Miracle-dz/UniFAR-FTUs huggingface dataset:
Penalty-free sparse PCA Conference Item

A drawback of the sparse principal component analysis (PCA) procedures using penalty functions is that the number of zeros in the matrix of component loadings as a whole cannot be specified in advance. We thus propose a new sparse PCA procedure in which the least squares PCA loss function is minimized subject to a pre-specified number of zeros in the loading matrix. The procedure is called unpenalized sparse matrix PCA (USMPCA), as it does not use a penalty function and obtains component loadings matrix-wise, i.e., simultaneously rather than sequentially. The key point of USMPCA is to use the fact that the PCA loss function can be decomposed into sum of two terms, one of them irrelevant to loadings, and another one being a function easily minimized under the considered cardinality constraint. This decomposition makes it possible to construct an efficient alternate least squares algorithm for USMPCA. Another useful feature is that the PC score matrix is column-orthonormal, which helps to define naturally the percentage of explained variance by the sparse PCs. USMPCA is illustrated with real data examples.
A BDD-based BMC Approach for the Verification of Multi-Agent Systems

We present a technique combining binary decision diagrams and bounded model checking for the verification of a temporal epistemic logic; a method for distributing the bounded verification process is also discussed. We include implementation details of these proposed approaches as an extension to MCMAS, a BDD-based model checker for multi-agent systems. The “Train Gate Controller” scenario is adapted to display faults and is used to provide a comparison with the original implementation. When variable reordering in the underlying library is disabled the serial bounded technique is shown to be effective; for satisfiable formulae the overhead imposed is negligible. The initial results for our distributed technique demonstrate that it out-performs the sequential approach for falsifiable formulae. Experimental data indicates that increasing the number of hosts improves verification efficiency.
Distributed retrieval of management information: is it about mobility, locality or distribution?

In this paper we present results from an experimental study addressing the use of mobile agents in the retrieval of management information. We compare several agent-based models for distributed collection and processing of management data, focusing on performance but also considering network traffic and setup costs. This study reveals that in many situations the performance of mobile agent systems is mainly determined by distribution, rather than locality. Furthermore, it shows that despite its importance in the flexibility and adaptability of the management system, agent mobility does not increase the system performance.
Epstein-Barr Virus Induces Erosive Arthritis in Humanized Mice

Epstein-Barr virus (EBV) has been implicated in the pathogenesis of rheumatoid arthritis (RA) on the basis of indirect evidence, such as its presence in affected joint tissues, antigenic cross reactions between EBV and human proteins, and elevated humoral and cellular anti-EBV immune responses in patients. Here we report development of erosive arthritis closely resembling RA in humanized mice inoculated with EBV. Human immune system components were reconstituted in mice of the NOD/Shi-scid/IL-2Rγnull (NOG) strain by transplantation with CD34+ hematopoietic stem cells isolated from cord blood. These humanized mice were then inoculated with EBV and examined pathologically for the signs of arthritis. Erosive arthritis accompanied by synovial membrane proliferation, pannus formation, and bone marrow edema developed in fifteen of twenty-three NOG mice transplanted with human HSC and inoculated with EBV, but not in the nine NOG mice that were transplanted with HSC but not inoculated with EBV. This is the first report of an animal model of EBV-induced arthritis and strongly suggest a causative role of the virus in RA.
Route Planning for Unmanned Aircraft Based on Ant Colony Optimization and Voronoi Diagram

The technology based on ant colony optimization and Voronoi diagram was used to achieve the intelligent route planning for unmanned aircraft. First, the Voronoi weighted direction diagram was created by the threat sources distribution and the threat costs. Then the ant colony optimization was used to find out the best route from all the possible routes. Simulation was carried out to find the best route by the Matlab soft, the results showed the UAV route planning based on Voronoi diagram and ant colony optimization was right and effective.
Trends of Homework in Mathematics: Comparative Research Based on TIMSS Study

Homework is a common instructional practice that is used to motivate students, develop students’ studying skills and habits, inform parents about student learning, and increase student achievement. Homework provides an opportunity for students to revisit daily topics, and improve students’ understanding of math concepts and problem-solving skills, helps students learn from their mistakes, and prepare for tests. One of the primary goals of this study was to find the trends of homework frequency. This study used TIMSS 2003, 2007, 2011, and 2015 data for Singapore, United States, Slovenia, and Turkey. The study used hierarchical multiple regression analyses to examine the relationship between homework frequency and student achievement in fourthand eighth-grade mathematics in Slovenia, Singapore, Turkey, and US. The study also sought optimal homework frequencies in those countries. The study found that homework frequency significantly effects student achievement in 8th grade but not in 4th grade. The study also found that trend of the assigning homework from 2003 to 2015 is negative both in 4th and 8 grades in all selected countries, except in Turkey.
Validity, Reliability, and Responsiveness of the Brief Pain Inventory in Inflammatory Bowel Disease

Background and Aims. No patient-reported outcome measures targeting pain have yet been validated for use in IBD patients. Consequently, the aim of this study was to test the psychometrical properties of the brief pain inventory (BPI) in an outpatient population with IBD. Methods. Participants were recruited from nine hospitals in the southeastern and western parts of Norway. Clinical and sociodemographic data were collected, and participants completed the BPI, as well as the Short-Form 36 (SF-36). Results. In total, 410 patients were included. The BPI displayed high correlations with the bodily pain dimension of the SF-36, as well as moderate correlations with disease activity indices. The BPI also displayed excellent internal consistency (Cronbach's alpha value of 0.91, regardless of diagnosis) and good to excellent test-retest values (intraclass correlation coefficient (ICC) 0.84–0.90 and Kappa values > . 70). In UC, calculation of responsiveness revealed that only BPI interference in patients reporting improvement reached the threshold of 0.2. In CD, Cohen's d ranged from 0.26 to 0.68. Conclusions. The BPI may serve as an important supplement in patient-reported outcome measurement in IBD. There is need to confirm responsiveness in future studies. Moreover, responsiveness should ideally be investigated using changes in objective markers of inflammation.
An advanced and distributed control architecture based on intelligent agents and neural networks

A new layered architecture for the implementation of intelligent distributed control systems is proposed. The proposed architecture distinguishes four layers in a distributed control system. Upper layer consists of a digital control layer, where high level decisions are taken. This level is implemented by means of intelligent agents that carry out the discrete control functions, system supervision as well as diagnosis and fault tolerance. Third layer deals with numeric values, performs analog operations and implement analog control loops. It is also in carry of the conversion from numerical variables values to evaluated expressions. This layer has been implemented by means of neural networks. Communications network appears in the second layer. Selected network was CAN (controller area network) because of its particular characteristics. Finally, every node should implement a hardware interface with the process to control. Some interesting characteristics provided by this architecture are its low-cost implementation, easy distribution through a communication network, distributed execution in virtual generic nodes-with no hardware dependency-, bounded response time and fault tolerance mechanisms
Outage Probability Analysis on Multiple-Access Relaying Channel with Analog Network Coding

The work interests in the one-way multiple-access relaying channel (MARC), in which analog network coding (ANC) is employed. The one-way MARC relaying channel consists of two source nodes, one relay node, and one destination node, all of which work in half-duplex state. The two source nodes want to transmit information to destination node with the help of relay. For the scheme, the outage probabilities of the two source signals, basic signal and additional signal, are obtained by strict mathematical process and deduction under the assumption of high signal-to-noise ratio (SNR). With the obtained outage probability, the impact of source power allocation on the performance of the one-way MARC is analyzed. The numerical results of both throughput and outage probability show that the results obtained are reasonable.
Tailored antihypertensive drug therapy prescribed to older women attenuates circulating levels of interleukin-6 and tumor necrosis factor-α

Objective To test the hypothesis that antihypertensive drug therapy produces anti-inflammatory effects in clinical practice, this study investigated circulating levels of selected proinflammatory mediators (interleukin-6 [IL-6], tumor necrosis factor-alpha [TNF-α], and interferon-γ [INF-γ]) in response to multivariate drug directions for blood pressure (BP) control. Methods Prospective study involving 110 hypertensive, community-dwelling older women with different metabolic disorders. A short-term BP-lowering drug therapy was conducted according to current Brazilian guidelines on hypertension, and basal cytokine levels were measured before and after intervention. Results Interventions were found to represent current hypertension-management practices in Brazil and corresponded to a significant reduction in systolic and diastolic BP levels in a whole-group analysis, as well as when users and nonusers of the most common therapeutic classes were considered separately. Considering all patients, mean IL-6 and TNF-α levels showed a significant decrease in circulating concentrations (P<0.01) at the endpoint compared with baseline, whereas the mean INF-γ level was not significantly different from baseline values. In separate analyses, only users of antagonists of the renin–angiotensin system and users of diuretics exhibited the same significant treatment-induced reduction in serum IL-6 and TNF-α observed in the whole group. Conclusion Our data demonstrates that a clinically guided antihypertensive treatment is effective in reversing the low-grade proinflammatory state of serum cytokines found in postmenopausal women and support extracardiac benefits from diuretics and renin–angiotensin system antagonists.
Oriented pooling for dense and non-dense rotation-invariant features

This paper proposes a pooling strategy for local descriptors to produce a vector representation that is orientation-invariant yet implicitly incorporates the relative angles between features measured by their dominant orientation. This pooling is associated with a similarity metric that ensures that all the features have undergone a comparable rotation. This approach is especially effective when combined with dense oriented features, in contrast to existing methods that either rely on oriented features extracted on key points or on non-oriented dense features. The interest of our approach in a retrieval scenario is demonstrated on popular benchmarks comprising up to 1 million database images.
Boosting strategy for classification

This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifiers in terms of the 2-norm of the margin slack vector. We develop an effective, adaptive and robust boosting algorithm, DMBoost, by optimising this bound. The soft margin based quadratic loss function is insensitive to points having a large margin. The algorithm improves the generalisation performance of a system by ignoring the examples having small or negative margin. We evaluate the efficacy of the proposed method by applying it to a text categorization task. Experimental results show that DMBoost performs significantly better than AdaBoost, hence validating the effectiveness of the method. Furthermore, experimental results on UCI data sets demonstrate that DMBoost generally outperforms AdaBoost.
On-line Detection of Quality Problems in Continuous Casting of Steel

Quality problems in continuous casting of steel can be identified as they occur by monitoring mold signals (level sensor, thermocouples in the mold walls, friction etc.) and taking appropriate action (such as slowing casting speed, changing taper, changing a clogged nozzle, or later visual inspection of the surface for possible downgrading. Surface depressions and groups of deep oscillation marks form at meniscus and reduce local heat transfer as they move down the mold at the casting speed. This slows shell growth, increases shell surface temperature, and causes characteristic dips in mold thermocouple signals. More importantly, they are also associated with longitudinal cracks. Characteristic thermocouple signatures have been identified for many defects, including sticker breakouts, transverse depressions and deep oscillation marks, narrow-face bleeds, transverse corner cracks, longitudinal cracks, mold level fluctuation defects, and other problems. With the help of computational models, these mold signals should be used to troubleshoot defects, and to take appropriate corrective action.
Mining Performance Regression Testing Repositories for Automated Performance Analysis

Performance regression testing detects performance regressions in a system under load. Such regressions refer to situations where software performance degrades compared to previous releases, although the new version behaves correctly. In current practice, performance analysts must manually analyze performance regression testing data to uncover performance regressions. This process is both time-consuming and error-prone due to the large volume of metrics collected, the absence of formal performance objectives and the subjectivity of individual performance analysts. In this paper, we present an automated approach to detect potential performance regressions in a performance regression test. Our approach compares new test results against correlations pre-computed performance metrics extracted from performance regression testing repositories. Case studies show that our approach scales well to large industrial systems, and detects performance problems that are often overlooked by performance analysts.
CAFTL: A Content-Aware Flash Translation Layer Enhancing the Lifespan of Flash Memory based Solid State Drives

Although Flash Memory based Solid State Drive (SSD) exhibits high performance and low power consumption, a critical concern is its limited lifespan along with the associated reliability issues. In this paper, we propose to build a Content-Aware Flash Translation Layer (CAFTL) to enhance the endurance of SSDs at the device level. With no need of any semantic information from the host, CAFTL can effectively reduce write traffic to flash memory by removing unnecessary duplicate writes and can also substantially extend available free flash memory space by coalescing redundant data in SSDs, which further improves the efficiency of garbage collection and wear-leveling. In order to retain high data access performance, we have also designed a set of acceleration techniques to reduce the runtime overhead and minimize the performance impact caused by extra computational cost. Our experimental results show that our solution can effectively identify up to 86.2% of the duplicate writes, which translates to a write traffic reduction of up to 24.2% and extends the flash space by a factor of up to 31.2%. Meanwhile, CAFTL only incurs a minimized performance overhead by a factor of up to 0.5%.
Impact of the Quality of ERP Implementations on Business Value

This study compares the financial performance trend of successful and less successful ERP implementers over three years following the implementation. The findings indicate no significant difference in the change in ROA and ROI of the two groups of adopters. Successful ERP adopters however have statistically significant higher efficiency benefits in terms of Asset Turnover and Capital Turnover than the less successful ERP adopters in the first two years after implementation. The findings of this paper reveal no significant contribution of the implementation effort to the success of ERP implementations.
A New Tool for Investigating the Functional Testing of the VOR

Peripheral vestibular function may be tested quantitatively, by measuring the gain of the angular vestibulo-ocular reflex (aVOR), or functionally, by assessing how well the aVOR performs with respect to its goal of stabilizing gaze in space and thus allow to acquire visual information during the head movement. In recent years, several groups have developed clinical and quantitative approaches to functional testing of the vestibular system based on the ability to identify an optotype briefly displayed on screen during head rotations. Although the proposed techniques differ in terms of the parameters controlling the testing paradigm, no study has thus far dealt with understanding the role of such choices in determining the effectiveness and reliability of the testing approach. Moreover, recent work has shown that peripheral vestibular patients may produce corrective saccades during the head movement (covert saccades), yet the role of these eye movements toward reading ability during head rotations is not yet understood. Finally, no study has thus far dealt with measuring the true performance of their experimental setups, which is nonetheless likely to be crucial information for understanding the effectiveness of functional testing approaches. Thus we propose a new software and hardware research tool allowing the combined measurement of eye and head movements, together with the timing of the optotype on screen, during functional testing of the vestibulo-ocular reflex (VOR) based on the Head Impulse Test. The goal of such tool is therefore that of allowing functional testing of the VOR while collecting the experimental data necessary to understand, for instance, (a) the effectiveness of the covert saccades strategy toward image stabilization, (b) which experimental parameters are crucial for optimizing the diagnostic power of the functional testing approach, and (c) which conditions lead to a successful reading or an error trial.
A Hierarchical Checksum Scheme for SCTP over Wireless Networks with Worse Channel Condition

Stream Control Transmission Protocol (SCTP) uses an overall checksum scheme for each segment, by which a corrupted packet will be regarded as a lost one. This may result in degradation of SCTP's throughput performance over wireless networks. This paper proposes a hierarchical checksum scheme for SCTP, in which several checksum fields are distributed within a segment for different coverages. The main purpose is to extract the available payload from a corrupted packet and to deliver those in-order data to the upper layer in time so as to reduce the retransmission amount as much as possible. Simulation results show that the performance gain of the proposed scheme could be prominent in the wireless environments with high packet corruption rate, compared to the standard SCTP.
Modeling and Automated Containment of Worms based on object oriented technologies

1565 | P a g e  Abstract— After many Internet-scale worm incidents in recent years, it is clear that a simple self-propagating worm can quickly spread across the Internet and cause severe damage to our society. Facing this great security threat, we need to build an early detection system that can detect the presence of a worm in the Internet as quickly as possible in order to give people accurate early warning information and possible reaction time for counteractions. In this paper, we present a (stochastic) branching process model for characterizing the propagation of Internet worms. The model is developed for uniform scanning worms and then extended to preference scanning worms. Our strategy is based on limiting the number of scans to dark-address space. Our experimental results show that this proposed method is somehow better compared to other techniques.
PABIRS: A data access middleware for distributed file systems

Various big data management systems have emerged to handle different types of applications, which cast very different demands on storage, indexing and retrieval of large amount of data on distributed file system. Such diversity on demands has raised huge challenges to the design of new generation of data access service for big data. In this paper, we present PABIRS, a unified data access middleware to support mixed workloads. PABIRS encapsulates the underlying distributed file system (DFS) and provides a unified access interface to systems such as MapReduce and key-value stores. PABIRS achieves dramatic improvement on efficiency by employing a novel hybrid indexing scheme. Based on the data distribution, the indexing scheme adaptively builds bitmap index and Log Structured Merge Tree (LSM) index. Moreover, PABIRS distributes the computation to multiple index nodes and utilizes a Pregel-based algorithm to facilitate parallel data search and retrieval. We empirically evaluate PABIRS against other existing distributed data processing systems and verify the huge advantages of PABIRS on shorter response time, higher throughput and better scalability, over big data with real-life phone logs and TPC-H benchmark.
A graph based approach to barrier synchronisation minimisation

This paper presents a new graph theoretic approach to minimising the number of barriers in parallelised programs. A simple procedure to reduce the complexity of barrier placement, without athscting optimality, is developed. A new algorithm is then presented which places provably the minimal number of barriers in perfect loop nests. This technique is extended so as to place the minimal number of barriers in certain imperfect loop nest structures. This scheme is generalised to accept entire programs and implemented in a prototype parallelising compiler where it has been applied to several well-known benchmarks and shown to place significantly fewer synchronisation points than an existing commercial compiler.
Enforcing security with behavioral fingerprinting

Although fingerprinting techniques are helpful for security assessment, they have limited support to advanced security related applications. We have developed a new security framework focusing especially on the authentication reinforcement and the automatic generation of stateful firewall rules based on behavioral fingerprinting. Such fingerprinting is highly effective in capturing sequential patterns in the behavior of a device. A new machine learning technique is also adapted to monitor high speed networks by evaluating both computational complexity and experimented performances.