Miracle-dz/UniFAR-FTUs huggingface dataset:
Bicoloring covers for graphs and hypergraphs

Let the {\it bicoloring cover number $\chi^c(G)$} for a hypergraph $G(V,E)$ be the minimum number of bicolorings of vertices of $G$ such that every hyperedge $e\in E$ of $G$ is properly bicolored in at least one of the $\chi^c(G)$ bicolorings. We investigate the relationship between $\chi^c(G)$, matchings, hitting sets, $\alpha(G)$(independence number) and $\chi(G)$ (chromatic number). We design a factor $O(\frac{\log n}{\log \log n-\log \log \log n})$ approximation algorithm for computing a bicoloring cover. We define a new parameter for hypergraphs - "cover independence number $\gamma(G)$" and prove that $\log \frac{|V|}{\gamma(G)}$ and $\frac{|V|}{2\gamma(G)}$ are lower bounds for $\chi^c(G)$ and $\chi(G)$, respectively. We show that $\chi^c(G)$ can be approximated by a polynomial time algorithm achieving approximation ratio $\frac{1}{1-t}$, if $\gamma(G)=n^t$, where $t t$. Let $m(k,x)$ denote the minimum number of hyperedges %in a $k$-uniform hypergraph $G$ such that some $k$-uniform hypergraph $G$ with $m(k,x)$ hyperedges does not have a bicoloring cover of size $x$. We show that $ 2^{(k-1)x-1} < m(k,x) \leq x \cdot k^2 \cdot 2^{(k+1)x+2}$. Let the {\it dependency $d(G)$} of $G$ be the maximum number of hyperedge neighbors of any hyperedge in $G$. We propose an algorithm for computing a bicoloring cover of size $x$ for $G$ if $d(G) \leq(\frac{2^{x(k-1)}}{e}-1)$ using $nx+kx\frac{m}{d}$ random bits.
Domain Based Access Control Model for Distributed Collaborative Applications

This paper describes the design and development of a flexible domain-based access control infrastructure for distributed Collaborative Environments. The paper proposes extensions to classical RBAC models to address typical problems and tasks in the distributed hierarchical resource organisation that came from the practical experience in developing industry oriented virtual laboratories infrastructure, particular: hierarchical resources policy administration, user roles management, dynamic security context and authorisation session management. The paper provides implementation details on the use of XACML for finegrained access control policy definition for domain based resources and roles organisation. The paper analyses the required functionality and suggests extensions to the major service-oriented access generic framework such as Acegi, Globus Toolkit Authorisation framework, and GAAA Authorisation framework in order to support complex resource organisation and collaboration scenarios in dynamic virtualised environments. The paper is based on experiences gained from the industry funded project Collaboratory.nl and other major Grid-based and Grid-oriented projects in collaborative applications and complex resource provisioning.
Resource allocation for multimedia streaming over the Internet

This paper addresses the resource allocation problem for multiple media streaming over the Internet. First, we present an end-to-end transport architecture for multimedia streaming over the Internet. Second, we propose a new multimedia streaming TCP-friendly protocol (MSTFP), which combines forward estimation of network conditions with information feedback control to optimally track the network conditions. Third, we propose a novel resource allocation scheme to adapt media rate to the estimated network bandwidth using each media's rate-distortion function under various network conditions. By dynamically allocating resources according to network status and media characteristics, we improve the end-to-end quality of services (QoS). Simulation results demonstrate the effectiveness of our proposed schemes.
Introducing Flow Field Forecasting

A machine learning methodology, called flow field forecasting, is proposed for statistically predicting the future of a univariate time series. Flow field forecasting draws information from the interpolated flow field of an observed time series to build a forecast step-by-step. Flow field forecasting is presented with examples, a discussion of its properties relative to other common forecasting techniques, and a statistical error analysis.
Unsupervised and Domain Independent Ontology Learning: Combining Heterogeneous Sources of Evidence

Acquiring knowledge from the Web to build domain ontologies has become a common practice in the Ontological Engineering field. The vast amount of freely available information allows collecting enough information about any domain. However, the Web usually suffers a lack of structure, untrustworthiness and ambiguity of the content. These drawbacks hamper the application of unsupervised methods of building ontologies demanded by the increasingly popular applications of the Semantic Web. We believe that the combination of several processing mechanisms and complementary information sources may potentially solve the problem. The analysis of different sources of evidence allows determining with greater reliability the validity of the detected knowledge. In this paper, we present GALeOn (General Architecture for Learning Ontologies) that combines sources and processing resources to provide complementary and redundant evidence for making better estimations about the relevance of the extracted knowledge and their relationships. Our goal in this paper is to show how combining several information sources and extraction mechanisms is possible to build a taxonomy of concepts with a higher accuracy than if only one of them is applied. The experimental results show how this combination notably increases the precision of the obtained results with minimum user intervention.
Ensemble Modeling for Aromatic Production in Escherichia coli

Ensemble Modeling (EM) is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate) to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt), transaldolase (Tal), and phosphoenolpyruvate synthase (Pps) to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning.
Comparison of Multichannel MAC Protocols

This paper compares, through analysis and simulation, a number of multichannel MAC protocols. We first classify these protocols into four categories based on their principles of operation: dedicated control channel, common hopping, split phase, and parallel rendezvous protocols. We then examine the effects of the number of channels and devices, channel switching times, and traffic patterns on the throughput and delay of the protocols. Here are some of the conclusions of our study: (1) parallel rendezvous protocols generally perform better than single rendezvous protocols, (2) the dedicated control channel protocol can be a good approach with its simplicity when the number of channels is high and the packets are long, and (3) the split phase protocol is very sensitive to the durations of the control and data phases. Our study focuses on a single collision domain.
On network simplification for Gaussian Half-Duplex diamond networks

This paper investigates the simplification problem in Gaussian Half-Duplex (HD) diamond networks. The goal is to answer the following question: what is the minimum (worst-case) fraction of the total HD capacity that one can always achieve by smartly selecting a subset of k relays, out of the N possible ones? We make progress on this problem for k = 1 and k = 2 and show that for N = k + 1, k ∈ {1, 2} at least k/k+1 of the total HD capacity is always approximately (i.e., up to a constant gap) achieved. Interestingly, and differently from the Full-Duplex (FD) case, the ratio in HD depends on N, and decreases as N increases. For all values of N and k for which we derive worst case fractions, we also show these to be approximately tight. This is accomplished by presenting N-relay Gaussian HD diamond networks for which the best k-relay subnetwork has an approximate HD capacity equal to the worst-case fraction of the total approximate HD capacity. Moreover, we provide additional comparisons between the performance of this simplification problem for HD and FD networks, which highlight their different natures.
Construction of rate compatible length scalable LDPC codes with low implementation complexity

Due to the rapid development of communication systems, a highly flexible scheme of multi-rate multi-length channel code is urgently required. In this paper, we propose a design method of highly flexible rate-compatible (RC) length-scalable (LS) low density parity check (LDPC) codes, which is based on the progressive extension idea of both information bit/node and parity check bit/node. According to our method, a family of RC-LS-LDPC codes with one common template matrix can be generated, which facilitates hardware implementation. With the aid of multi-edge type density evolution (MET-DE) analysis, the method can achieve near-capacity performance for each code rate and code length. The simulation results show that the designed codes with arbitrary rate and variable code length are within 0.30dB to 0.48dB compared with Shannon limit at bit error rate (BER) =2∗10−9 under BI-AWGN channel.
Influences of the Adrenergic Nervous System on the Repolarization Phase of the Electrocardiogram

The following conclusions can be drawn : (1) The nervous outflow to the heart may be varied from the baseline to opposite directions by different stressful stimuli. (2) ST-T alterations may be induced and abolished by adrenergic activation and inhibition respectively. (3) These effects are dissociated from or not necessarily associated with an exaggerated responsiveness of the cardiac beta receptors. (4) The adrenergic influences on the ST-T abnormalities of myocardial ischemia and hypertension are limited.
Fast Gaussian Process Posteriors with Product Trees

Gaussian processes (GP) are a powerful tool for nonparametric regression; unfortunately, calculating the posterior variance in a standard GP model requires time O(n2) in the size of the training set. Previous work by Shen et al. (2006) used a k-d tree structure to approximate the posterior mean in certain GP models. We extend this approach to achieve efficient approximation of the posterior covariance using a tree clustering on pairs of training points, and demonstrate significant improvements in performance with negligible loss of accuracy.
Robust fault-tolerant control of systems with time-varying structured uncertainties

Robust fault-tolerant control for uncertain systems with time-varying delays is considered in the paper. Basing on the Lyapunov stability theory and the linear matrix inequality (LMI) method, the sufficient condition for the sensor fault system to have robust stabilization and robust fault-tolerant capability is derived. In view of the different fault types, a multi-state fault model is presented. The state feedback controller with perturbation terms is calculated. A numerical example and its simulation results are given to illustrate the effectiveness of the approach.
Hierarchical Modularity: Compilation Management for Standard ML

Many programming languages identify modular units with compilation units, while only few extend this to permit hierarchies of language-level modules within individual compilation units. But when the number of such compilation units is large, then it becomes increasingly important that they themselves can be grouped together and that explicit export interfaces can be used to control namespaces. We explain how the group model implemented in SML/NJ’s compilation manager CM provides the necessary facilities to avoid unwanted interferences between unrelated parts of large programs. We also discuss the problem of automatic dependency analysis as well as its complexity and show ways of avoiding intractability.
A Subject-to-subject Transfer Learning Framework Based on Jensen-Shannon Divergence for Improving Brain-computer Interface

One of the major limitations of current electroencephalogram (EEG)-based brain-computer interfaces (BCIs) is the long calibration time. Due to a high level of noise and non-stationarity inherent in EEG signals, a calibration model trained using limited number of train data may not yield an accurate BCI model. To address this problem, this paper proposes a novel subject-to-subject transfer learning framework that improves the classification accuracy using limited training data. The proposed framework consists of two steps: The first step identifies if the target subject will benefit from transfer learning using cross-validation on the few available subject-specific training data. If transfer learning is required a novel algorithm for measuring similarity, called the Jensen-Shannon ratio (JSR) compares the data of the target subject with the data sets from previous subjects. Subsequently, the previously calibrated BCI subject model with the highest similarity to the target subject is used as the BCI target model. Our experimental results using the proposed framework obtained an average accuracy of 77% using 40 subject-specific trials, outperforming the subject-specific BCI model by 3%.
Machine Translation for Government Applications

Thousands of languages are spoken in the world. The commercial sector provides significant translation capabilities for a few dozen of these, both in the form of trained professionals and in the form of machine translation (MT) systems. However, the U.S. government has many unmet foreign-language requirements that are likely to remain unmet by the commercial sector. Limited resources have affected military operations in Iraq and Afghanistan, where people speak several dialects of Arabic and Kurdish, as well as Pashto, Dari, and Farsi, among other languages. A reasonably short list of languages required for accomplishing the military's needs more broadly would include Chinese, The list of other language translation needs is potentially very long and depends on specific missions and needs. Tactical missions may require face-to-face communication, whereas strategic intelligence operations may involve processing large volumes of language data. The Defense Advanced Research Projects Agency (DARPA) provides substantial funding for MT. The DARPA Global Autonomous Language Exploitation (GALE) program has developed media-monitoring systems for foreign languages, focusing on Arabic and Chinese. These systems can monitor an Arabic Al-Jazeera news program and provide automatic translations into English of high enough quality that output can be examined by English-speaking personnel and routed for subsequent detailed processing by a linguist if necessary. The DARPA Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is developing portable two-way speech-to-speech translation systems that operate on The idea of a mechanical process for converting one human language into another can be traced to a letter written by René Descartes in 1629, and after nearly 400 years, this vision has not been fully realized. Machine translation (MT) using digital computers has been a grand challenge for computer scientists, mathematicians, and linguists since the first international conference on MT was held at the Massachusetts Institute of Technology in 1952. Currently, Lincoln Laboratory is achieving success in a highly focused research program that specializes in developing speech translation technology for limited language resource domains and in adapting foreign-language proficiency standards for MT evaluation. Our specialized research program is situated within a general framework for multilingual speech and text processing for government applications. MacHine tranSlation for governMent applicationS laptops and handheld devices. The translations contain errors, but the systems show strong promise in specialized domains (e.g., operating in a laboratory environment using vocabulary for which the systems have been trained). Outside the specific and perhaps narrow band for which …
A Randomized Pilot Study of Acupuncture as an Adjunct Therapy in Adult Asthmatic Patients

Objective. This trial aimed to evaluate the feasibility of estimating the effectiveness of acupuncture on asthmatic patients under conventional medical management. Participations and Methods. A prospective randomized, patient/assessor-blinded, sham acupuncture–, and waiting list–controlled pilot trial was conducted. Forty-five eligible asthmatic participants underwent a 1-week run-in period and were then randomized into one of three groups: an active acupuncture group, a sham acupuncture group, and a waiting list group. They were instructed to maintain the use of antiasthmatic medications. Needling was administered three times per week for 4 weeks with a 2-week follow-up in the active and sham acupuncture groups. The primary outcome was daily morning peak expiratory flow (PEF) and the secondary outcomes included forced expiratory volume one second (FEV1), quality of life questionnaire for adult Korean asthmatics (QLQAKA), transition dyspnea index (TDI), serum eosinophil count, and total serum immunoglobulin E (IgE). Results. No significant differences in the between- or within-group values of weekly average PEF (recorded daily in the morning) and FEV1 were found. For QLQAKA and TDI, the active acupuncture group showed a significant improvement over the waiting list group at 2, 4, and 6 weeks after randomization. Discussion. Acupuncture as an adjunct therapy to conventional medical care does not seem to affect pulmonary function in asthmatic patients. However, 12 sessions of acupuncture treatment during 4 weeks showed a favorable effect on the quality of life in adult asthmatic patients. Further large trials assessing the effectiveness of acupuncture on the quality of life and symptoms in asthmatic patients are needed.
The strength of strong ties: The importance of Philos in organizations

4-Pyridylthioacetic acid is prepared economically without the formation of any noxious substance by (1) reacting a 4-nitropyridyl-N-oxide with a lower alkyl thioglycolate or with thioglycolic acid to form 4-thioglycolic acid (or 4-thioglycolate)-pyridyl-N-oxide, (2) reducing the latter oxide in the form of its 4-alkyl thioglycolate to obtain the corresponding 4-pyridylthioglycolic acid ester, and (3) converting said ester into a 4-pyridylthioacetic acid by saponification followed by acidification. When a lower alkyl thioglycolate is used for the reaction in step (1), step (2) can follow directly for reduction of the reaction product, and high yields are obtained.
An Appraisal of Content-Based Image Retrieval (CBIR) Methods

Background: Content Based Image Retrieval (CBIR) is an aspect of computer vision and image processing that finds images that are similar to a given query image in a large scale database using the visual contents of images such as colour, texture, shape, and spatial arrangement of regions of interest (ROIs) rather than manually annotated textual keywords. A CBIR system represents an image as a feature vector and measures the similarity between the image and other images in the database for the purpose of retrieving similar images with minimal human intervention. The CBIR system has been deployed in several fields such as fingerprint identification, biodiversity information systems, digital libraries, Architectural and Engineering design, crime prevention, historical research and medicine. There are several steps involved in the development of CBIR systems. Typical examples of these steps include feature extraction and selection, indexing and similarity measurement. Problem: However, each of these steps has its own method. Nevertheless, there is no universally acceptable method for retrieving similar images in CBIR. Aim: Hence, this study examines the diverse methods used in CBIR systems. This is with the aim of revealing the strengths and weakness of each of these methods. Methodology: Literatures that are related to the subject matter were sought in three scientific electronic databases namely CiteseerX, Science Direct and Google scholar. The Google search engine was used to search for documents and WebPages that are appropriate to the study. Results: The result of the study revealed that three main features are usually extracted during CBIR. These features include colour, shape and text. The study also revealed that diverse methods that can be used for extracting each of the features in CBIR. For instance, colour space, colour histogram, colour moments, geometric moment as well as colour correlogram can be used for extracting colour features. The commonly used methods for texture feature extraction include statistical, model-based, and transform-based methods while the edge method, Fourier transform and Zernike methods can be used for extracting shape features. Contributions: The paper highlights the benefits and challenges of diverse methods used in CBIR. This is with the aim of revealing the methods that are more efficient for CBIR. Conclusion: Each of the CBIR methods has their own advantages and disadvantages. However, there is a need for a further work that will validate the reliability and efficiency of each of the method.
BendIT { An Interactive Game with two Robots

In this paper we report on an interactive game with two robots and review its components. A human user uses his torso move- ments to steer a Robotino robot along a pre-dened course. Our domes- tic service robot Caesar acts as a referee and autonomously follows the Robotino and makes sure that it stays within a corridor along the path. If the user manages to keep the Robotino within the corridor for the whole path he wins. The game can be used, for example, to engage people in physical training such as a rehabilitation after an injury. It was designed and implemented as a student project in winter term 2011/2012.
Performance Centric Sensor Scheduling in Wireless Sensor Network

In a dense wireless sensor network, multiple sensors sense an event simultaneously and try to transmit the information per application level needs. we investigate the impact of the number of communicating nodes on the estimation performance of dense wireless sensor network based on major MAC protocols. We present a Markov model to illustrate the correlation between packet reception probability and the number of communicating nodes and lossy multi-sensor Kalman filter filter. A sensing threshold based approach for sensor scheduling is proposed.