Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Workflow Benchmarking: Open Research Challenges

Workflow Management Systems (WfMS) provide platforms for delivering complex service-oriented applications that need to satisfy enterprise-grade quality of service requirements such as dependability and scalability. The performance of these applications largely depends on the performance of the WfMS supporting them. Comparing the performance of different WfMSs and optimizing their configuration requires that appropriate benchmarks are made available. In this position paper we make the case for benchmarking the performance of WfMSs that are compliant with the Business Process Model and Notation 2.0 standard and explore most of the challenges that one must tackle when constructing such benchmarks.
Robust Linear Regression Analysis— A Greedy Approach

The task of robust linear estimation in the presence of outliers is of particular importance in signal processing, statistics and machine learning. Although the problem has been stated a few decades ago and solved using classical (considered nowadays) methods, recently, it has attracted more attention in the context of sparse modeling, where several notable contributions have been made. In the present manuscript, a new approach is considered in the framework of greedy algorithms. The noise is split into two components: a) the inlier bounded noise and b) the outliers, which are explicitly modeled by employing sparsity arguments. Based on this scheme, a novel efficient algorithm (Greedy Algorithm for Robust Denoising-GARD), is derived. GARD alternates between a least square optimization criterion and an Orthogonal Matching Pursuit (OMP) selection step that identifies the outliers. The case where only outliers are present has been studied separately, where bounds on the Restricted Isometry Property guarantee that the recovery of the signal via GARD is exact. Moreover, theoretical results concerning convergence as well as the the recovery of the support of the sparse outlier vector and derivation of error bounds in the case of additional bounded noise are discussed. Finally, we provide extensive simulations, which demonstrate the comparative advantages of the new technique.
An open-label, non-randomized comparison of venlafaxine and gabapentin as monotherapy or adjuvant therapy in the management of neuropathic pain in patients with peripheral neuropathy

Although many therapies are used in the management of neuropathic pain (NeP) due to polyneuropathy (PN), few comparison studies exist. We performed a prospective, non-randomized, unblended, efficacy comparison of the serotonin-norepinephrine reuptake inhibitor venlafaxine, as either monotherapy or adjuvant therapy, with a first-line medication for NeP, gabapentin, in patients with PN-related NeP. VAS pain scores were assessed after 3 and 6 months in intervention groups and in a cohort of patients receiving no pharmacotherapy. In a total of 223 patients, we analyzed pain quantity and quality (visual analogue scale [VAS] score, Brief Pain Inventory [BPI]), quality of life and health status measures [EuroQol 5 Domains, EQ-5D], Medical Outcomes Sleep Study Scale [MOSSS], Hospital Anxiety and Depression Scale [HADS] and Short Form 36 Health Survey [SF-36]) after 6 months of therapy. Significant improvements in VAS pain scores occurred for all treatment groups after 6 months. Improvements in aspects of daily life and anxiety were identified in all treatment groups. Our data suggest that monotherapy or adjuvant therapy with venlafaxine is comparable to gabapentin for NeP management. We advocate for head-to-head, randomized, double-blinded studies of current NeP therapies.
The Polynomial Method and Restricted Sums of Congruence Classes

Abstract We present a simple and general algebraic technique for obtaining results in Additive Number Theory, and apply it to derive various new extensions of the Cauchy–Davenport Theorem. In particular we obtain, for subsets A 0 , A 1 , …, A k of the finite field Z p , a tight lower bound on the minimum possible cardinality of[formula]as a function of the cardinalities of the sets A i .
Pockets of Excellence: Teacher Beliefs and Behaviors That Lead to High Student Achievement at Low Achieving Schools

This qualitative multiple case study examined the beliefs and behaviors of three teachers who worked at former Reading First Schools and whose student population consistently scored 10% above state average on the California Standards Test (CST) in English language arts. Test scores of all teachers who taught under the Reading First initiative at 29 schools in a county in Southern California were considered. Consent to participate was secured for three teachers who met the study’s selection criteria. To identify the behaviors and beliefs of these teachers, the researcher conducted classroom observations and interviews with the teachers and their principals. The information gathered was coded and triangulated, and then reported by themes. The findings revealed that participating teachers believed that all students could and would learn, and that student learning was a direct reflection of their teaching. They also believed that for learning to take place, teachers engaged in their own professional learning and provided appropriate instruction. Professional learning included collaborating with colleagues and analyzing student data. Appropriate instruction included behaviors that engaged students in learning activities and provided a positive class climate. The findings of this study will contribute to teachers’ and school principals’ understanding of behaviors and beliefs of effective teachers. The study findings might also inform professional development for teachers and identify areas in which more research would be beneficial to the field of education in general and the teaching profession in particular.
A Nomogram Predicting Extrahepatic Metastases for Patients with Adjuvant Transarterial Chemoembolization after Hepatectomy

Background: Prognosis remains poor for hepatocellular carcinoma (HCC) patients with extrahepatic metastases (EHMs). This study aimed to develop a nomogram to predict EHMs in HCC patients who underwent adjuvant transarterial chemoembolization (TACE) following hepatectomy. Methods: Data of 578 HCC patients who underwent TACE after hepatectomy at the Eastern Hepatobiliary Surgery Hospital was retrospectively reviewed. Cox regression analyses was used to select variables to construct the nomogram. Predictive accuracy and discriminative ability of the model were performed using concordance index (C-index), calibration curve and the area under time-dependent receiver operating characteristic (ROC) curve. Results: Postoperative EHMs were detected in 89 and 31 patients in the training cohort (n = 453) and validation cohort (n = 125), respectively. Multivariate analysis showed that tumor size (HR, 1.099; 95% CI, 1.049-1.152), coarse beam type of tumor histopathological structure (HR, 2.382; 95% CI, 1.030-5.512), presence of satellite nodules (HR, 1.936; 95% CI, 1.156-3.244) and alpha-fetoprotein (AFP) (HR, 1.399; 95% CI, 1.098-1.783) were independent risk factors for EHMs (all p < 0.05). The nomogram incorporated these factors achieved good agreement between prediction and actual observation with a concordance index (C-index) of 0.73 (95% CI, 0.68 to 0.78) and 0.71 (95% CI, 0.63 to 0.79) in the training cohort and validation cohort, respectively. In addition, patients who had a nomogram score > 17 were considered to have higher risk for EHMs compared with those scored ≤ 12. Furthermore, the time-dependent area under the ROC curve indicated comparative stability and adequate discriminative ability of the model. Conclusions: This novel nomogram can identify those with high risk of EHMs after adjuvant TACE following hepatectomy. The validation cohort showed a good performance, suggesting it could benefit surgeons on decision-making.
ZigBee network system for observing operating activities of work vehicles

Observing activities of working vehicles on a work site, such as a factory, is important in regard to managing the lifetime of vehicles and achieving high operational availability. However, it is a problem that an administrator cannot completely grasp the activities of a working vehicle. Existing systems cannot cover a large area, particularly in an indoor environment. A system is proposed for monitoring operating activities of working vehicles, regardless of whether they are operating indoors or outdoors. The system calculates the activity rate of a vehicle by analyzing the topology of a network configured by the wireless technology ZigBee. In addition, it was experimentally verified that network topology and RSSI can be used to estimate activities of working vehicles.
On computing givens rotations reliably and efficiently

We consider the efficient and accurate computation of Givens rotations. When <i>f</i> and <i>g</i> are positive real numbers, this simply amounts to computing the values of <i>c</i> = <i>f</i>/√<i>f</i><sup>2</sup> + <i>g</i><sup>2</sup>, <i>s</i> = <i>g</i>/√<i>f</i><sup>2</sup> + <i>g</i><sup>2</sup>, and <i>r</i> = √<i>f</i><sup>2</sup> + <i>g</i><sup>2</sup>. This apparently trivial computation merits closer consideration for the following three reasons. First, while the definitions of <i>c</i>, <i>s</i> and <i>r</i> seem obvious in the case of two nonnegative arguments <i>f</i> and <i>g</i>, there is enough freedom of choice when one or more of <i>f</i> and <i>g</i> are negative, zero or complex that LAPACK auxiliary routines SLARTG, CLARTG, SLARGV and CLARGV can compute rather different values of <i>c</i>, <i>s</i> and <i>r</i> for mathematically identical values of <i>f</i> and <i>g</i>. To eliminate this unnecessary ambiguity, the BLAS Technical Forum chose a single consistent definition of Givens rotations that we will justify here. Second, computing accurate values of <i>c</i>, <i>s</i> and <i>r</i> as efficiently as possible and reliably despite over/underflow is surprisingly complicated. For complex Givens rotations, the most efficient formulas require only one real square root and one real divide (as well as several much cheaper additions and multiplications), but a reliable implementation using only working precision has a number of cases. On a Sun Ultra-10, the new implementation is slightly faster than the previous LAPACK implementation in the most common case, and 2.7 to 4.6 times faster than the corresponding vendor, reference or ATLAS routines. It is also more reliable; all previous codes occasionally suffer from large inaccuracies due to over/underflow. For real Givens rotations, there are also improvements in speed and accuracy, though not as striking. Third, the design process that led to this reliable implementation is quite systematic, and could be applied to the design of similarly reliable subroutines.
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels

Exploiting autocorrelation for node-label prediction in networked data has led to great success. However, when dealing with sparsely labeled networks, common in present-day tasks, the autocorrelation assumption is dicult to exploit. Taking a step beyond, we propose the coinciding walk kernel (cwk), a novel kernel leveraging label-structure similarity ‐ the idea that nodes with similarly arranged labels in their local neighbourhoods are likely to have the same label ‐ for learning problems on partially labeled graphs. Inspired by the success of random walk based schemes for the construction of graph kernels, cwk is defined in terms of the probability that the labels encountered during parallel random walks coincide. In addition to its intuitive probabilistic interpretation, coinciding walk kernels outperform existing kernel- and walk-based methods on the task of node-label prediction in sparsely labeled graphs with high label-structure similarity. We also show that computing cwks is faster than many state-of-the-art kernels on graphs. We evaluate cwks on several realworld networks, including cocitation and coauthor graphs, as well as a graph of interlinked populated places extracted from the dbpedia knowledge base.
ENHANCING PRIVACY IN DISTRIBUTED DATA CLUSTERING

The protocol of privacy-preserving clustering with distributed EM mixture modeling was proposed. However, it is not completely secure in the situation that something more than just the model parameters are revealed. Specially, when the dataset is horizontally partitioned into just two parts, this reveals extra information. The aim of this work is firstly to develop a more general protocol which allows the number of participating parties to be arbitrary and more secure. Secondly, we propose a better method for the case in which the dataset is horizontally partitioned into only two parts. This method allows computing covariance matrices and final results without revealing the private information and the clustering centers. Tóm tắt. Mô. t số giao thú. c da’m ba’o t́ınh riêng tu. trong bài toán phân cu.m dũ. liê. u du. a trên thuâ. t toán EM dã du.o. c dè̂ xuất trong cô. ng dồng nghiên cú. u. Tuy nhiên, các giao thú. c này không hoàn toàn da’m ba’o t́ınh riêng tu. , v̀ı trong mô. t số t̀ınh huống mô. t vài tham số cu’a mô h̀ınh có thê’ bi. lô. , dă. c biê. t khi tâ. p dũ. liê. u chı’ du.o. c phân thành hai phà̂n theo chiè̂u ngang. Bài báo này gió. i thiê. u hai dóng góp ch́ınh trong mô. t phu.o.ng pháp mó. i gia’ i bài toán trên. Mô. t là giao thú. c mó. i cho phép mô. t số lu.o. ng tùy ý các thành viên tham gia vào viê. c phân cu.m dũ. liê. u và da’m ba’o tốt ho.n t́ınh riêng tu. cho dũ. liê. u cu’a các thành viên. Hai là lò. i gia’ i tốt ho.n trong tru. ̀o.ng ho. p tâ. p dũ. liê. u chı’ du.o. c phân thành hai phà̂n theo chiè̂u ngang. Phu.o.ng pháp này cho phép t́ınh toán các ma trâ. n hiê. p phu.o.ng sai và các kết qua’ cuối vó. i viê. c da’m ba’o không làm lô. các thông tin riêng tu. cũng nhu. dối tu.o. ng trung tâm cu’a mỗi cu.m dũ. liê. u.
Automatic detection and correction of pronunciation errors for foreign language learners: the demosthenes application

This paper accounts for the DEMOSTHENES application, an interactive tool for the correction of foreign language learners' pronunciation. After giving the didactic and technical arguments advocating for DEMOSTHENES, the authors describe the phase of creation and labelling of a sound database for the application language (Dutch). The methodolgy for the training of the recognizer is then discussed, as well as the pronunciation scoring paradigm. To conclude, the final application is described, together with preliminary but promising results.
Representing Task and Machine Heterogeneities for Heterogeneous Computing Systems

ABSTRACT A distributed heterogeneous computing (HC) system consists of diversely capable machines harnessed together to execute a set of tasks that vary in their computational requirements. Heuristics are needed to map (match and schedule) tasks onto machines in an HC system so as to optimize some figure of merit. An HC system model is needed to simulate different HC environments to allow the study of the relative performance of different mapping heuristics under different circumstances. This paper characterizes a simulated HC environment by using the expected execution times of the tasks that arrive in the system on the different machines present in the system. This information is arranged in an “expected time to compute” (ETC) matrix as a model of the given HC system, where the entry (i, j) is the expected execution time of task i on machine j. The ETC model is used to express the heterogeneity among the runtimes of the tasks to be executed, and among the machines in the HC system. An existing range-based technique to express heterogeneity in ETC matrices is described. A coefficient-of-variation based technique to express heterogeneity in ETC matrices is proposed, and compared with the range-based technique. The coefficient-of-variation-based ETC generation method provides a greater control over the spread of values (i.e., heterogeneity) in any given row or column of the ETC matrix than the range-based method.
Cost-sensitive classification with genetic programming

Cost-sensitive classification is an attractive topic in data mining. Although genetic programming (GP) technique has been applied to general classification, to our knowledge, it has not been exploited to address cost-sensitive classification in the literature, where the costs of misclassification errors are non-uniform. To investigate the applicability of GP to cost-sensitive classification, this paper first reviews the existing methods of cost-sensitive classification in data mining. We then apply GP to address cost-sensitive classification by means of two methods through: a) manipulating training data, and b) modifying the learning algorithm. In particular, a constrained genetic programming (CGP), a GP-based cost-sensitive classifier, has been introduced in this study. CGP is capable of building decision trees to minimize not only the expected number of errors, but also the expected misclassification costs through a novel constraint fitness function. CGP has been tested on the heart disease dataset and the German credit dataset from the UCI repository. Its efficacy with respect to cost has been demonstrated by comparisons with non-cost-sensitive learning methods and cost-sensitive learning methods in terms of the costs.
The uplink and downlink design of MIMO-SCMA system

Sparse code multiple access (SCMA) is a novel kind of air interface technology which can dramatically improve spectral efficiency of wireless radio access. Different from conventional CDMA and OFDMA, SCMA achieves the non-orthogonal multiple access of frequency domain. On the other hand, Multiple-Input Multiple-Output (MIMO) can make full use of spatial-domain resource to improve system performance without a corresponding increase in spectrum resource. This paper firstly combines SCMA and illustrates the system model and scheme. Particularly, Vertical Bell Labs Layered Space Time (V-BLAST) Coding and Space Time Block Coding (STBC) are applied in uplink and downlink respectively. The theoretical derivation and simulation results demonstrate that the integration of the two kinds of technology can achieve better performance.
3D Diagnostic Imaging of Blood Vessels using an X-Ray Rotational Angiographic System

In this paper, we describe a prototype system that. reconstructs three-dimensional (3D) blood vessels image from cone-beam projection images and analyzes the 3D reconstructed image. Several 3D reconstruction methods utilize biplane or stereo angiographic system and assume the cross section shapes of blood vessels (e.g. ellipse). However, the information provided by a few projections is insufficient for reconstructing a precise 3D image of blood vessels. Furthermore, the assumption of cross sectional shapes is not usually valid for abnormal blood vessels. In the present method using an X-ray rotational angiographic system, digital angiograms are collected in a short period time and a 3D image of blood vessels is approximately reconstructed using a short scan cone-beam reconstruction algorithm. The analysis method is based on the structure description of 3D blood vessels image. The procedure approximates the centerline of 3D blood vessels image using a 3D thinning algorithm and extracts the geometrical features of the 3D line pattern. Final graph data-structure is realized by the list representation with attributions representing geometrical features like edge points, branchings, and loops. From results of the application to patient's cerebral blood vessels, we present the ~. ffectiveness of the system.
State dependence, personality, and plants: light‐foraging decisions in Mimosa pudica (L.)

Abstract Plants make foraging decisions that are dependent on ecological conditions, such as resource availability and distribution. Despite the field of plant behavioral ecology gaining momentum, ecologists still know little about what factors impact plant behavior, especially light‐foraging behavior. We made use of the behavioral reaction norm approach to investigate light foraging in a plant species that exhibits rapid movement: Mimosa pudica. We explored how herbivore avoidance behavior in M. pudica (which closes its leaflets temporarily when disturbed) is affected by an individual's energy state and the quality of the current environment and also repeatedly tested the behavior of individuals from two seed sources to determine whether individuals exhibit a “personality” (i.e., behavioral syndrome). We found that when individuals are in a low‐energy state, they adopt a riskier light‐foraging strategy, opening leaflets faster, and not closing leaflets as often in response to a disturbance. However, when plants are in a high‐energy state, they exhibit a plastic light‐foraging strategy dependent on environment quality. Although we found no evidence that individuals exhibit behavioral syndromes, we found that individuals from different seed sources consistently behave differently from each other. Our results suggest that plants are capable of making state‐dependent decisions and that plant decision making is complex, depending on the interplay between internal and external factors.
Annotation by Category: ELAN and ISO DCR

The Data Category Registry is one of the ISO initiatives towards the establishment of standards for Language Resource management, creation and coding. Successful application of the DCR depends on the availability of tools that can interact with it. This paper describes the first steps that have been taken to provide users of the multimedia annotation tool ELAN, with the means to create references from tiers and annotations to data categories defined in the ISO Data Category Registry. It first gives a brief description of the capabilities of ELAN and the structure of the documents it creates. After a concise overview of the goals and current state of the ISO DCR infrastructure, a description is given of how the preliminary connectivity with the DCR is implemented in ELAN.
A Review of Propagation Algorithms for Imprecise Probabilities

This paper reviews algorithms for local computation with imprecise probabilities. These algorithms try to solve problems of inference (calculation of conditional or unconditional probabilities) in cases in which there are a large number of variables. There are two main types depending on the nature of assumed independence relationships in each case. In both of them the global knowledge is composed of several pieces of local information. The objective is to carry out a sound global computation but mainly using the initial local representation.
Optimization of the marinating conditions of cassava fish (Pseudotolithus sp.) fillet for Lanhouin production through application of Doehlert experimental design

Abstract Lanhouin is a traditional fermented salted fish made from the spontaneous and uncontrolled fermentation of whole salted cassava fish (Pseudotolithus senegalensis) mainly produced in the coastal regions of West Africa. The combined effects of NaCl, citric acid concentration, and marination time on the physicochemical and microbiological characteristics of the fish fillet used for Lanhouin production were studied using a Doehlert experimental design with the objective of preserving its quality and safety. The marination time has significant effects on total viable and lactic acid bacteria counts, and NaCl content of the marinated fish fillet while the pH was significantly affected by citric acid concentration and marination duration with high regression coefficient R 2 of 0.83. The experiment showed that the best conditions for marination process of fish fillet were salt ratio 10 g/100 g, acid citric concentration 2.5 g/100 g, and marination time 6 h. These optimum marinating conditions obtained present the best quality of marinated flesh fish leading to the safety of the final fermented product. This pretreatment is necessary in Lanhouin production processes to ensure its safety quality.