Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-intensive Scheduling

In many modern data management scenarios, we encounter tasks, operations or computational phases that are data-intensive where the sheer volume of data proves to be overwhelming to handle and becomes a performance bottleneck. For data-intensive tasks, the bottleneck is data loading, where the cost of loading data into memory is more significant than the cost of actual computation. For data-intensive shuffling, the bottleneck is data transfer, where intermediate data are scattered and shuffled for further processing. This thesis addresses two data-intensive scheduling problems: (1) multiprocessor scheduling for data-intensive tasks to reduce redundant data loading; (2) reducer scheduling for data-intensive shuffling to reduce redundant data communication. For data-intensive tasks, we focus on workloads with precedence constraints of data dependencies, which are common in various applications such as data analytics and ETL processing. These workloads are often known in advance, are presented as directed acyclic graphs (DAG), and are data-intensive and sensitive to cache misses. We solve the problem of scheduling DAGs of data-intensive tasks on multiple processors or machines, in order to minimize execution time. To do so, we propose scheduling algorithms that take cache misses into account. Simulations and an experimental evaluation using a Spark cluster demonstrate the advantages of our solutions in terms of workload completion time. For data-intensive shuffling, we focus on MapReduce-style processing. Communication overhead is incurred in the Shuffle stage which sends intermediate results from mappers to reducers. We solve this problem: given a collection of mapper outputs (intermediate key-value pairs) and a partitioning of this collection among the reducers, which node should each reducer run on to minimize data transfer? We reduce two natural formulations of this problem to optimization problems for which polynomial solutions exist. We show that our techniques can cut communication costs by 50 percent or more compared to Hadoop’s default reducer placement, which leads to lower network utilization and faster MapReduce job runtimes.
PII: S0167-2789(00)00216-5

In a delayed Hopfield neural network that is strongly connected with non-inhibitory interconnections , fast and inhibitory self-connections lead to global convergence to a unique equilibrium of the network. By applying monotone dynamical systems theory and an embedding technique, we prove that this conclusion remains true without the requirement of strong connectivity or non-inhibitory interconnections. © 2001 Elsevier Science B.V. All rights reserved.
Efficient Customer Churn Prediction Model Using Support Vector Machine with Particle Swarm Optimization

---Today, telecommunication market all over the world is facing a severe loss of revenue due to fierce competition and loss of potential customers. To keep the competitive advantages and acquire as many customers as possible, most operators invest a huge amount of revenue to expand their business in the very beginning. Customer Relationship Management (CRM) strategy helps an organization to improve the business processes and technology solutions around selling, marketing, and servicing functions across all customer touch-points. One of the important issues in customer relationship management is churn prediction. It aims at identifying potential churning customers based on past information and prior behaviors. In this proposed work the data mining techniques were utilized for efficient churn prediction. Here the normalized k means algorithm is utilized for dataset preprocessing. Then the attributes are selected from preprocessed image by utilizing minimum Redundancy and Maximum Relevance (mRMR) approach. It tends to select attributes with a high correlation with the class (output) and a low correlation between themselves. Based on the selected attributes the customer churn separation or prediction is examined with the help of Support Vector Machine with Particle Swarm Optimization (SVM with PSO). In order to optimize the hyper parameters of SVM the PSO is used. And also it overcome the local optimal solution problem and obtains higher classification accuracy. The experimental results show that the proposed system achieves better performance compared with the existing system in terms of accuracy, true positive rate, false positive rate and processing time.
ANTIMICROBIAL AND ANTICANCER ACTIVITY OF METHANOLIC EXTRACT OF DRIED MULBERRY FRUITS AND LEAVES ILLUSTRATED WITH THEIR CHEMICAL COMPOSITION

This study was undertaken to determine some selected nutritive chemical composition of dried mulberry fruits and leaves (proximate composition: moisture, ash, fiber, protein, fat and carbohydrate, amino acids and minerals) and evaluation of antimicrobial and anticancer potential of their methanolic extract. The results indicated that the leaves have more nutritious quality than the fruits. The dried mulberry leaves recorded higher content of ash, protein, fiber, amino acids and minerals than that in fruits while moisture and fat content were higher in fruits than in leaves. The carbohydrate content was slightly higher in fruits than in leaves. However, both of them were nutritionally rich. The antimicrobial effect of different concentrations (5, 10 and 15 mg/ml DMSO) of mulberry fruits and leaves extract on growth and survival of Staphylococcus aureus strain and Escherichia coli strain in vitro and in mulberry juice were evaluated. Both fruits and leaves extract have attenuated effect on both bacteria. The concentration, 15 mg/ml of mulberry fruits extract represent the optimum concentration for decreasing E. coli and Staph. aureus counts in liquid medium such paid to decreasing them from 5X10 10 and 5X10 12 to 14X10 2 and 4X10 5 cfu/ml respectively. The different concentrations (10 and 15 mg/ml) of fruits and leaves extract induced completely elimination of Staph. aureus from mulberry juice and reduction of E. coli from 5X10 10 to 4X10 2 and 3X10 3 cfu/ml respectively at concentration 15 mg/ml. The expression of p53 (tumor suppressor gene) from three types of cancer cell lines (Hep-2 (Larynx carcinoma), HepG2 (liver carcinoma) and CaCo2 (colorectal adenocarcinoma)) treated with fruits and leaves extract were evaluated to explore their anticancer effect. The results showed that the cancer cells treated with fruits and leaves extract were negative for p53 gene expression as the gene not detected comparing with positive cell control. The tested extracts were not anticancer agent.
Evaluation of the outcome of non-surgical root canal treatment performed at the student clinic, University of Tromsø

2 Introduction.4 Materials and Methods.5 Results.8 Discussion.10 Conclusion.15 Acknowledgement.15 References.16 Appendix 1.21 Appendix 2.23 Appendix 3.26
An integrated 6DoF video camera and system design

Designing a fully integrated 360° video camera supporting 6DoF head motion parallax requires overcoming many technical hurdles, including camera placement, optical design, sensor resolution, system calibration, real-time video capture, depth reconstruction, and real-time novel view synthesis. While there is a large body of work describing various system components, such as multi-view depth estimation, our paper is the first to describe a complete, reproducible system that considers the challenges arising when designing, building, and deploying a full end-to-end 6DoF video camera and playback environment. Our system includes a computational imaging software pipeline supporting online markerless calibration, high-quality reconstruction, and real-time streaming and rendering. Most of our exposition is based on a professional 16-camera configuration, which will be commercially available to film producers. However, our software pipeline is generic and can handle a variety of camera geometries and configurations. The entire calibration and reconstruction software pipeline along with example datasets is open sourced to encourage follow-up research in high-quality 6DoF video reconstruction and rendering 1.
DRONEVR: A virtual reality simulator for DroneOperator

In recent years, Unmanned Aerial Vehicle (UAV) has been used extensively in various applications from entertainment, virtual tourism to construction, mining, agriculture. Navigation, path planning, and image acquisition are the main tasks in administering these aerial devices in accordance with real-time object tracking for affordable aerial vehicles. Aircraft crash is one of the most critical issues due to the uncontrolled environment and signal loss that cause the aerial vehicle to hit the buildings on its returning mode. Furthermore, real-time image processing, such as object tracking, has not yet been exploited for a low-cost aerial vehicle. This paper proposes a prototype embedded in a Web-based application called DroneVR to mitigate the aforementioned issues. The virtual reality environment was reconstructed based on the real-world fly data (OpenStreetMap) in which path planning and navigation were carried out. Gaussian Mixture Model was used to extract foreground and detect a moving object, Kalman Filter method was then applied to predict and keep track of object’s motion. Perceived ease of use was investigated with a small sample size users to improve the simulator.
Explicitation in a Specialized Corpus Related to the Field of Environment: An Analysis of Strategies in English-French Translations

This article aims to present some findings of a study 1 on explicitation strategies in English-French translations of specialized texts related to the field of environment. The goal of the study is to identify the range of explicitation strategies, as well as analyzing and classifying them. For our research, we compiled a corpus of English-French environment texts. The texts were then aligned using the aligner LogiTerm Pro. Our work is based on that of Pápai (2004): her typology of explicitation strategies was used in our own analysis. We found that explicitation strategies occur at five levels. Our findings show that the number and variety of instances of explicitation are high in English-French translations of specialized texts in the field of the environment.
PROBABILISTIC SEISMIC HAZARD ANALYSIS FOR WARANGAL CONSIDERING SINGLE SEISMOGENIC ZONING

The estimation of probabilistic seismic hazard in low seismicity regions such as stable continental regions has to copeup with the difficulty in identification of active faults and with the low amount of available seismicity data. In this paper, an attempt is made to carry out comprehensive probabilistic seismic hazard analysis for low seismicity region like Warangal, South India. Warangal is the secondfastest growing city in Telangana state, after Hyderabad. The city is known for its heritage and in late 2014 was included in the Government of India's proposed HRIDAY Heritage City Development and Augmentation Yojana. A new earthquake catalogue for Warangal, with unified moment magnitude scale has been prepared. The earthquake catalogue compiled by Rao & Rao (1984), Srivastava & Ramachandran (1985), Jaiswal & Sinha (2007), International Seismological Centre and U.S Geological Survey were used for the analysis. A total of 389 earthquake events of magnitude (Mw>=3) spanning from time 1800 A.D. to 2015 A.D. were prepared before declustering. Declustering of earthquake events was performed by Z MAP software using Urhammer method. 111 events out of 389 were identified as dependent events. Catalogue completeness analysis has been carried out by CUVI and Stepp’s method on declustered catalogue. Seismic Hazard Analysis is carried out by considering the seismotectonic parameters of the study region covering a radius of 350 km with NIT Warangal (17.9808°N, 79.5328°E) as the center. Major faults and lineaments such as Latur Lineament , Kaddam fault , Kinnerasani-Godavari fault, Gundlakamma faults were identified as the sources of occurred earthquake events. The standard Cornell-McGuire method has 1 Nirbhay Narayan Singh, Civil Department, NIT Warangal, Warangal, India, nirbhay.mnnit@gmail.com 2 Deviprasad B S, Civil Department, IIT Madras, Chennai, India, deviprasad.bsg@gmail.com 3 Dr. P Hari Krishna,Civil Department, NIT Warangal, Warangal, India, phknitw@gmail.com 4 Dr. G. Kalyan Kumar, Civil Department, NIT Warangal, Warangal, India, kalyan@nitw.ac. in Nirbhay Narayan Singh, Deviprasad B S. , Dr. P. Hari Krishna, Dr. G. Kalyan Kumar been used for hazard computation considering single seismogenic zoning. Five attenuation relationships suggested by Raghu Kanth and Iyengar (2007), Abrahamson and Silva (1997), Ambraseys et al. (2005), Campbell and Bozorgnia (2003), Hwang and Huo (1997) are selected for calculation of PGA. Annual rate of exceedance of different time periods for Warangal has been evaluated by using the Gutenberg-Richter recurrence relationship. CRISIS 2007 Version 1.1, a computer program for computing seismic hazard, developed by Ordaz et. al., (2007) has been used for seismic hazard analysis. The frequency-intensity curves are generated by computing the annual probability of exceedance for a range of ground motion intensities. The uniform hazard spectra of acceleration and Spectrum-compatible acceleration timehistories have been obtained for different return periods and is compared with the IS 1893 code specified design response spectra.
An Empirical Estimation of the Rational Expectations Competitive Storage Model∗

This study estimates by Simulated Method of Moments (SMM), using price data alone, the commodity storage model following the standard competitive framework based on Williams and Wright (1991), a simple but intuitive economic model of price determination. Results show that the SMM estimator presents small bias and variance. However, particular attention may be paid to the choice of starting values, since restricting their choice to economically reasonable figures may not be a sufficient strategy to follow. In fact, whenever not accurately chosen they can eventually mislead parameter estimates. Finally, in efficiency terms the competing Pseudo-Maximum Likelihood (PML) estimator seems to perform better than this simulation estimator when considering the storage model framework. JEL classification: C15, B4, Q11.
Modelling of Energy Systems with High Integration of Renewable Energy Sources

This project examines the Nordic and the German energy systems using the energy model Balmorel. Two core scenarios in 2030 including additional RE capacities, interconnectors and EVs, are examined with and without the option of Balmorel to implement unit commitment to power plants, in order to include inflexibility in the systems and approach a more realistic representation of their operation. It will be researched what impacts will the different scenarios have to the energy generation, total system costs, electricity prices and the operation of the energy systems in an attempt to answer the following research question: “What are the differences when energy systems with high penetration of fluctuating renewable energy sources are modelled with and without unit commitment? ” The main findings of this project are that more fossil fuels, biomass and wind is used when UC is applied. Moreover, the total costs are increased when UC is applied, to some extent due to the additional start-up costs but mainly due to the raised fuel and CO2 costs. In addition, the electricity prices are increased and present high peaks, due to the operation of more expensive power plants in the UC. Furthermore, in the UC less curtailment of the wind is noticed. It is concluded by the author, that this study indicates that the simulations without UC provide a better representation of the actual operation of the today’s energy systems, since there is uncertainty of how the market will operate in the future and the simulations are carried out using current UC data.
MULTIFRACTAL ANALYSIS OF SEISMIC DATA FOR DELINEATING RESERVOIR FLUIDS

Oil and gas is at present the most important energy fuel in the world. Consumption of these resources has reached huge dimensions forcing companies to explore more and more potential sources of hydrocarbon reservoir. The established approaches for predicting reservoir fluids can be time-consuming and inaccurate. This paper describes the application of multifractal analysis on seismograms for delineation of reservoir fluids. Preliminary results show that the multifractal analysis on seismograms is able to delineate the reservoir fluids effectively. The sets of holder exponents and the singularity spectrum show that each reservoir fluid exhibits a unique value of singularity strength and spectrum. Effective delineation is an important step that will improve performance of oil and gas industry by reducing drilling uncertainties. More accurate seismic data processing and interpretation will help reservoir engineers to make a better decision concerning production plans.
The Factors Influencing on Online Store Selecting Intention for Purchasing Imported Products of Chinese Consumers

As China is going to be the next world’s leading retail markets which the biggest purchasing power over E-commerce market, international companies and investors thus interested in expanding its businesses to Chinese market. The present study is carried with the purpose to critically review and identify the gaps in current literature on cross-border e-commerce, to draw the relationship among online store image, trust towards online store and online store selecting intention. Five factors on store image were selected to be studied which are online store reputation, service, promotion, design, and products as independent variable, trust towards online store plays as mediator, and online store selecting intention as a dependent variable. The proposed conceptual model framework of the present study is expected to assist online store, marketers or related persons to understand the Chinese consumer’s behavioral intention in cross-border ecommerce. Also, the result can be used as a benchmark for future study with different context.
Purinergic P2Y2 Receptors Promote Neutrophil Infiltration and Hepatocyte Death in Mice with Acute Liver Injury

Background & Aims: During progression of liver disease, inflammation affects survival of hepatocytes. Endogenous release of ATP in the liver activates purinergic P2 receptors (P2R), which regulates inflammatory responses, but little is known about the roles of these processes in development of acute hepatitis. Methods: We induced acute hepatitis in C57BL/6 mice by intravenous injection of concanavalin A and then analyzed liver concentrations of ATP and expression of P2R. We assessed P2R knockout (P2Y2R) mice and C57BL/6 wild-type mice injected with suramin, a pharmacologic inhibitor of P2YR. Toxic liver failure was induced in mice by intraperitoneal injection of acetaminophen. Hepatocyte-specific functions of P2R signaling were analyzed in primary mouse hepatocytes. Results: Induction of acute hepatitis in wild-type C57BL/6 mice released large amounts of ATP from livers and induced expression of P2Y2R. Liver damage and necrosis were greatly reduced in P2Y2R mice and C57BL/6 mice given injections of suramin. Acetaminopheninduced liver damage was reduced in P2Y2R mice. Analysis of liver-infiltrating immune cells during acute hepatitis revealed that expression of P2Y2R in bone marrow-derived cells was required for liver infiltration by neutrophils and subsequent liver damage. Hepatic expression of P2Y2R interfered with expression of genes that regulate cell survival, and promoted tumor necrosis factor (TNF)α-mediated cell death, in a cell-autonomous manner. Conclusions: Extracellular ATP and P2Y2R have cell-type specific, but synergistic functions during liver damage that regulate cellular immune responses and promote hepatocyte death. Reagents designed to target P2Y2R might be developed to treat inflammatory liver disease.
Understanding Disease Progression in the Kagera Region of Tanzania: A Framework for Efficient Health Care Delivery

Today, chronic illnesses remain a great health burden for households and individuals in sub-Saharan Africa. This has been especially true in the Kagera Region in Tanzania, where HIV/AIDS rates have historically been greater than the national averages and health services have been poorly administered. In Kagera and elsewhere, policymakers must understand the progression of specific diseases in order to develop appropriate guidelines for treatment and care, and prioritize and allocate resources for health services. This study attempts to provide such a framework. Using longitudinal data from the Kagera Health and Development Survey 1991-1994, and 2004, the study examines health patterns among adults (aged 15-95) in Tanzania, and explores how well chronic health symptoms explain variations in survival time. This analysis shows that there are a number of populations that are at higher risk of experiencing death in the Kagera region: individuals with persistent weight-loss; females; individuals aged 35-44 years of age; previously married men and women; and individuals with higher levels of education. Future research is needed to explain why it is that some parts of the population survive less relative to individuals without those characteristics.
NICKEL, COPPER, ZINC AND CADMIUM FRACTIONATION IN MANGROVE SEDIMENTS, RED SEA, EGYPT

Nickle (Ni), copper (Cu), zinc (Zn) and cadmium (Cd) in eight sediment samples from mangrove area, Red Sea, Egypt were fractionated using diethylenetriamine pentaacetic acid (DTPA) and a sequential extraction procedure (SEP). These sediment samples were collected horizontally from two locations (four samples from each site) based on different layer visual characterizations. Sediments were initially characterised using different analytical and statistical procedures. DTPA-extract table metal percent of the total metal content varies widely from 1.93 : 25.6% for Ni, from 3.86 : 18.2% for Cu from 0.6 to 4.1 for Zn and from 3.36 : 11.2% for Cd depending on soil characteristics. There no consistent trend of metal extracted by DTPA as a function of sediment depths although CdDTPA (%) was increased by increasing sediment depths in site 1 and in site 2. Moreover, metal extracted by DTPA showed no consistent correspondence with any single fraction of SEP. The metal extracted by DTPA showed reasonable correlation with the summation of exchangeable (F1) and carbonate (F2) fractions in both sites. So it may be reasonable to conclude that most ‘available’ metal is (presumably) surface-bound on CaCO3, rather than occluded within CaCO3 or present as a mixed solid-solution (Ca1-xMxCO3). Approximately 84%, 30%, 70% and 95% of the variability in PTPA-extractable-Ni, Cu, Zn and Cd (mg kg-1) values for a whole dataset, respectively were explained by the variation in soil pH, (%) SOM, (%) CaCO3 and total metals content. CdDTPA showed the highest prediction performance while Cu showed the worst case of the regression model in which Cu availability is more likely controlled by either the source of Cu or other conditions rather than sediment properties.