Miracle-dz/UniFAR-FTUs huggingface dataset:
Title : Feasible Performance Evaluations of Digitally-Controlled Auxiliary Resonant Commutation Snubber-Assisted Three Phase Vo

The use of renewable energy sources in microgrids has grown dramatically in recent years. The absence of a rotational mass in these microgrids and their interfaces leads to a lack of inertia and consequently, frequency and voltage instability. To cope with these dilemmas, the virtual synchronous generator (VSG) has been introduced as an effective solution. This paper first focuses on modeling a VSG using basic electrical equations. It, then, proffers a transient fuzzy controller augmented on virtual inertia’s topology. Inspired by the FACTS’ performance, the privileged specifications such as STATCOM fluctuation damping ability for major perturbations at transient times are appended to the VSG scheme by a fuzzy controller. This controller is implemented with a difference in voltage angle and its derivative, as well as in frequency and its derivative. The modified coefficients of both active and reactive powers are outputs of the fuzzy system. Using the proposed fuzzy controller, the transient response of VSG-based microgrids is improved. Simplicity and ability to improve the transient response are the principal specifications of the proposed configuration. Simulation results confirm the improvement of the presented method by the introduced augmented VSG control mechanism.
Carbink: Fault-Tolerant Far Memory

Far memory systems allow an application to transparently access local memory as well as memory belonging to remote machines. Fault tolerance is a critical property of any practical approach for far memory, since machine failures (both planned and unplanned) are endemic in datacenters. However, designing a fault tolerance scheme that is efﬁcient with respect to both computation and storage is difﬁcult. In this paper, we introduce Carbink, a far memory system that uses erasure-coding, remote memory compaction, one-sided RMAs, and ofﬂoadable parity calculations to achieve fast, storage-efﬁcient fault tolerance. Compared to Hydra, a state-of-the-art fault-tolerant system for far memory, Carbink has 29% lower tail latency and 48% higher application performance, with at most 35% higher memory usage.
A Statistical Model for Parsing and Word-Sense Disambiguation

This paper describes a rst attempt at a statistical model for simultaneous syntactic parsing and generalized word-sense disambiguation. On a new data set we have constructed for the task, while we were disappointed not to nd parsing improvement over a traditional parsing model, our model achieves a recall of 84.0% and a precision of 67.3% of exact synset matches on our test corpus, where the gold standard has a reported inter-annotator agreement of 78.6%.
Climate, Diversification and Refugia in the Common Shrew: Evidence from the Fossil Record

The Sorex araneus group has a rich but understudied Eurasian fossil record that spans more than two million years and stretches geographically from Britain to China. Their fossils have been found in association with mammoths, lions, hyenas, Neanderthals and even the mysterious Denisovans, people whose ancient DNA reveals them to be distinct from both Neanderthals and modern humans (Schreve, 2000; Currant and Jacobi, 2001; Agadjanian and Serdyuk, 2005; Rzebik-Kowalska, 2008). When combined with molecular phylogenetic data from extant species, the fossil record provides a broad picture of the timing and geographic context of the group’s diversification (Fig. 13.1), including the fragmentation of the range of the common shrew during glacial cycles.
A Novel Stochastic Optimization Strategy for Parallel Sparse Tucker Decomposition

— SparseTuckerDecomposition(STD)algorithmslearnacoretensorandagroupoffactormatricestoobtainanoptimallow-rank representationfeaturefortheHigh-Order,High-Dimension,andSparseTensor(HOHDST). However,existingSTDalgorithmsfacethe problemofintermediatevariablesexplosionwhichresultsfromthefact thattheformationofthosevariables,i.e.,matricesKhatri-Raoproduct, Kroneckerproduct,andmatrix-matrixmultiplication,followsthewholeelementsinsparsetensor.Theaboveproblemspreventdeepfusionof efﬁcientcomputationandbigdataplatforms. Toovercomethebottleneck,anovelstochasticoptimizationstrategy(SGD Tucker)isproposed forSTDwhichcanautomaticallydividethehigh-dimensionintermediatevariablesintosmallbatchesofintermediatematrices. Speciﬁcally, SGD Tuckeronlyfollowstherandomlyselectedsmallsamplesratherthanthewholeelements, whilemaintainingtheoverallaccuracyand convergencerate.Inpractice,SGD Tuckerfeaturesthetwodistinctadvancementsoverthestateoftheart.First,SGD Tuckercanprunethe communicationoverheadforthecoretensorindistributedsettings.Second, thelowdata-dependenceofSGD Tuckerenablesﬁne-grained parallelization, whichmakesSGD Tuckerobtaininglowercomputationaloverheadswiththesameaccuracy.Experimentalresultsshowthat SGD Tuckerrunsatleast2 X fasterthanthestateoftheart.
Contemporary aspects in the assessment of quality and treatment of swimming pool water

Recent reports in the literature relate to the identification of various substances in the pool water, including low-molecular weight pharmaceuticals that can react with chlorine residues contributing to the formation of a large group of irritant and toxic compounds. These substances are not covered by standard monitoring. As part of this work, the authors present information on the methods for assessing the quality of the swimming pool water. Common processes used in swimming pool water treatment systems were described. Previous experience of the authors in the use of a detailed assessment of the quality of the swimming pool water on the basis of toxicity tests was presented. The authors have researched the application of pressure driven membrane filtration for the improvement of the efficiency of the swimming pool water treatment.
Protein classification using modified n-grams and skip-grams

Motivation Classification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in this process requires detailed knowledge of attributes used to classify the proteins. Lack of this knowledge risks the selection of irrelevant features, resulting in a faulty model. In this study, we introduce a supervised protein classification method with a novel means of automating the work-intensive feature generation step via a Natural Language Processing (NLP)-dependent model, using a modified combination of n-grams and skip-grams (m-NGSG). Results A meta-comparison of cross-validation accuracy with twelve training datasets from nine different published studies demonstrates a consistent increase in accuracy of m-NGSG when compared to contemporary classification and feature generation models. We expect this model to accelerate the classification of proteins from primary sequence data and increase the accessibility of protein characteristic prediction to a broader range of scientists. Availability and implementation m-NGSG is freely available at Bitbucket: https://bitbucket.org/sm_islam/mngsg/src. A web server is available at watson.ecs. baylor.edu/ngsg. Contact erich_baker@baylor.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Investigating natural variability within headwater catchments in North Yorkshire, with regards to Margaritifera margaritifera conservation

Catchment management for water quality is an evolving process that requires social cohesion between a variety of stakeholders, effective management of land, coupled with a change in social behaviour, in order to effect a reduction in the flux of nutrients entering a river. Through creating a dynamic strategy which acknowledges the limitations of reducing nutrient concentrations entering a river, catchment managers are required to improve water quality according to the Water Framework Directive Legislation (2000/60/EC). Current catchment management processes have successfully reduced nutrient concentrations from point sources and are beginning to address nutrient concentrations associated with diffuse sources. In rural catchments, such as the one studied, diffuse pollution is influenced by land management practices, agricultural practices, and septic tank contributions. Highlighting the importance of adopting an integrated catchment management plan to address the headwaters within a catchment, this thesis has recognised the variations within water quality which can be overlooked by monthly spot sampling at a downstream location of a river catchment. Conservation efforts for the umbrella species M. margaritifera requires spatial and temporal investigations across a catchment to ensure successful relocation and recruitment. Hydrological connectivity plays an integral role within a catchment; new transportation routes can elevate nutrient concentrations, thus degrading water quality. Through investigating the different hydrological connections within a catchment, appropriate management practices can be identified. Spatial variations across the low-order tributaries of a catchment can have a significant influence on river water quality downstream. The catchment management practices, which go hand in hand with creating a healthy, self-regulating ecosystem, with minimal environmental degradation, must be aligned to these spatial variations in connectivity and pollution transport. This thesis investigates the spatial and temporal variability of water quality within three rural subcatchments of the River Esk in the North York Moors, in particular the influence of land use, differences in management practices and the importance of viewing the hydrological connectivity at different scales of a catchment. Fortnightly sampling using a YSI probe and anion and cation analysis was undertaken. The results of the research led to suggestions for addressing water quality variations across the headwater tributaries with the aim of improving the recruitment of the umbrella species M. margaritifera in the River Esk catchment.
An Analysis of DNF Maximum Entropy

AN ANALYSIS OF DNF MAXIMUM ENTROPY By Belinda Hasanaj December 2014 Thesis supervised by Karl Wimmer, Ph.D., Assistant Professor This study focuses on the entropy of functions computed by monotone DNF formulas. Entropy, which is a measure of uncertainty, information, and choice, has been long studied in the field of mathematics and computer science. We will be considering spectral entropy and focus on the conjecture that for each fixed number of terms t, the maximum entropy of a function computed by a t-term DNF is achieved by a function computable by a read-once DNF. A Python program was written to first express the t-term DNF Boolean functions as multilinear polynomials and then to compute their spectral entropy. This was done for the cases t = 1, 2, 3, 4. Our results agree with the conjecture and show that the maximum entropy occurs for functions with a small number of literals.
Halogen Heterogeneity in the Lithosphere and Evolution of Mantle Halogen Abundances Inferred From Intraplate Mantle Xenoliths

We present halogen, noble gas, and major and trace element compositions of mantle xenoliths from intraplate settings (Eifel, Kilbourne Hole, San Carlos, and Hawaii). The xenoliths show a wide range of halogen elemental ratios, which form two arrays centered on the halogen composition of mid‐ocean ridge basalts. The samples on the array toward high I/Cl value have relatively low Cl concentration and low ratios of highly incompatible elements relative to heavy rare earth elements, whereas the samples on the array toward low Br/Cl value have higher Cl concentration and trace elements ratios. The detailed mechanisms to account for these signatures are equivocal at present. However, they are most likely to be related to secondary processes of volatile loss during partial melting and secondary phase formation during interaction with melts. The common primary mid‐ocean ridge basalt‐like halogen ratios in mantle xenoliths from different parts of the globe indicate that the mantle itself must have a relatively uniform composition over a wide scale. The mantle has maintained its halogen composition over billion year timescales without being affected by I‐rich halogens being transported into the mantle. Mass balance calculations suggest that, in order to maintain the I/Cl ratio of the convecting mantle over 2 Gyr, the I/Cl ratio of the subducted halogens must be no more than several times higher than the present‐day mantle value.
System \ Use Quality 1 Individual ) Organizational Impact Impact Information A User Quality Satisfaction

DeLone and McLean's (1992) comprehensive review of different information system success measures concludes with a model of interrelationships between six IS Success constructs. This paper critically examines the meaning of four of these constructs and the evidence of relationships between them. It then provides results from an empirical test of these relationships. The empirical results provide substantial support for DeLone and McLean's model. Three factors, System Quality, Information Quality, and Usefulness, are found to explain 72% of the variance in the overall User Satisfaction measure. Three factors, System Quality, Information Quality, and a measure of the importance of the system to the user, User Involvement, are found to explain 56% of the variance in Usefulness. The paper concludes that of the four measures studied, the best "omnibus" measure of IS success is User Saisfacion. This can be measured using the simple four-question instrument presented in the study.
DIVISION OF THE HUMANITIES AND SOCIAL SCIENCES A REVIEW OF AND AS IT RELATES TO ECONOMIC THEORY* supported in part by NSF Grant #SESS0-03863.

This paper analyzes the behavior of a single firm engaged in R and D for a ''sponsor,'' We are interested in two particular aspects of the interaction between the two agents: (1) the revelation to the sponsor of new information generated by the firm's research, and (2) the firm's choice of research strategy. We show that contractual forms which provide good incentives in a static environment may introduce incentive problems in a dynamic setting, More speoif ioally, we show that a firm engaged in a sequence of R and D contracts is more likely to do research (1) the lower are the costs of R and D, (2) the better is the state of sponsor knowledge, and (3) the longer is the sequence of contracts (given an appropriately high discount factor), We also show that the firm reveals a larger share of its results (1) the better is the state of sponsor knowledge, (2) the better is the state of private knowledge possessed by the firm, and (3) the shorter is the sequence of contracts, Finally, somewhat surprisingly, we find that the amount of information a firm reveals is independent of the costs of R and D. A DYNAMIC MODEL OF RESEARCH CONTRACTING 1, INTRODUCTION Joel Balbien and Louis L. Wilde California Institute of Technology A considerable body of economic theory has been developed over the last fifteen years to model (i) R and D decisionmaking by private firms, (ii) general equilibrium aspects of industrial innovation, and (iii) principal-agent relations. Of particular interest to those concerned with public policy are papers by Scherer [1969), Bernholdt [19671 and Cummins [1973), who have analyzed the behavior of defense contractors as reflected in cost over-runs or under-runs. These authors consider the rational choice of risk-assumption provisions in the uncertain environment typically characterizing a bilateral procurement contract, Related papers are by Williamson [1967), who has attempted to ascertain what factors are responsible for performance results obtained in military contracts, and Agapos and Dunlop [1970), who have developed a price-determination model for bilateral procurement, In spite of this work, our understanding of the behavior of firms engaged in sponsored research is very limited. In this paper we are particularly interested in two aspects of the interaction between private firms and a research sponsor (who may or may not be a government bureaucrat): (1) the revelation to the sponsor of technical change embodied in the firm's physical and human capital and (2) the firm's choice of research strategy.
No Evidence for Milankovitch Cycle Influence on Abyssal Hills at Intermediate, Fast, and Superfast Spreading Rates

A recent hypothesis contends that abyssal hill topography is linked to sea level periodicities expressed by Milankovitch cycles, predicting that abyssal hill elevation is correlated to crustal age. We test this prediction by stacking (averaging) bathymetry as a function of age to enhance age‐dependent signal while suppressing random (primarily faulted) components. Stacking is applied to bathymetry data flanking intermediate, fast, and superfast spreading ridges. Revised digital crustal age models were generated in these regions using a recent compilation of reliable magnetic anomaly identifications, with inferred temporal uncertainty of ~0.01 my. We utilize statistical properties of abyssal hills to predict the variability of the age‐stack under the null hypothesis that abyssal hills are random with respect to crustal age; the age‐stacked profile is significantly different from zero only if it exceeds this expected variability by a large margin. Our results do not support the presence of Milankovitch‐driven signals in abyssal hill topography.
Smart Information Systems: Computational Intelligence for Real-Life Applications

This text presents an overview of smart information systems for both the private and public sector, highlighting the research questions that can be studied by applying computational intelligence. The book demonstrates how to transform raw data into effective smart information services, covering the challenges and potential of this approach. Each chapter describes the algorithms, tools, measures and evaluations used to answer important questions. This is then further illustrated by a diverse selection of case studies reflecting genuine problems faced by SMEs, multinational manufacturers, service companies, and the public sector. Features: provides a state-of-the-art introduction to the field, integrating contributions from both academia and industry; reviews novel information aggregation services; discusses personalization and recommendation systems; examines sensor-based knowledge acquisition services, describing how the analysis of sensor data can be used to provide a clear picture of our world.
Split-ordered lists: lock-free extensible hash tables

We present the first lock-free implementation of an extensible hash table running on current architectures. It provides concurrent insert, delete, and search operations with an expected O(1) cost. It consists of very simple code, easily implementable using only load, store, and compare-and-swap operations. The new mathematical structure at the core of our algorithm is recursive split-ordering, a way of ordering elements in a linked list so that they can be repeatedly "split" using a single compare-and-swap operation. Empirical tests conducted on a large shared memory multiprocessor show that even in non-multiprogrammed environments, the new algorithm significantly outperforms the most efficient known lock-based algorithm at all concurrency levels, exhibiting up to four times higher throughput at peak load. The incremental nature of our algorithm makes it well suited for real-time applications, as it offers predictable performance without unexpected breaks for resizing.
Accelerating Functional Verification Coverage Data Manipulation Using Map Reduce

— As the size and complexity of today’s HW designs have been increased significantly, a huge amount of coverage information is generated during the design simulation and throughout the coverage closure cycle. Accordingly an efficient method for coverage data manipulation will be of great help to reduce the time and accuracy of the coverage data analysis process. This paper proposes the utilization of a distributed data processing technique, namely MapReduce, to accelerate the merging of coverage data sets from multiple simulation sessions. Inspired by the spirit of MapReduce, we formulate coverage data merging problem into tasks that are associated with keys and values and perform massively parallel map and reduce operations on distributed systems. Our coverage data manipulation framework is able to handle coverage data that is stored in coverage data bases or in multiple coverage reports. We demonstrate how the proposed approach can speed up the merging step by up to 1.8x factor with respect to other traditional merging techniques using real industrial designs.
Performance Analysis of Reconfigurable Heterogeneous Adder Architectures

: The computational problems are solved by adaptable fabrics. A reconfigurable fabric has attracted high priority as the complexity and throughput has increased. The problem related to a specific architecture can be effectively addressed by reconfigurable computing. Various adder structures like Carry Bypass (CBA), Carry Look-Ahead (CLA), Ripple Carry Adder (RCA) and Carry Select (CSLA) with reconfigurable architecture are designed for Field Programmable Gate Array (FPGA) application. Performance metrics like area speed and power consumption can be effectively optimized by reconfigurable architectures. More fine grained architecture with improved can be achieved using reconfiguration techniques. The proposed structures are coded in Verilog-HDL. These architectures are targeted for 65 nm technology node using Synopsis tool. The proposed technique can be extended for more complex designs with improved performance. An area reduction of 14% to 44% and power reduction of 18% to 54% has been achieved using proposed reconfigurable adder architectures.
Isolates of tannery effluent and their antibiogram from effluent plant in South India.

The tanning industry was designated as “Red categor y” due to the high pollution contributed to environ ment by its solid and liquid wastes the toxicity by heavy metal s is spreading throughout the world along with indu strial progress. The present study deals with isolation, i dentification and characterization of isolated from tannery effluent collected in and around Erode, South India. A total of 60 isolates were screened from tannery effluent . A ibiotic sensitivity pattern was studied using disk diffusio n method. Most of the bacterial strains were sensit ive sensitive to cotrimoxazole, gentamycin, kanamycin, nalidixic aci d, ampicillin, and Penicillin showed resistance aga inst bacteria. Staph aureus was 50% resistant to amikaci n, 49% resistant to gentamycin and norfloxacin. Bac illus spp. demonstrated higher resistance for Ciprofloxacin si milarly E.coli had 49.7% resistance to clindamycin. P.aeruginosa exhibited very high resistance for col istin and norfloxacin. The two major dominant isola tes were Pseudomonas spp. and Bacillus spp. , Staph aureus wa s found to be in subdominant form. It is found that domestic and industrial effluents are responsible for the de velopment of bacterial resistance with the risk of human health and environment.