Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Coding Scheme for Tolerating Double Disk Failures

A new MDS array erasure code, called DA-Code, which can tolerate double disk erasures for highly reliable data storage system is proposed in this paper. The DA-Code requires only XOR operations and achieves optimal encoding, updating and decoding complexity. The parity symbols are evenly distributed in the array, overcoming the bottleneck effects of repeated write operation. Detailed DA-Code’s decoding algorithm for correcting double disk failures is provided. Analysis result shows that the new coding scheme has excellent performance. Thus, the DA-Code is practically very meaningful for storage systems which need high reliability.
Credit union performance : does CEO gender matter ?

This is an empirical paper that on financial performance of financial institutions. We examine data for time periods before (2006.4), during using both univariate and multivariate analysis. While CEOs in commercial banks are disproportionately male, the same is not true of credit unions. After examining the relevant literature on gender based performance difference we developed a model that includes proxy variables for institutional asset size, return on assets, asset utilization, technology, risk taking, growth and liquidity versus female CEOs are hypothesized to be associated with financial performance of the institution. Discriminant differences in financial performance between credit unions led by a female vs. a male CEO.
Knowing a Few Rules Doesn't Mean You Can Play the Game: The LImits of "Best Practice" in Enterprise Systems

We examine the common claim that “best practices” are encompassed and represented in Enterprise Systems (ES). We suggest that an ES can at best only represent the ostensive and not the performative elements of work tasks. Thus, representation of best practice in an ES does not take practical action into account. This has two important implications. First, ostensive abstractions of best practice in an ES are a sparse and superficial representation of a “good” business process, at a specific moment in time. Second, the practical understanding required for performance is often ignored in the ostensive representation of best practice in the implementation of an ES. This constrains user and business adaptability. Inflexible coding of ostensive business tasks furthermore leads to rigidity where flexibility should be sought, to keep on top of the competition. Implications and directions for further research are discussed.
A rigid-body target design methodology for optical pose-tracking systems

The standard method for estimating the rigid-body motion of arbitrary interaction devices with an infrared-optical tracking system involves attaching pre-defined geometric constellations of retro-reflective or light-emitting markers, commonly referred to as "targets", to all tracked objects. Optical markers of the same type are typically indistinguishable from each other, requiring the tracking system to establish their identities through known spatial relationships. Consequently, the specific geometric arrangement of markers across multiple targets has a considerable impact on the system's overall performance and robustness. In this paper, we propose a simple new methodology for constructing optically tracked rigid-body targets. Our practically-oriented approach employs an optimization heuristic to compute near-optimal marker arrangements. Using prefabricated mounting fixtures, the assembly step requires only basic hobbyist tools and skills.
Car Parking Vacancy Detection and Its Application in 24-Hour Statistical Analysis

Finding empty parking spaces is a common problem in densely populated areas. Drivers spend an unnecessarily large amount of time searching for the empty spots, because they do not have perfect knowledge about the available vacant spots. An effective vacancy detection system would significantly reduce search time and increase the efficiency of utilizing the scarce parking spaces. The proposed solution uses trained neural networks to determine occupancy states based on visual features extracted from parking spots. This method addresses three technical problems. First, it responds to changing light intensity and non-uniformity by having adaptive reference pavement pixel value calculate the color distance between the parking spots in question and the pavement. Second, it approximates images with limited lighting to have similar feature values to images with sufficient illumination, merging the two patterns. Third, the solution separately considers nighttime vacancy detection, choosing appropriate regions to obtain reference color value. The accuracy was 99.9% for occupied spots and 97.9% for empty spots for this 24-hour video. Besides giving an accurate depiction of the car park's utilization rate, this study also reveals the patterns of parking events at different times of the day and insights to the activities that car drivers engage with.
Does it matter who contributes: a study on featured articles in the german wikipedia

The considerable high quality of Wikipedia articles is often accredited to the large number of users who contribute to Wikipedia's encyclopedia articles, who watch articles and correct errors immediately. In this paper, we are in particular interested in a certain type of Wikipedia articles, namely, the featured articles - articles marked by a community's vote as being of outstanding quality. The German Wikipedia has the nice property that it has two types of featured articles: excellent and worth reading. We explore on the German Wikipedia whether only the mere number of contributors makes the difference or whether the high quality of featured articles results from having experienced authors contributing with a reputation for high quality contributions. Our results indicate that it does matter who contributes.
Taxation and Evasion in the Presence of Extortion by Organized Crime

We model the taxation behavior of a revenue maximizing government in the presence of tax evasion by firms and the existence of a competing tax collector in the form of organized crime (the "mafia"). In order to evade taxes, the firm must shift some of its sales underground, possibly incurring costs. We show that the government's optimal tax rate and revenue in equilibrium crucially depend on the importance of public goods or, equivalently, the efficiency of their production. When public goods can be produced cheaply, both the state's tax rate and tax revenues are lower in the presence of the mafia than without it. However, when public goods are difficult to provide, the government benefits from the fact that the mafia's taxation imposes costs on the underground activities of the firms. The firms, on the other hand, are typically hurt by the mafia's presence when public goods are not important and benefit from it otherwise. The joint payoffs of all players are higher with the mafia than without it if public goods are difficult to produce, but may become lower at the other extreme.
Cortical Neurovascular Coupling Driven by Stimulation of Channelrhodopsin-2

While functional imaging is widely used in studies of the brain, how well the hemodynamic signal represents the underlying neural activity is still unclear. And there is a debate on whether hemodynamic signal is more tightly related to synaptic activity or action potentials. This study intends to address these questions by examining neurovascular coupling driven by pyramidal cells in the motor cortex of rats. Pyramidal cells in the motor cortex of rats were selectively transduced with the light sensitive cation channel channelrhodopsin-2 (ChR2). Electrophysiological recordings and optical intrinsic signal imaging were performed simultaneously and synchronously to capture the neural activity and hemodynamics induced by optical stimulation of ChR2-expressing pyramidal cells. Our results indicate that both synaptic activity (local field potential, LFP) and action potentials (multi-unit activity, MUA) are tightly related to hemodynamic signals. While LFPs in γ band are better in predicting hemodynamic signals elicited by short stimuli, MUA has better predictions to hemodynamic signals elicited by long stimuli. Our results also indicate that strong nonlinearity exists in neurovascular coupling.
Is Canada an Optimal Currency Area? An Inflation Targeting Perspective

We propose a method, based on the currency union model of Gali and Monacelli ( ), to determine whether a region within an existing currency area belongs in the currency union. The method involves assessing the predictability of regional inflation rates at medium term horizons. We apply the method to the Canadian provinces and find that for all but Alberta there is little evidence of costs in terms of inflation arising from national monetary policy. For Alberta, the evidence suggests that they are not as well served by the inflation targeting framework and that a more flexible policy environment might improve inflation outcomes.
Constraint Handling in Manufacturing Planning Systems

This paper deals with constraint handling in manufacturing. It starts with a basic de nition of the constraint satisfaction problem, followed by a description of consistency enforcing and constraint guided search. Constraint handling in scheduling problems is the main topic of the paper also presenting di erent types of schedule construction methods and explaining the use of temporal constraints. Special attention is given to the task of mid-term production planning. First, production planning in ordinary MRP II-based systems is introduced, followed by the presentation of the master production scheduling leitstand (MPSL), a research and development activity of a \Forschungsschwerpunkt" at the University GH Essen.
Costing Generated Runtime Execution Plans for Large-Scale Machine Learning Programs

Declarative large-scale machine learning (ML) aims at the specification of ML algorithms in a high-level language and automatic generation of hybrid runtime execution plans ranging from single node, in-memory computations to distributed computations on MapReduce (MR) or similar frameworks like Spark. The compilation of large-scale ML programs exhibits many opportunities for automatic optimization. Advanced cost-based optimization techniques require---as a fundamental precondition---an accurate cost model for evaluating the impact of optimization decisions. In this paper, we share insights into a simple and robust yet accurate technique for costing alternative runtime execution plans of ML programs. Our cost model relies on generating and costing runtime plans in order to automatically reflect all successive optimization phases. Costing runtime plans also captures control flow structures such as loops and branches, and a variety of cost factors like IO, latency, and computation costs. Finally, we linearize all these cost factors into a single measure of expected execution time. Within SystemML, this cost model is leveraged by several advanced optimizers like resource optimization and global data flow optimization. We share our lessons learned in order to provide foundations for the optimization of ML programs.
Capacity Analysis for Transmit Antenna Selection Using Orthogonal Space-Time Block Codes

Antenna selection for multiple-input multiple-output (MIMO) where only a subset of antennas at the transmitter and/or receiver are activated for signal transmission is a practical technique for the realization of full diversity. Despite extensive research, closed-form capacity expressions for MIMO systems employing transmit antenna selection (TAS) and orthogonal space-time block codes (OSTBCs) are not available. We thus derive the exact closed-form capacity expressions when an OSTBC is employed and N transmit antennas out of total Lt antennas are selected for transmission. The expressions are valid for a frequency-flat Rayleigh fading MIMO channel and avoid numerical integration methods
Convergence of Nonparametric Long-Memory Phase I Designs

We examine nonparametric dose-finding designs that use toxicity estimates based on all available data at each dose allocation decision. We prove that one such design family, called here "interval design", converges almost surely to the maximum tolerated dose (MTD), if the MTD is the only dose level whose toxicity rate falls within the pre-specified interval around the desired target rate. Another nonparametric family, called "point design", has a positive probability of not converging. In a numerical sensitivity study, a diverse sample of dose-toxicity scenarios was randomly generated. On this sample, the "interval design" convergence conditions are met far more often than the conditions for one-parameter design convergence (the Shen-O'Quigley conditions), suggesting that the interval-design conditions are less restrictive. Implications of these theoretical and numerical results for small-sample behavior of the designs, and for future research, are discussed.
ECG arrhythmias classification using wavelet transform and neural networks

In this research, a new method for heart Arrhythmias classification based on Wavelet Transform and Neural Networks has been proposed. Discrete Wavelet Transform (DWT) is normally used for processing and extracting the time and frequency characteristics (specifications) of ECG records. In this work, the obtained features from Wavelet Transform and morphological features of the ECG is combined with time of features this signal in order to use its results as final features to teach and test a Multi Layer Perceptron (MLP) Neural Network. In this research, 189 heart signal samples existed in MIT-BIH data base are utilized in order to teach and test the classifier. The best accuracy of 97.33 percent have been achieved for three different class of ECG signals including; Normal rhythm RBBB and LBBB.
A social group utility maximization framework with applications in database assisted spectrum access

In this paper, we develop a social group utility maximization (SGUM) framework for cooperative networking that takes into account both social relationships and physical coupling among users. Specifically, instead of maximizing its individual utility or the overall network utility, each user aims to maximize its social group utility that hinges heavily on its social ties with other users. We show that this framework provides rich modeling flexibility and spans the continuum space between non-cooperative game and network utility maximization (NUM) - two traditionally disjoint paradigms for network optimization. Based on this framework, we study an important application in database assisted spectrum access. We formulate the distributed spectrum access problem among white-space users with social ties as a SGUM game. We show that the game is a potential game and always admits a social-aware Nash equilibrium. We also design a distributed spectrum access algorithm that can achieve the social-aware Nash equilibrium of the game and quantify its performance gap. We evaluate the performance of the SGUM solution using real social data traces. Numerical results demonstrate that the performance gap between the SGUM solution and the NUM (social welfare optimal) solution is at most 15%.
Scalar vacuum structure in general relativity and alternative theories. Conformal continuations

We discuss the global properties of static, spherically symmetric configurations of a self-gravitating real scalar field $\phi$ in general relativity (GR), scalar-tensor theories (STT) and high-order gravity ($L=f(R)$) in various dimensions. In GR, for fields with arbitrary potentials $V(\phi)$, not necessarily positive-definite, it is shown that the list of all possible types of space-time causal structure in the models under consideration is the same as the one for $\phi = const$. In particular, there are no regular black holes with any asymptotics. These features are extended to STT and $f(R)$ theories, connected with GR by conformal mappings, unless there is a conformal continuation, i.e., a case when a singularity in a solution of GR maps to a regular surface in an alternative theory, and the solution is continued through such a surface. This effect is exemplified by exact solutions in GR with a massless conformal scalar field, considered as a special STT. Necessary conditions for the existence of a conformal continuation are found; they only hold for special choices of STT and high-order theories of gravity.
Okinawa in Japanese and English wikipedia

This research analyzes edits by foreign-language users in Wikipedia articles about Okinawa, Japan, in the Japanese and English editions of the encyclopedia. Okinawa, home to both English and Japanese speaking users, provides a good case to look at content differences and cross-language editing in a small geographic area on Wikipedia. Consistent with prior work, this research finds large differences in the representations of Okinawa in the content of the two editions. The number of users crossing the language boundary to edit both editions is also extremely small. When users do edit in a non-primary language, they most frequently edit articles that have cross-language (interwiki) links, articles that are edited more by other users, and articles that have more images. Finally, the possible value of edits from foreign-language users and design possibilities to motivate wider contributions from foreign-language users are discussed.
The Myeloid Receptor PILRβ Mediates the Balance of Inflammatory Responses through Regulation of IL-27 Production

Paired immunoglobulin-like receptors beta, PILRβ, and alpha, PILRα, are related to the Siglec family of receptors and are expressed primarily on cells of the myeloid lineage. PILRβ is a DAP12 binding partner expressed on both human and mouse myeloid cells. The potential ligand, CD99, is found on many cell types, such as epithelial cells where it plays a role in migration of immune cells to sites of inflammation. Pilrb deficient mice were challenged with the parasite Toxoplasma gondii in two different models of infection induced inflammation; one involving the establishment of chronic encephalitis and a second mimicking inflammatory bowel disease in order to understand the potential role of this receptor in persistent inflammatory responses. It was found that in the absence of activating signals from PILRβ, antigen-presenting cells (APCs) produced increased amounts of IL-27, p28 and promoted IL-10 production in effector T cells. The sustained production of IL-27 led ultimately to enhanced survival after challenge due to dampened immune pathology in the gut. Similar protection was also observed in the CNS during chronic T. gondii infection after i.p. challenge again providing evidence that PILRβ is important for regulating aberrant inflammatory responses.
DLOLIS-A: Description Logic based Text Ontology Learning

Ontology Learning has been the subject of intensive study for the past decade. Researchers in this field have been motivated by the possibility of automatically building a knowledge base on top of text documents so as to support reasoning based knowledge extraction. While most works in this field have been primarily statistical (known as light-weight Ontology Learning) not much attempt has been made in axiomatic Ontology Learning (called heavy-weight Ontology Learning) from Natural Language text documents. Heavy-weight Ontology Learning supports more precise formal logic-based reasoning when compared to statistical ontology learning. In this paper we have proposed a sound Ontology Learning tool DLOL_(IS-A) that maps English language IS-A sentences into their equivalent Description Logic (DL) expressions in order to automatically generate a consistent pair of T-box and A-box thereby forming both regular (definitional form) and generalized (axiomatic form) DL ontology. The current scope of the paper is strictly limited to IS-A sentences that exclude the possible structures of: (i) implicative IS-A sentences, and (ii) "Wh" IS-A questions. Other linguistic nuances that arise out of pragmatics and epistemic of IS-A sentences are beyond the scope of this present work. We have adopted Gold Standard based Ontology Learning evaluation on chosen IS-A rich Wikipedia documents.
Tree, funny, to_read, google: what are tags supposed to achieve? a comparative analysis of user keywords for different digital resource types

Social tagging systems have become increasingly popular over the past years. Users' tagging practices have been little studied and understood so far. However, understanding tagging behaviour can contribute towards a thorough understanding of the tagging phenomenon from multiple perspectives. In the present paper, results of a comparative analysis of tag characteristics on the tagging platforms connotea.org (scientific articles), del.icio. us (bookmarks), flickr.com (photos), and youtube.com (videos) are presented. Results show that differences in tagging behaviour can be observed for different digital resource types. Finally, a short discussion of the possible implications of the results for the design of future tagging systems is presented.
A Context, Rule and Role-Based Access Control Model In Enterprise Pervasive Computing Environment

With the enterprise applications being integrated into the pervasive computing environment, the traditional role-based access control model has not been suitable to the new requirements of dynamic controlling the access authority of enterprise resources. In this paper, a context, rule and role-based access control model in enterprise pervasive computing environment is proposed. Through dynamic context and rule-based controlling of the permissions of access enterprise resources, the model repaired the vulnerabilities of the static management existing in the role-based access authority of the traditional RBAC model. The model can provide a simple and efficient solution to integrate the enterprise applications into pervasive computing environment. It is also verified that the proposed model can be applied into the enterprise applications in the pervasive computing environment by the implementation of a prototype system
A Web-based and integrated hospital information system

A Web-based and integrated hospital information system (WIHIS), is presented in this paper. WIHIS is a three-tier Web-based system and focuses on medical information instead of financial affairs. It is integrated with workflow engine to automatize the management and supervising of medical business process as well as rule engine to separate business rules from program code. It could use XML as integration media and adopt a top-down integration strategy to integrate heterogeneous electronic medical records distributed in different sources.