide better search and clustering experience SOC (Sequential Semantic Self Organizing Cluster) algorithm with feedback session modal has been applied. The proposed sequential feedback sessions based ranking algorithm utilizes the combination of query mining, matching and feedback analysis. Exiting analytical process for individual interest mining from personalized weblog is a tedious process, because the existing techniques considered only the “hits” based priority. The proposed system considers total number of hits, time spend by the user in a particular page and links. Additionally it performs the division technique, which is an effective technique concentrated by all websites to make the query cluster well. Effective search summarization with the use of semantic data analysis also introduced to reduce the user search effort. Implementing these algorithms with an effective searching process hopefully provides better output than the existing system.
Knn Search on Road Networks by Incorporating Social Influence

- The existing system incorporates road network and social network. Independent Cascade (IC) model in social network is applied to deﬁne social inﬂuence. One of the challenge was to speed up the computation of the social inﬂuence over large road and social networks. To address this challenge, three efﬁcient index-based search algorithms was proposed, i
Modelling Changes in Soil Chemical Parameters of Obio-Akpor, Rivers State, Nigeria using Geographic Information System

This research is to show the changes in soil quality, land use, land cover, soil physicochemical parameters and morphology. Satellite data and Geographic Information System (GIS) were used to investigate the soil changes in physicochemical parameters, land surveying and satellite data (Landsat TM and Arcview GIS 3.3) were used in GIS to explain the landforms and correlation between landforms, soil physicochemical properties and the morphological characteristics. The area was dominated by flood plain and marine plain of 58.24% while the water bodies and urban exhibit 41.76%, and the physicochemical properties were mapped. The morphological characteristic showed the textural class to comprise of silty loam, clay loam, sandy clay loam, sandy loam, and loamy sand while the soil structure are weak, strong and medium angular blocky and sub angular blocky with its consistency being non sticky due to the presence of abundant roots and some plastic in a non-root area. There is a prolonged distribution of the constraints of productivity all over the region due to the changes in the soil and land use settlement which could be due to the oil exploration in the region.
A Conceptual Framework On Knowledge Sharing, Intrinsic Motivation, High-Performance Work System, Authentic Leadership And Creativity

The aim of this research was to establish relationship among intrinsic motivation, authentic leadership and high-performance work system (HPWS) on university faculty members with the mediating role of knowledge sharing. Previous studies showed that authentic leadership, intrinsic motivation, and HPWS had a significant effect on faculty member‘s creativity. Theory and past studies also supported the idea that knowledge sharing mediates the relationship between HPWS, authentic leadership, intrinsic motivation and employee‘s creativity.
Resequencing Analysis for Time-Varying and Time-Invariant Channels Using ARQ Protocols

: In a parallel multichannel data communication system the stop-and-wait Automatic Repeat Request (ARQ) protocol for parallel channels with an in-sequence delivery guarantee is used for error control. Under the assumption that all channels have the same transmission rate but possibly different time-invariant error rates, we evaluate the probability generating function of the resequencing buffer occupancy and the probability mass function of the resequencing delay. Then, by assuming the Gilbert–Elliott model for each channel the probability mass functions of the resequencing buffer occupancy and the resequencing delay for time-invariant channels are computed. From numerical and simulation results, the mean resequencing buffer occupancy and the mean resequencing delay as functions of system parameters are analyzed. The modeling technique and analytical approach used in this paper can be applied to the performance evaluation of other ARQ protocols over multiple time-varying channels.
Automatic Extraction of Video Object using Hybrid Approach

— Saliency-based object detection approach has attracted much attention in recent years. However, computational modeling still remains a challenge. This paper aims to automatically detect foreground object of interest from a rapid scene using the combination of Saliency features, skin value and comparison of eigenfaces. The proposed method utilizes the saliency information from the input video to detect the object. Once features are extracted, detection is based on skin values and eigenfaces template matching methods. Eigenfaces technique is a more powerful yet simple method to recognize the face. This method is able to produce qualitatively satisfied video object detection result. It is an approach to recognize the person by comparing characteristics of the face to those of known individuals is described.
Antioxidant Activities and Thin Layer Chromatographic Analysis of Aqueous Extract of Barks of Cinnamomum

Objective: The objective of the present study was to investigate phytochemical constituents, free radical scavenging activities and TLC of the aqueous extract of barks of Cinnamomum zeylanicum Blume. Methodology: The qualitative and quantitative analyses were carried out for the aqueous extract of barks of C. zeylanicum using standard procedures. The antioxidant activities were carried out by DPPH, ABTS, OH and NO radical scavenging assay as well as Fe reducing power and phosphomolybdenum reduction assay methods. The aqueous extract of barks of C. zeylanicum showed good radical scavenging as well as reducing power activities. Results: The Phytochemical estimation revealed that the concentration of phenols and flavonoids in the aqueous extract of barks of C. zeylanicum were 42.3 ± 2.96 mg/g and 5.81 ± 0.40 mg/g respectively. The maximum percentage of DPPH, OH, ABTS and NO radicals inhibition were 84.39 ± 5.90, 54.84 ± 3.83, 67.06 ± 4.69, and 55.61 ± 3.89 respectively. Conclusion: The results revealed that the aqueous extract of barks of C. zeylanicum significantly inhibits the radicals and the antioxidant activity increases with increasing concentration.
Tag Completion using Annotation for Reliable Image Retrieval

— Image sharing is much popular in worldwide, so it is vast to distinguish such images in efficient way based on their tags. User given tags are not relative, consistent and complete. They are noisy, missing and dissimilar to image content. User-provided textual tags of web images are widely utilized for facilitating image management and retrieval. It results into performance degradations. The goal of this work is to develop a probabilistic model to take into account the dependencies between keywords so as to provide superior image search, retrieval, more precise, corrected annotations. The main findings suggest that, under certain conditions, taking into account keyword completion, coupled with an efficient method to search over sets of tags is an effective method to increase annotation accuracy. A schematic is developed to illustrate the dynamic relationship between the motivations and their contexts. The schema will make an important contribution by annotation and completing tags what is an otherwise completely unknown area of image retrieval. This study based on various techniques which are used to complete the missing tags and correct the noisy tags for given images thereby improving the retrieval performance.
Obtaining Approximation with Data Cube using Map-Reduce

— Data mining is a field that has an important contribution to data analysis, discovery of new meaningful knowledge, and autonomous decision making. Whereas, the rough set theory offers a viable approach for decision rule extraction from data. With the data cube we tried to put data in multidimensional way and accessed that data via map reduce. The adequate quantity or supply of data, coupled with the need for powerful data analysis tools, i.e. where data is rich but information is in poor situation. The proposed algorithm is been compared with other different rough set approximation approaches. Our algorithm to achieve approximation for decision rules has better performance. This proposed algorithm has been more efficient to obtain approximation
A Dynamic Classifier using Decision Tree Algorithm

— Every organization handles a vast amount of data. This data can be of different types such as sales, employee, customer, historical etc. The data often contains undiscovered patterns which can be useful if discovered and can be applied to future data for better efficiency. For the same, a dynamic classifier can be developed which can predict a certain attribute of future data by studying past data using concepts of Data Mining under Classification. This paper proposes the idea of such a classifier which can be built independently and without Bulky Business Intelligence software to effectively forecast future occurrences of any phenomena
LET IT GO! THE MEDIATING ROLE OF NEGATIVE AFFECT IN THE RELATIONSHIP BETWEEN ACCEPTANCE AND WORK ENGAGEMENT

For the past few years, researchers have paid a great deal of attention to antecedent variables of work engagement, such as job characteristics, organizational support, core self-identity, and self-efficacy, and empirical studies of acceptance have been rather rare and incomplete. Based on the job demands–resources model and affective event theory, the present study’s authors aimed to examine the role of affect in the link between acceptance and work engagement. A cross-sectional study was carried out, using a valid sample of 337 full-time Chinese employees. Pearson correlation analysis and structural equation modelling were used to examine the relationships between acceptance, negative affect, positive affect, and work engagement in full-time employees. Results suggested that acceptance was negatively associated with negative affect and was positively related to both positive affect and work engagement. Furthermore, negative affect mediated the effect of acceptance on work engagement. In conclusion, this study determined that acceptance contains affective, resource-conserving, and motivational benefits for work engagement.
Synonymous Mutations in rpsT Lead to Ribosomal Assembly Defects That Can Be Compensated by Mutations in fis and rpoA

We previously described how four deleterious synonymous mutations in the Salmonella enterica rpsT gene (encoding ribosomal protein S20) result in low S20 levels that can be compensated by mutations that restore [S20]. Here, we have further studied the cause for the deleterious effects of S20 deficiency and found that the S20 mutants were also deficient in four other 30S proteins (S1, S2, S12, and S21), which is likely due to an assembly defect of the S20 deficient 30S subunits. We examined the compensatory effect by six additional mutations affecting the global regulator Fis and the C-terminal domain of the α subunit of RNA polymerase (encoded by rpoA). The fis and rpoA mutations restored the S20 levels, concomitantly restoring the assembly defect and the levels of S1, S2, S12, and S21. These results illustrate the complexity of compensatory evolution and how the negative effects of deleterious mutations can be suppressed by a multitude of mechanisms. Additionally, we found that the mutations in fis and rpoA caused reduced expression of other ribosomal components. Notably, some of the fis mutations and the rpoA mutation corrected the fitness of the rpsT mutants to wild-type levels, although expression of other ribosomal components was reduced compared to wild-type. This finding raises new questions regarding the relation between translation capacity and growth rate.
Correlation Analysis: The Bootstrap Approach

For a general class of problems, the bootstrap method of resampling is one of the possible methods of constructing tests of significance. The sampling distribution of a test statistic for an experiment compiled by the bootstrap approach requires no reference to the population distribution and therefore no requirement that it should conform to a mathematically definable frequency distribution. Algorithms for the bootstrap distribution of correlation coefficients are presented and implemented. As an illustrative example, a critical value for Pearson’s product moment correlation coefficients and Spearman’s rank correlation coefficients are produced for a given set of data.
Quantifying RNA Editing in Deep Transcriptome Datasets

Massive transcriptome sequencing through the RNAseq technology has enabled quantitative transcriptome-wide investigation of co-/post-transcriptional mechanisms such as alternative splicing and RNA editing. The latter is abundant in human transcriptomes in which million adenosines are deaminated into inosines by the ADAR enzymes. RNA editing modulates the innate immune response and its deregulation has been associated with different human diseases including autoimmune and inflammatory pathologies, neurodegenerative and psychiatric disorders, and tumors. Accurate profiling of RNA editing using deep transcriptome data is still a challenge, and the results depend strongly on processing and alignment steps taken. Accurate calling of the inosinome repertoire, however, is required to reliably quantify RNA editing and, in turn, investigate its biological and functional role across multiple samples. Using real RNAseq data, we demonstrate the impact of different bioinformatics steps on RNA editing detection and describe the main metrics to quantify its level of activity.
Report of Initial Experience with a Novel Extracellular Matrix MaterialDerived from Porcine Urinary Bladder to Treat Patients with Vesico-Vaginal Fistula

Abstract Our objective was to report our initial experience with extracellular matrix material derived from porcine urinary bladder, MatriStem, in patients with vesico vaginal fistula (VVF). Materials and methods: For our retrospective review, we obtained the medical records of 40 consecutive patients who were seen for VVF during our 2 years study period. All patients underwent a thorough evaluation, including history, physical, examination, computed tomography urography, and single-dye pad tests. The cases were treated with two different kinds of MatriStem to repair VVF. Results: In 6 patients, the MatriStem procedure was performed by robotic surgery, in these cases a MatriStem graft were used; in 3 cases we injected micronized particles of MatriStem via cystoscopy and vaginoscopy. The mean follow-up 7.25 months. We observed that 75% of the cases had no fistula drainage per the vagina and progressed to full healing. Conclusion: MatriStem in our early results seem to have a role in effectively treating VVF. Further investigation and long term follow up is needed to establish MatriStem as An alternative treatment for VVF patients.
Using Science Museum Curator’s Knowledge to Create Astronomy Educational Content

The creation of astronomy educational content is sometimes a difficult task, especially in alternative learning environments such as a science museum. Many people visiting science museums have an interest in astronomy but are not specialists in this area. It should be interesting to find out if museum curators could make the knowledge that is present in museums more relevant to people's daily lives, thus making it easier to understand. General astronomy applications can yield really beautiful and precise sky images; however, the images are usually too complex to non-astronomy specialists or beginners. Therefore, it is difficult to use the applications' output images for educational purposes without spending a lot of time editing them. To solve this problem, the idea in this research study was to create an application that allows museum curators to apply the knowledge they already have through, and more quickly edit the images in an effort to make them more intelligible. After application developers worked with museum curators to develop and test such a system, the curators could create the educational content at least two times faster than they could using regular astronomy applications and image editors, and they were also able to easily create a content database and update the content.
PET / MRI : Current Prospects and Challenges Authors

PET/MRI is a hybrid imaging technology, increasingly being used in research applications as well as in clinical practice. The combined PET/MRI system is the latest in fusion imaging. The device provides specific molecular information related to cell surface receptors and enzymes and gene expression with high sensitivity, delivered by PET. Simultaneously, it also captures important anatomical data, superior soft tissue contrast, spatial resolution and information about perfusion and permeability, shown by MRI. Therefore it proves to be a highly sensitive and evaluator clinical investigation technique. PET/MRI is an expensive technology and its availability is extremely limited across the world. It still need further technical and clinical upgradations for better prospects and prove beneficiary towards the patients. However, initial experience with this new imaging system is very promising for oncology, cardiac imaging and neuro imaging. Not only pediatric and young oncologic patients but pregnant women would also be benefitted from PET/MRI. There are potential competitive advantages of PET/MRI over PET/CT. But, it is struggling to show its superiority over its arch-rival PET/CT in many cases. The aim of this paper is to review the current status of PET/MRI in clinical applications and its challenges.
Exploring the protective effect of silymarin against flutamide-induced hepatotoxicity in male rats

Article history Received: 2 Oct, 2016 Revised: 19 Oct, 2016 Accepted: 21 Oct, 2016 Abstract The current study was designed to explore the protective impact of silymarin (SIL) against the hepatotoxicity induced by daily treatment with flutamide (FLU), for one month, in intact male rats. Two different doses of FLU, one was low and corresponds to the human therapeutic dose (10 mg/kg) and the other was high and corresponds to 1⁄2 lowest lethal dose (500 mg/kg) were applied. Obtained results showed that oral administration of FLU in male rats significantly increased hepatic malonic dialdehyde (MDA), and markedly decreased hepatic reduced glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx) and glutathione-stranseferase (GST). In parallel, activities of alanine aminotranseferase (ALT), aspartate aminotranseferase (AST) and alkaline phosphatase (ALP), and level of total bilirubin in serum were significantly elevated; while serum total proteins, albumin and globulin, and hepatic total proteins were decreased in FLU-treated animals. Also, significant increases in serum and liver contents of total lipids (TL), total cholesterol (TC) and triglycerides (TG), and serum low density lipoproteins-cholesterol (LDL-c), which accompanied with decrease in serum level of high density lipoproteinscholesterol (HDL-c) following administration of FLU. The adverse effects of FLU on measured parameters appeared to be dose-dependent. Treatment with SIL (50 mg/kg) in rats given FLU (10 mg or 500 mg/kg) greatly improved the levels of investigated biomarkers of liver status. However, the beneficial effect of SIL was more remarkable in rats receiving FLU at a dose of 10 mg/kg. Obtained biochemical changes induced by the two used doses of FLU and the ameliorative impact of SIL were confirmed by histopathological examinations of liver sections of treated rats. In conclusion, SIL can be used effectively in the protection against hepatotoxicity induced by FLU.
The Nexus between Fiscal Decentralization and Economic Growth: Evidence from Sub-National Governments in India

Panel Vector Auto Regression is used to examine the impact of financial decentralization on economic growth in seventeen sub-national governments (SNGs) in India taking data from 2000-01 to 2014-15. We find the positive impact of decentralization on the economic growth of SNGs with feedback effect.