Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying User Messages For Managing Web Forum Data

Online discussion forums have become a popular medium for users to discuss with and seek information from other users having similar interests. A typical discussion thread consists of a sequence of posts posted by multiple users. All the posts in a thread are not equally useful and serve a different purpose providing different types of information (some posts contain questions, some answers, etc.). Identifying the purpose and nature of each post in a discussion thread is an interesting research problem as it can help in improving information extraction and intelligent assistance techniques [9]. We study the problem of classifying a given post as per its purpose in the discussion thread. We employ features based on the post’s content, structure of the thread, behavior of the participating users and sentiment analysis of post’s content. We achieve decent classification performance and also analyze the relative importance of different features used for the post classification task.
Inter-Task System Fusion for Speaker Recognition

Fusion is a common approach to improving the performance of speaker recognition systems. Multiple systems using different data, features or algorithms tend to bring complementary contributions to the final decisions being made. It is known that factors such as native language or accent contribute to speaker identity. In this paper, we explore inter-task fusion approaches to incorporating side information from accent and language identification systems to improve the performance of a speaker verification system. We explore both score level and model level approaches, linear logistic regression and linear discriminant analysis respectively, reporting significant gains on accented and multi-lingual data sets of the NIST Speaker Recognition Evaluation 2008 data. Equal error rate and expected rank metrics are reported for speaker verification and speaker identification tasks.
Quantitative PL imaging of thin film solar cells — Potential and pitfalls

Photoluminescence imaging as well as quantitative photoluminescence spectroscopy has been successfully applied to different solar cell materials, such as crystalline silicon and polycrystalline Cu(In, Ga)Se2. These methods can be used to investigate spatial inhomogeneities, as well as for the contactless determination of quasi-Fermi level splittings, which are related to the open-circuit voltage in finished photovoltaic devices. The theory underlying the analysis of quantitative PL imaging is found to work reliably for more ideal semiconductors such as silicon, but can pose substantial problems for the more non-ideal semiconductors such as kesterite-type materials, where both the optical properties as well as the recombination process may vary widely from sample to sample. In this contribution we will evaluate different approaches to analyse quantitative PL imaging and discuss the potential pitfalls incurred, especially when the actual sample temperature during the measurement is not properly taken into account.
Acquiring Cyber Threat Intelligence through Security Information Correlation

Cyber Physical Systems (CPS) operating in modern critical infrastructures (CIs) are increasingly being targeted by highly sophisticated cyber attacks. Threat actors have quickly learned of the value and potential impact of targeting CPS, and numerous tailored multi-stage cyber-physical attack campaigns, such as Advanced Persistent Threats (APTs), have been perpetrated in the last years. They aim at stealthily compromising systems' operations and cause severe impact on daily business operations such as shutdowns, equipment damage, reputation damage, financial loss, intellectual property theft, and health and safety risks. Protecting CIs against such threats has become as crucial as complicated. Novel distributed detection and reaction methodologies are necessary to effectively uncover these attacks, and timely mitigate their effects. Correlating large amounts of data, collected from a multitude of relevant sources, is fundamental for Security Operation Centers (SOCs) to establish cyber situational awareness, and allow to promptly adopt suitable countermeasures in case of attacks. In our previous work we introduced three methods for security information correlation. In this paper we define metrics and benchmarks to evaluate these correlation methods, we assess their accuracy, and we compare their performance. We finally demonstrate how the presented techniques, implemented within our cyber threat intelligence analysis engine called CAESAIR, can be applied to support incident handling tasks performed by SOCs.
BugLocalizer: integrated tool support for bug localization

To manage bugs that appear in a software, developers often make use of a bug tracking system such as Bugzilla. Users can report bugs that they encounter in such a system. Whenever a user reports a new bug report, developers need to read the summary and description of the bug report and manually locate the buggy files based on this information. This manual process is often time consuming and tedious. Thus, a number of past studies have proposed bug localization techniques to automatically recover potentially buggy files from bug reports. Unfortunately, none of these techniques are integrated to bug tracking systems and thus it hinders their adoption by practitioners. To help disseminate research in bug localization to practitioners, we develop a tool named BugLocalizer, which is implemented as a Bugzilla extension and builds upon a recently proposed bug localization technique. Our tool extracts texts from summary and description fields of a bug report and source code files. It then computes similarities of the bug report with source code files to find the buggy files. Developers can use our tool online from a Bugzilla web interface by providing a link to a git source code repository and specifying the version of the repository to be analyzed. We have released our tool publicly in GitHub, which is available at: https://github.com/smagsmu/buglocalizer. We have also provided a demo video, which can be accessed at: http://youtu.be/iWHaLNCUjBY.
Exploiting Functional Dependence in Bayesian Network Inference

In this paper we propose an efficient method for Bayesian network inference in models with functional dependence. We generalize the multiplicative factorization method originally designed by Takikawa and D'Ambrosio (1999) for models with independence of causal influence. Using a hidden variable, we transform a probability potential into a product of two-dimensional potentials. The multiplicative factorization yields more efficient inference. For example, in junction tree propagation it helps to avoid large cliques. In order to keep potentials small, the number of states of the hidden variable should be minimized. We transform this problem into a combinatorial problem of minimal base in a particular space. We present an example of a computerized adaptive test, in which the factorization method is significantly more efficient than previous inference methods.
Genome engineering of isogenic human ES cells to model autism disorders

Isogenic pluripotent stem cells are critical tools for studying human neurological diseases by allowing one to study the effects of a mutation in a fixed genetic background. Of particular interest are the spectrum of autism disorders, some of which are monogenic such as Timothy syndrome (TS); others are multigenic such as the microdeletion and microduplication syndromes of the 16p11.2 chromosomal locus. Here, we report engineered human embryonic stem cell (hESC) lines for modeling these two disorders using locus-specific endonucleases to increase the efficiency of homology-directed repair (HDR). We developed a system to: (1) computationally identify unique transcription activator-like effector nuclease (TALEN) binding sites in the genome using a new software program, TALENSeek, (2) assemble the TALEN genes by combining golden gate cloning with modified constructs from the FLASH protocol, and (3) test the TALEN pairs in an amplification-based HDR assay that is more sensitive than the typical non-homologous end joining assay. We applied these methods to identify, construct, and test TALENs that were used with HDR donors in hESCs to generate an isogenic TS cell line in a scarless manner and to model the 16p11.2 copy number disorder without modifying genomic loci with high sequence similarity.
Inadequate Effort on Neuropsychological Evaluation is Associated With Increased Healthcare Utilization

Patients who exert inadequate effort on neuropsychological examination might not receive accurate diagnoses and recommendations, and might not cooperate fully with other aspects of healthcare. This study examined whether inadequate effort is associated with increased healthcare utilization. Of 355 patients seen for routine, clinical neuropsychological examination at a VA Medical Center, 283 (79.7%) showed adequate effort and 72 (20.3%) showed inadequate effort, as determined at time of evaluation using the Word Memory Test and/or Test of Memory Malingering. Utilization data included number of Emergency Department (ED) visits and inpatient hospitalizations in the year following evaluation. Patients who had shown inadequate effort on examination had more Emergency Department visits, more inpatient hospitalizations, and more days of inpatient hospitalization in the year after evaluation, compared to patients who had exerted adequate effort. This finding was not attributable to group differences in age or medical/psychiatric comorbidities. Thus, patients who exerted inadequate effort showed greater healthcare utilization in the year following evaluation. Such patients might use more resources since diagnostic evaluations are inconclusive. Inadequate effort on examination might also serve as a “marker” for more general failure to cooperate fully in one’s healthcare, possibly resulting in greater utilization.
Oxytocin levels are lower in premenopausal women with type 1 diabetes mellitus compared with matched controls

Oxytocin, a hormone most commonly associated with parturition and lactation, may have additional roles in diabetes complications. We determined oxytocin levels in premenopausal women with type 1 diabetes mellitus (T1DM) compared with non‐diabetic controls and examined associations of oxytocin with health behaviours, clinical factors, biomarkers, kidney function and bone health. Lower oxytocin was hypothesized for T1DM.
Maternal Education and Micro-Geographic Disparities in Nutritional Status among School-Aged Children in Rural Northwestern China

Objectives Prior evidence suggests geographic disparities in the effect of maternal education on child nutritional status between countries, between regions and between urban and rural areas. We postulated its effect would also vary by micro-geographic locations (indicated by mountain areas, plain areas and the edge areas) in a Chinese minority area. Methods A cross-sectional study was conducted with a multistage random sample of 1474 school children aged 5-12 years in Guyuan, China. Child nutritional status was measured by height-for-age z scores (HAZ). Linear mixed models were used to examine its association with place of residence and maternal education. Results Micro-geographic disparities in child nutritional status and the level of socioeconomic composition were found. Children living in mountain areas had poorer nutritional status, even after adjusting for demographic (plain versus mountain, β = 0.16, P = 0.033; edge versus mountain, β = 0.29, P = 0.002) and socioeconomic factors (plain versus mountain, β = 0.12, P = 0.137; edge versus mountain, β = 0.25, P = 0.009). The disparities significantly widened with increasing years of mothers’ schooling (maternal education*plain versus mountain: β = 0.06, P = 0.007; maternal education*edge versus mountain: β = 0.07, P = 0.005). Moreover, the association between maternal education and child nutrition was negative (β = -0.03, P = 0.056) in mountain areas but positive in plain areas (β = 0.02, P = 0.094) or in the edge areas (β = 0.04, P = 0.055). Conclusions Micro-geographic disparities in child nutritional status increase with increasing level of maternal education and the effect of maternal education varies by micro-geographic locations, which exacerbates child health inequity. Educating rural girls alone is not sufficient; improving unfavorable conditions in mountain areas might make such investments more effective in promoting child health. Nutrition programs targeting to the least educated groups in plain and in edge areas would be critical to their cost-effectiveness.
Tool and evaluation method for idea creation support

We have developed a new idea creation support tool in which (1) each idea is represented by a tree structure, (2) the idea is automatically evaluated on the basis of the tree structure so that the relative advantages among several alternative ideas is found, (3) the ideas are presented in a poster format, and (4) the ideas are shared by multiple users so that the ideas can be quoted and expanded upon by individual users. In this work, we explain the mechanisms of this tool, including the evaluation and poster conversion of ideas and collaborative idea creation, and briefly discuss our plan for the future.
Multivariate Non-Linear Regression with Applications: A Frequency Domain Approach

1ABSTRACTIn this paper we consider estimating the parameters of a multivariate multiple nonlinear regressionmodel with correlated errors, through the use of Finite Fourier Transforms. Consistency and asymp-totic normality of the weighted least squares estimates are established under various conditions onthe regressor variables. These conditions involve diﬁerent types of scalings, and such scaling factorsare obtained explicitly for various nonlinear regression models including an interesting model whichrequires estimating the frequencies. This is a very classical problem in signal processing and is alsoof great interest in many other areas. We illustrate our techniques on the time-series data of polarmotion (which is now widely known as "Chandlers Wobble") where one has to estimate the drift pa-rameters, the oﬁset parameters and the two periodicities associated with elliptical motion. The datawas ﬂrst analyzed by Arato, Kolmogorov and Sinai who treat it as bivariate time series data satisfyinga ﬂnite order time series model. They estimate the periodicities using the coe–cients of the models.Our analysis shows that the two dominant frequencies are 12 hours and 410 days and that the errorsexhibit some long-range dependence.
DiscoTK: Using Discourse Structure for Machine Translation Evaluation

We present novel automatic metrics for machine translation evaluation that use discourse structure and convolution kernels to compare the discourse tree of an automatic translation with that of the human reference. We experiment with five transformations and augmentations of a base discourse tree representation based on the rhetorical structure theory, and we combine the kernel scores for each of them into a single score. Finally, we add other metrics from the ASIYA MT evaluation toolkit, and we tune the weights of the combination on actual human judgments. Experiments on the WMT12 and WMT13 metrics shared task datasets show correlation with human judgments that outperforms what the best systems that participated in these years achieved, both at the segment and at the system level.
Physical Search Problems Applying Economic Search Models

This paper considers the problem of an agent searching for a resource or a tangible good in a physical environment, where at each stage of its search it observes one source where this good can be found. The cost of acquiring the resource or good at a given source is uncertain (a-priori), and the agent can observe its true value only when physically arriving at the source. Sample applications involving this type of search include agents in exploration and patrol missions (e.g., an agent seeking to find the best location to deploy sensing equipment along its path). The uniqueness of these settings is that the expense of observing the source on each step of the process derives from the last source the agent explored. We analyze three variants of the problem, differing in their objective: minimizing the total expected cost, maximizing the success probability given an initial budget, and minimizing the budget necessary to obtain a given success probability. For each variant, we first introduce and analyze the problem with a single agent, either providing a polynomial solution to the problem or proving it is NP-Complete. We also introduce an innovative fully polynomial time approximation scheme algorithm for the minimum budget variant. Finally, the results for the single agent case are generalized to multi-agent settings.
The non validity of the gaussian approximation for multi-user interference in ultra wide band impulse radio: from an inconvenience to an advantage - transactions papers

The huge potential of ultra wide band impulse radio (UWB IR) with multiple access was initially evaluated using the standard Gaussian approximation which assumed that multi user interference could be approximated as classical Gaussian noise. Later the standard Gaussian approximation has been proved to be invalid in several cases. Thus the performance of the classical UWB IR correlation receiver dramatically reduces. We show in this paper how the non Gaussianity of the multi user interference can be exploited, turning the non Gaussianity into an advantage, increasing the performance with respect to the Gaussian interference case which was supposed to be too optimistic until now.
Atrial Fibrillation and the Hypercoagulable State: From Basic Science to Clinical Practice

Atrial fibrillation (AF) is the commonest sustained cardiac rhythm disturbance in clinical practice [1]. Its presence increases mortality by two-fold [2], mostly by increasing the risk of stroke and thromboembolism. The reasons for stroke occurring in AF are multiple and complex, but many strokes related to AF represent embolism of thrombus formed within the left atrium (LA), predominantly within the left atrial appendage (LAA). The elucidation of the pathophysiological mechanisms leading to stroke and thromboembolism in AF have therefore gained much interest. Over 150 years ago, Virchow proposed a triad of abnormalities that predisposes to thrombus formation flow abnormalities, abnormalities of the vessel wall and abnormal blood constituents. The pathophysiology of thromboembolism is AF is multi-factorial but increasing evidence points to the fulfillment of Virchow's triad in this arrhythmia, leading to a prothrombotic or hypercoagulable state in AF. Flow Abnormalities
Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching

Reports on the design and test of an image processing algorithm for the localization of the optic disk (OD) in low-resolution (about 20 /spl mu//pixel) color fundus images. The design relies on the combination of two procedures: 1) a Hausdorff-based template matching technique on edge map, guided by 2) a pyramidal decomposition for large scale object tracking. The two approaches are tested against a database of 40 images of various visual quality and retinal pigmentation, as well as of normal and small pupils. An average error of 7% on OD center positioning is reached with no false detection. In addition, a confidence level is associated to the final detection that indicates the "level of difficulty" the detector has to identify the OD position and shape.
End-effector airbags to accelerate human-robot collaboration

A fundamental problem in human-robot collaboration is to ensure safety for humans being located in the workspace of the robot. Several new robots, referred to as collaborative robots, are pushing into the market. Most of these so-called co-bots have similar properties. They are small, lightweight and designed with big roundings to ensure safety in the case of a collision with a human. Equipped with torque sensors, external torque observers, tactile skins, etc., they are able to stop the robot when an emergency occurs. While developing more and more co-bots, the main focus lies on the robot itself. But to make a robot deployable, a special tool for a defined task is needed. These tools are often sharp-edged and dangerous in case of a collision with a human. In this paper we present a new safety module for robots to ensure safety for different tools in collaborative tasks. This module, filled with air pressure during the robot motion, covers mounted tools and carried workpieces. In case of a non or very slow moving robot, the safety module is able to pull back and the tool is uncovered. In our experiments we found out that we can increase the velocity up to 1 m/s while satisfying the requirements of the ISO/TS 15066 and retain the full functionality of the tool.
On the energy efficiency of cooperative communications in wireless sensor networks

Cooperative communications represent a potential candidate to combat the effects of channel fading and to increase the transmit energy efficiency in wireless sensor networks with the downside being the increased complexity. In sensor networks the power consumed in the receiving and processing circuitry can constitute a significant portion of the total consumed power. By taking into consideration such overhead, an analytical framework for studying the energy efficiency trade-off of cooperation in sensor networks is presented. This trade-off is shown to depend on several parameters such as the receive and processing power, the required quality-of-service, the power amplifier loss, and several other factors. The analytical and numerical results reveal that for small distance separation between the source and destination, direct transmission is more energy efficient than relaying. The results also reveal that equal power allocation performs as well as optimal power allocation for some scenarios. The effects of the relay location and the number of employed relays on energy efficiency are also investigated in this work. Moreover, there are experimental results conducted to verify the channel model assumed in the article.
Investigating Word Correlation at Difierent Scopes { a Latent-Concept Approach

This paper presents work in progress on clustering methods that identify semantic concepts in a document collection. These methods are based on the observation that semantically related words occur close together. We investigate the size of neighborhood which should be taken into account for this purpose: sentences or documents. We further investigate how local co-occurrence afiects the clustering quality by including word bigrams as additional terms. We apply two difierent latent-concept models, probabilistic latent semantic analysis (PLSA) and latent Dirichlet allocation (LDA), to a corpus of German news stories. The resulting soft clusterings are compared with a given a priori classiflcation of documents using an information-based distance metric. Preliminary results show that this cluster distance was smaller using (1) entire documents (compared to combinations of documents and sentences), as well as (2) combinations of unigrams and bigrams (compared to exclusive use of unigrams or bigrams).
Selective laser patterning in organic solar cells

Selective laser patterning for integrative serious connection has been industrially established in inorganic thin film solar cells based on glass substrates since a few years. In organic solar cells (OSC) the used materials significantly differ in terms of their patterning behavior. Due to their processability by wet chemical methods inverted architectures are often preferred in organic solar cells which allow the patterning by ultrashort laser pulses in substrate and superstrate configuration. Starting with an introduction of the ablation mechanisms taking place in OSC thin films, an overview of the current state-of-the-art in laser patterning of organic solar cells is presented. Besides progress in research also current achievements in industrial applications are illustrated.