Miracle-dz/UniFAR-FTUs huggingface dataset:
Automating power system fault diagnosis through multi-agent system technology

Fault diagnosis within electrical power systems is a time consuming and complex task. SCADA systems, digital fault recorders, travelling wave fault locators and other monitoring devices are drawn upon to inform the engineers of incidents, problems and faults. Extensive research by the authors has led to the conclusion that there are two issues which must be overcome. Firstly, the data capture and analysis activity is unmanageable in terms of time. Secondly, the data volume leads to engineers being overloaded with data to interpret. This paper describes how multi-agent system technology, combined with intelligent systems, can be used to automate the fault diagnosis activity. Within the multi-agent system, knowledge-based and model-based reasoning are employed to automatically interpret SCADA system data and fault records. These techniques and the design of the multi-agent system architecture that integrates them are described. Consequently, the use of engineering assistant agents as a means of providing engineers with decision support, in terms of timely and summarised diagnostic information tailored to meet their personal requirements, is discussed.
Digital Demand: Demand for Digital Cameras on Ebay

The paper estimates the demand for new digital cameras sold in eBay auctions. EBay data seems to offer significant advantages over traditional transactions data for estimating demand for differentiated products. However, there are a number of concerns including censoring bias and the interpretation of the bidding behavior. This paper discusses these problems as well as possible solutions. The paper presents results from three different methods for estimating demand for differentiated products on eBay. The results suggest that the demand for digital cameras is highly elastic and there isn't a lot of substitution, particularly across brands.
Burden Distribution Analysis by Digital Image Processing in a Scale Model of a Blast Furnace Shaft

During the realigning of Aceralia's blast furnace B in Gijon, a 1/10 scale half-section, three-dimensional cold model of the BF shaft was built to test charging patterns and the effect of gas flow in burden distribution. The front side of this half model is closed by a methacrylate sheet that allows images of the burden distribution inside the model to be obtained, during and after the charging process. Image processing techniques were applied to obtain useful information from burden profile images. A complete study of a charging pattern is presented in this paper. The model has allowed study of some local effects of gas flow in burden distribution, such as changes in the final coke layer during ore charging, and the formation of a narrow window in the centre of the model that connects the successive coke layers.
Effects of apps on consumer behavior of smartphones and telecommunication providers:feature fatigue vs. mass customization

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
Cost Based Power Aware Cross Layer Routing Protocol

Summary Mobile Ad-Hoc Networks (MANETs) are wireless networks consisting of a collection of mobile nodes with no fixed infrastructure, where some intermediate nodes should participate in forwarding data packets. So energy conservation is a critical issue in ad hoc wireless networks for node and network life. This issue is crucial in the design of new routing protocols. To design such protocols, we have to look away from the traditional minimum hop routing schemes. In this paper, we propose a cost based power aware cross layer design to AODV. The discovery mechanism in this algorithm uses Battery Capacity of a node as a routing metric. This approach is based on intermediate nodes calculating cost based on Battery capacity . The intermediate node judges its ability to forward the RREQ packets or drop it. That is it integrates the routing decision of network layer with battery capacity estimation of MAC layer. Simulations are performed to study the performance of power aware cross layer AODV protocol using NS2. The simulation shows that the cross layer protocol improves packet delivery ratio & throughput and also nodes energy consumption is reduced by routing packets using energy optimal routes. In summary our design offers a simple but efficient power aware cross layer routing protocol to support routing in AdHoc networks.
A comparison of half-bridge resonant converter topologies

The half-bridge series resonant, parallel resonant and combination series-parallel resonant converters are compared for use in low output voltage power supply applications. It is shown that the combination series-parallel converter, which takes on the desirable characteristics of the pure series and the pure parallel converter, removes the main disadvantages of those two converters. Analyses and breadboard results show that the combination series-parallel converter can run over a large input voltage range and a large load range (no-load to full-load) while while maintaining excellent efficiency. A useful analysis technique based on classical ac complex analysis is also introduced.
Tensor Topology Tracking: A Visualization Method for Time‐Dependent 2D Symmetric Tensor Fields

Topological methods produce simple and meaningful depictions of symmetric, second order two‐dimensional tensor fields. Extending previous work dealing with vector fields, we propose here a scheme for the visualization of time‐dependent tensor fields. Basic notions of unsteady tensor topology are discussed. Topological changes ‐ known as bifurcations ‐ are precisely detected and identified by our method which permits an accurate tracking of degenerate points and related structures.
H -Control Design for a Class of LPV Systems

In this paper, we focus on the issue of adaptive ∞ H -control design for a class of linear parameter-varying (LPV) systems based on the Hamiltonian-Jacobi-Isaac (HJI) method. By combining the idea of polynomially parameter- dependent quadratic functions and vector projection method to derive an adaptive ∞ H -control, sufficient conditions with high precision are given to guarantee both robust asymptotic stability and disturbance attenuation of the LPV systems with unknown constant parameters. The applicability of the proposed design method is illustrated on a simple example.
Online commercial intention detection framework based on web pages

The China Internet Network Information Centre (CNNIC) published that internet users around the world mostly spent 10-16 hours per week online. For effective advertising and social information publishing on the internet, how to dig out the commercial value from users' online behaviour becomes a new challenge compared with the traditional recommendation system. In this paper, we propose a novel system named 'online commercial intention (OCI) detection system' using users' global web browsing history to predict potential purchasing products on an online shopping platform. A 'commercial keyword dictionary (KD)' that reveals the relationship between user queries and product categories is firstly set up by analysing the click distribution of billion queries on the shopping platform. Footprints of millions of internet users are gathered and the raw page contents are crawled. Keywords in these pages are extracted using N-gram algorithm and commercial probabilities are estimated with query frequency (QF), inverse category frequency (ICF), etc. The page OCI is estimated by merging the KD matrices of its commercial keywords. In order to increase categories' coherence and accuracy, we provide a category similarity model to observe the distance between top N categories. The experiment results show that category prediction accuracy reaches 86% with manual evaluation.
Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.
Investigating the long memory property of the Hungarian market pig prices by using detrended fluctuation analysis

A B S T R A C T Within the scope of this study we test the Long Memory property on monthly average pig market prices including piglet, young pig, sow and slaughter pig. We also calculate the Hurst exponent using Detrended Fluctuation Analysis (DFA) method. DFA is a method for determining the statistical self-affinity of a time serie. It is a useful technique for investigating time series with long memory (diverging correlation time and powerlow decaying autocorrelation function. The obtained exponent by DFA is similar to those Hurst exponents estimated by other methods such as Rescaled Range (R/S) and AutoRegressive Fractionally Integrated Moving Average (ARFIMA), except the fact that DFA may also be applied to non-stacionary time series (mean and variance is changing with time) as in our case. We study the long memory property of the market pig prices. Data consist of four time series (piglet, young pig, sow, slaughter pig) between 1991 and 2013. Before the econometric analysis all the series were seasonally adjusted by using TRAMO/SEATS method. Data preparation was followed by differencing the time series and testing the normality and stationarity of them. In the next step we divided the analysed period to four parts and determined the Hurst exponent for each sub-period with the DFA method. So as to sum it up, slaughter pig prices are random, young pig and piglet prices developed similarly and have long memory, while sow price changes have definitely short memory.
Role of the nhaC-Encoded Na 1 / H 1 Antiporter of Alkaliphilic Bacillus firmus OF 4

Application of protoplast transformation and singleand double-crossover mutagenesis protocols to alkaliphilic Bacillus firmus OF4811M (an auxotrophic strain of B. firmus OF4) facilitated the extension of the sequence of the previously cloned nhaC gene, which encodes an Na/H antiporter, and the surrounding region. The nhaC gene is part of a likely 2-gene operon encompassing nhaC and a small gene that was designated nhaS; the operon is preceded by novel direct repeats. The predicted alkaliphile NhaC, based on the extended sequence analysis, would be a membrane protein with 462 amino acid residues and 12 transmembrane segments that is highly homologous to the deduced products of homologous genes of unknown function from Bacillus subtilis and Haemophilus influenzae. The full-length version of nhaC complemented the Nasensitive phenotype of an antiporter-deficient mutant strain of Escherichia coli but not the alkali-sensitive growth phenotypes of Na/H-deficient mutants of either alkaliphilic B. firmus OF4811M or B. subtilis. Indeed, NhaC has no required role in alkaliphily, inasmuch as the nhaC deletion strain of B. firmus OF4811M, N13, grew well at pH 10.5 at Na concentrations equal to or greater than 10 mM. Even at lower Na concentrations, N13 exhibited only a modest growth defect at pH 10.5. This was accompanied by a reduced capacity to acidify the cytoplasm relative to the medium compared to the wild-type strain or to N13 complemented by cloned nhaC. The most notable deficiency observed in N13 was its poor growth at pH 7.5 and Na concentrations up to 25 mM. During growth at pH 7.5, NhaC is apparently a major component of the relatively high affinity Na/H antiport activity available to extrude the Na and to confer some initial protection in the face of a sudden upshift in external pH, i.e., before full induction of additional antiporters. Consistent with the inference that NhaC is a relatively high affinity, electrogenic Na/H antiporter, N13 exhibited a defect in diffusion potentialenergized efflux of Na from right-side-out membrane vesicles from cells that were preloaded with 2 mM Na and energized at pH 7.5. When the experiment was conducted with vesicles loaded with 25 mM Na, comparable efflux was observed in preparations from all the strains.
Temporal Scalable Live Video Streaming over Hybrid CDN-P2P Architecture

Most of currently deployed live video streaming systems don‟t consider heterogeneous bandwidth of peers. To address this issue, many researches combine P2P solution with scalable video streaming, however none of the existing hybrid CDN-P2P consider it. This paper presents the combination of Hybrid CDN-P2P and temporal scalable streaming. The main design goal of our approach is changing requesting and transmission policy of peers commensurate with bandwidth to optimize video distribution and frame losses. Heterogeneity is addressed by changing upload policy of peers to send different layers for neighbors. The experimental result shows that, it achieves significant improvement to decrees video distortion and hop count.
A Universal Density Profile from Hierarchical Clustering

We use high-resolution N-body simulations to study the equilibrium density profiles of dark matter halos in hierarchically clustering universes. We find that all such profiles have the same shape, independent of the halo mass, the initial density fluctuation spectrum, and the values of the cosmological parameters. Spherically averaged equilibrium profiles are well fitted over two decades in radius by a simple formula originally proposed to describe the structure of galaxy clusters in a cold dark matter universe. In any particular cosmology, the two scale parameters of the fit, the halo mass and its characteristic density, are strongly correlated. Low-mass halos are significantly denser than more massive systems, a correlation that reflects the higher collapse redshift of small halos. The characteristic density of an equilibrium halo is proportional to the density of the universe at the time it was assembled. A suitable definition of this assembly time allows the same proportionality constant to be used for all the cosmologies that we have tested. We compare our results with previous work on halo density profiles and show that there is good agreement. We also provide a step-by-step analytic procedure, based on the Press-Schechter formalism, that allows accurate equilibrium profiles to be calculated as a function of mass in any hierarchical model.
Associations of the glutathione S-transferase P1 Ile105Val genetic polymorphism with gynecological cancer susceptibility: a meta-analysis

The association between the glutathione S-transferase P1 (GSTP1) Ile105Val polymorphism and gynecological cancer susceptibility has been evaluated in many studies. However, the results remain controversial. Thus, this meta-analysis, based on 10 published case-control studies, was designed to clarify the association of the GSTP1 Ile105Val polymorphism with gynecological cancer risk. Our results suggested that there was no significant association between the GSTP1 Ile105Val polymorphism and the risk of gynecological cancer in all genetic models (GG vs. AA: odds ratio [OR] = 1.41, 95% confidence interval [CI] = 0.75-2.26; AG vs. AA: OR = 1.13, 95% CI = 0.74-1.73; AG/GG vs. AA: OR = 1.17, 95% CI = 0.75-1.81; GG vs. AA/AG: OR = 1.38, 95% CI = 0.79-2.42). Similarly, in the subgroup analyses by cancer type, ethnicity, and smoking status, no significant association with any genetic model was observed. In conclusion, the results of our meta-analysis suggest that the GSTP1 Ile105Val polymorphism is not associated with the development of gynecological cancer.
VDBSCAN+: Performance Optimization Based on GPU Parallelism

Spatial data mining techniques enable the knowledge extraction from spatial databases. However, the high computational cost and the complexity of algorithms are some of the main problems in this area. This work proposes a new algorithm referred to as VDBSCAN+, which derived from the algorithm VDBSCAN (Varied Density Based Spatial Clustering of Applications with Noise) and focuses on the use of parallelism techniques in GPU (Graphics Processing Unit), obtaining a significant performance improvement, by increasing the runtime by 95% in comparison with VDBSCAN.
Bill Sponsorship in Congress: The Moderating Effect of Agenda Positions on Legislative Proposals

Positions of influence over the legislative agenda provide greater opportunities for shaping policy outcomes. Do legislators take advantage of this? If they do, when the median is pivotal and legislators' goals reflect both position taking and policy seeking, greater influence over the agenda leads legislators to moderate their bills relative to legislators with lower agenda priority. Analysis of a formal game theoretic model provides rigorous justification for the proposition, and empirical analysis of House and Senate bills from the 101st to 108th Congresses using cosponsorship data to measure the ideological locations of bills largely supports it. Committee leadership and majority party status have moderating effects while the effect of committee membership is slight. The analysis also tentatively supports the pivotalness of the median over other alternatives. Contrary to the view that bill sponsorship is mere position taking, legislative organization significantly shapes early-stage legislative behavior. Specifically, greater legislative influence implies greater responsiveness to the median legislator.
Introducing The Neuroscience Gateway

Last few decades have seen the emergence of computational neuroscience as a mature field where researchers are interested in modeling complex and large neuronal systems and require access to high performance computing machines and associated cyberinfrastructure to manage computational workflow and data. The neuronal simulation tools, used in this research field, are also implemented for parallel computers and suitable for high performance computing machines. But using these tools on complex high performance computing machines remain a challenge due to issues with acquiring computer time on these machines located at national supercomputer centers, dealing with complex user interface of these machines, dealing with data management and retrieval. The Neuroscience Gateway is being developed to alleviate all of these barriers to entry for computational neuroscientist. It hides or eliminates, from the point of view of the users, all the administrative and technical barriers and makes parallel neuronal simulation tools easily available and accessible on complex high performance computing machines and handles the running of jobs and data management and retrieval. This paper describes the architecture it is based on, how it is implemented, and how users can use this for computational neuroscience research using high performance computing at the back end.
A Clustering Approximation Technique for Queueing Network Models with a Large Number of Chains

The past few years have witnessed an increasing number of large distributed computer system implementations based on local area networks. In these systems a number of resources (CPU's, file servers, disks, etc.) are shared among jobs originating at different sites. Evaluating the performance of such large systems typically requires the solution of a queueing network model with a large number of closed chains, which precludes the use of exact solution techniques. Therefore, it is important to develop accurate and cost-effective methods for the approximate analysis of closed queueing networks with many chains. In this paper, we present an approach based on the clustering of chains and service centers. The method is applicable to queueing networks with single server fixed rate, infimite server and multiple server service centers. We present the results obtained when the method is used to solve large queueing network models. Extensive comparison of this method to existing approximation techniques indicates that the approach has better accuracy/cost characteristics.
Full Memory Read Attack on a Java Card

We present a simple attack on a Java Card smart card to perform arbitrary memory reads. The attack utilises a known technique of type confusion of the card’s Java Virtual Machine by exploiting the faulty transaction mechanism implementation. The type confusion attack lets us access the application’s private meta-data, reverse engineer it, and in turn get full read and write access to arbitrary memory locations on the card. The attack gives us good insights into overall memory organisation of the card. We discuss the exploit in detail, including the exploit applet source code, to provide a reproducible attack. We shortly discuss the usefulness of an on-card Bytecode Veriﬁer, that the exploited card is equipped with, and also the Java Card ﬁrewall mechanism deﬁciencies.
Toward Near-Ground Localization: Modeling and Applications for TOA Ranging Error

Near-ground localization is a special type of localization scenario that is widely considered in both academic and industry. In this communication, with considering the multipath condition in near-ground environments, we conducted field measurements and proposed an antenna height-dependent time of arrival (TOA) ranging error model. Experiment results show that TOA distance measurement errors accord with Gaussian distribution, and its mean and variance are directly related with antenna height and communication distance. Based on the proposed TOA ranging error model, Cramer–Rao lower bound under typical scenarios have been calculated, and localization performance simulation has been studied. The experiment results indicate that the proposed TOA ranging error model has significant theoretical and practical application values.
Elderly care recommendation system for informal caregivers using case-based reasoning

The aging world population is a challenge for global healthcare. Caring for the elderly is particularly stressful and difficult for informal caregivers. Accordingly, automated systems to assist informal caregivers will fill a great need. In this paper, a system prototype is developed to provide recommendations for elderly care to informal caregivers applying case-based reasoning (CBR) techniques. The recommendations are divided into four areas, namely, physical therapy, food, emotional, and exercise regimes. Real data was used as the input to create a case database and identify weighted attributes in consultation with experts. A novelty in our application of CBR is the use of tailored similarity measures depending on the attribute type. The system prototype performs with high accuracy.