nils-herrmann/clean_scirepeval huggingface dataset:
Offline handwritten signature verification using local and global features

This paper presents a new approach to address the problem of offline handwritten signature verification. In contrast to many existing systems, we are interested in making soft decision rather than a purely binary classification for the signatures under verification. To accomplish this goal, we incorporate both types of features: finer intensity-based features and global geometry-based features. Particularly, the finer features are computed for every sample point of a signature using histogram of intensities, and the geometry-based features are extracted using an adaptation of the shape context descriptor. One of the advantages of our approach is that the extracted features are very robust to noise, rotation and scaling change without heavily relying on any complicated pre-processing steps. The extracted features are used to compute the similarity score, followed by a score calibration process to estimate the corresponding confidence score (i.e., using log-likelihood-ratio). To validate our work, we submitted our system to the signature verification competition (SignComp2011) and achieved quite good results.
The Spanish version of the Work-related Acceptance and Action Questionnaire (WAAQ).

Psychological flexibility, a key construct of Acceptance and Commitment Therapy (ACT), has recently been found to be an important determinant of mental health and behavioral effectiveness in the workplace. This finding has led to designing a measure of psychological flexibility especially tailored to the workplace (the Work-related Acceptance and Action Questionnaire; WAAQ) in the hope that it may reveal even stronger associations with variables related to a work context.



First, we back-translated the WAAQ into Spanish and then administered it to 209 workers, in addition to other relevant work-related measures.



Data were very similar to those obtained with the original WAAQ version. The WAAQ showed a very good internal consistency (a = .92) and a clear one-factor structure. It also showed higher correlations with work-specific measures than a general measure of psychological inflexibility (the Acceptance and Action Questionnaire-II; AAQ-II). As hypothesized by the ACT theory, the correlation between the WAAQ and the AAQ-II was moderate but not so high as to suggest that they are assessing the same construct.



This Spanish translation of the WAAQ emerges as a reliable and valid measure of psychological flexibility in relation to the workplace.
Membership Inference Attacks Against Machine Learning Models

We quantitatively investigate how machine learning models leak information about the individual data records on which they were trained. We focus on the basic membership inference attack: given a data record and black-box access to a model, determine if the record was in the model's training dataset. To perform membership inference against a target model, we make adversarial use of machine learning and train our own inference model to recognize differences in the target model's predictions on the inputs that it trained on versus the inputs that it did not train on. We empirically evaluate our inference techniques on classification models trained by commercial "machine learning as a service" providers such as Google and Amazon. Using realistic datasets and classification tasks, including a hospital discharge dataset whose membership is sensitive from the privacy perspective, we show that these models can be vulnerable to membership inference attacks. We then investigate the factors that influence this leakage and evaluate mitigation strategies.
Depression as a risk factor for coronary artery disease: evidence, mechanisms, and treatment.

The present paper reviews the evidence that depression is a risk factor for the development and progression of coronary artery disease (CAD).



MEDLINE searches and reviews of bibliographies were used to identify relevant articles. Articles were clustered by theme: depression as a risk factor, biobehavioral mechanisms, and treatment outcome studies.



Depression confers a relative risk between 1.5 and 2.0 for the onset of CAD in healthy individuals, whereas depression in patients with existing CAD confers a relative risk between 1.5 and 2.5 for cardiac morbidity and mortality. A number of plausible biobehavioral mechanisms linking depression and CAD have been identified, including treatment adherence, lifestyle factors, traditional risk factors, alterations in autonomic nervous system (ANS) and hypothalamic pituitary adrenal (HPA) axis functioning, platelet activation, and inflammation.



There is substantial evidence for a relationship between depression and adverse clinical outcomes. However, despite the availability of effective therapies for depression, there is a paucity of data to support the efficacy of these interventions to improve clinical outcomes for depressed CAD patients. Randomized clinical trials are needed to further evaluate the value of treating depression in CAD patients to improve survival and reduce morbidity.
Steatocystoma simplex in penile foreskin: a case report

Steatocystoma simplex is an uncommon skin lesion with a histological pattern that is identical to that of steatocystoma multiplex. We are reporting this case of steatocystoma simplex for its uncommon location in the penile foreskin, and its occurrence in a Wapishana man.



A 56-year-old man of Wapishana ethnicity presented with complaints of referred penile discomfort and pain during sexual intercourse for 5 years. A physical examination revealed a mobile, compressible subcutaneous non-tender mass of 4 cm diameter located on the left-side of his penile foreskin. There were no signs of inflammation, no grip on the penile shaft, and no urethral discharge or enlargement of lymph nodes. We found no evidence of other cysts on cutaneous examination. We performed classical excision of the lesion under local anesthesia and confirmed the diagnosis of steatocystoma with the pathological report. As there were no complications, we discharged him the same day.



Steatocystoma can be considered a differential diagnosis for cystic lesions on and around the penis.
New Sliding-Mode Observer for Position Sensorless Control of Permanent-Magnet Synchronous Motor

This paper proposes a novel sliding-mode observer (SMO) to achieve the sensorless control of permanent-magnet synchronous motor (PMSM). An observer is built according to the back electromotive force (EMF) model after the back EMF equivalent signal is obtained. In this way, not only are low-pass filter and phase compensation module eliminated, but also estimation accuracy is improved. Numerical simulations and experiments with an 11-kW low-speed PMSM are carried out. The results demonstrate that the novel SMO can effectively estimate rotor position and speed and achieve good static and dynamic performance.
TEXT DEPENDENT SPEAKER RECOGNITION

— Now a days biometric person authentication is secure way to authenticate or recognize a person. Speech is one of the easiest and safest method among all biometric model. Speaker recognition can divided in to text dependent and text independent recognition. Feature extraction is the first process in any speaker recognition technique. This paper describes text dependent speaker recognition In this, Mel Frequency Cepstral Coefficient (MFCC) have been used for feature extraction. Along with this pitch and formants are also extracted. Gaussian Mixture Model (GMM) and Artificial Neural Network (ANN) are used for modelling and speaker matching process. GMM is parametric model of probability distribution of features in speaker recognition process. Compared to GMM, ANN is seen to be best for recognizing a person. It is unaffected by differing shape and style of testing speech. False Acceptance Rate (FAR) in ANN is small compared to ANN.
The Most Probable Database Problem

This paper proposes a novel inference task for probabilistic databases: the most probable database (MPD) problem. The MPD is the most probable deterministic database where a given query or constraint is true. We highlight two distinctive applications, in database repair of key and dependency constraints, and in finding most probable explanations in statistical relational learning. The MPD problem raises new theoretical questions, such as the possibility of a dichotomy theorem for MPD, classifying queries as being either PTIME or NP-hard. We show that such a dichotomy would diverge from dichotomies for other inference tasks. We then prove a dichotomy for queries that represent unary functional dependency constraints. Finally, we discuss symmetric probabilities and the opportunities for lifted inference.
Judo strategy. The competitive dynamics of Internet time.

Competition on the Internet is creating fierce battles between industry giants and small-scale start-ups. Smart start-ups can avoid those conflicts by moving quickly to uncontested ground and, when that's no longer possible, turning dominant players' strengths against them. The authors call this competitive approach judo strategy. They use the Netscape-Microsoft battles to illustrate the three main principles of judo strategy: rapid movement, flexibility, and leverage. In the early part of the browser wars, for instance, Netscape applied the principle of rapid movement by being the first company to offer a free stand-alone browser. This allowed Netscape to build market share fast and to set the market standard. Flexibility became a critical factor later in the browser wars. In December 1995, when Microsoft announced that it would "embrace and extend" competitors' Internet successes, Netscape failed to give way in the face of superior strength. Instead it squared off against Microsoft and even turned down numerous opportunities to craft deep partnerships with other companies. The result was that Netscape lost deal after deal when competing with Microsoft for common distribution channels. Netscape applied the principle of leverage by using Microsoft's strengths against it. Taking advantage of Microsoft's determination to convert the world to Windows or Windows NT, Netscape made its software compatible with existing UNIX systems. While it is true that these principles can't replace basic execution, say the authors, without speed, flexibility, and leverage, very few companies can compete successfully on Internet time.
Creating value in networks : A value network mapping method for assessing the current and potential value networks in cross-sector collaboration

How to manage value creation and how to maximize the potential of collaborations are challenging issues in the management of cross-sector collaborations. One strategic tool for addressing these areas of concern is value network mapping; this serves as the starting point for value network analysis, which is used to maximize innovations by forging stronger value creation links with strategic partners. The objective of this study was to design and implement a method for value network mapping that would increase our understanding of how new value can be created in cross-sector collaborations. The proposed mapping method also permits the assessment of current and potential value networks; e.g., what value is exchanged in the current collaborative state and what new value can be created through the proper management of a value network? Using the case study of a collaboration among the public, private, and non-profit sectors for elderly care, this paper describes, step by step, how the proposed value network mapping method can be applied in practice to help managers and experts understand how to develop complex value network maps, how new values can be created, and how to maximize the potential of a collaboration.
Analysis and Optimization of Switched-Capacitor DC–DC Converters

Analysis methods are developed that fully determine a switched-capacitor (SC) dc-dc converter's steady-state performance through evaluation of its output impedance. This analysis method has been verified through simulation and experimentation. The simple formulation developed permits optimization of the capacitor sizes to meet a constraint such as a total capacitance or total energy storage limit, and also permits optimization of the switch sizes subject to constraints on total switch conductances or total switch volt-ampere (V-A) products. These optimizations then permit comparison among several switched-capacitor topologies, and comparisons of SC converters with conventional magnetic-based dc-dc converter circuits, in the context of various application settings. Significantly, the performance (based on conduction loss) of a ladder-type converter is found to be superior to that of a conventional magnetic-based converter for medium to high conversion ratios.
How to Construct Deep Recurrent Neural Networks

In this paper, we explore different ways to extend a recurrent neural network (RNN) to a deep RNN. We start by arguing that the concept of depth in an RNN is not as clear as it is in feedforward neural networks. By carefully analyzing and understanding the architecture of an RNN, however, we find three points of an RNN which may be made deeper; (1) input-to-hidden function, (2) hidden-tohidden transition and (3) hidden-to-output function. Based on this observation, we propose two novel architectures of a deep RNN which are orthogonal to an earlier attempt of stacking multiple recurrent layers to build a deep RNN (Schmidhuber, 1992; El Hihi and Bengio, 1996). We provide an alternative interpretation of these deep RNNs using a novel framework based on neural operators. The proposed deep RNNs are empirically evaluated on the tasks of polyphonic music prediction and language modeling. The experimental result supports our claim that the proposed deep RNNs benefit from the depth and outperform the conventional, shallow RNNs.
Feature Selection for Clustering - A Filter Solution

Processing applications with a large number of dimensions has been a challenge to the KDD community. Feature selection, an effective dimensionality reduction technique, is an essential pre-processing method to remove noisy features. In the literature there are only a few methods proposed for feature selection for clustering. And, almost all of those methods are ‘wrapper’ techniques that require a clustering algorithm to evaluate the candidate feature subsets. The wrapper approach is largely unsuitable in real-world applications due to its heavy reliance on clustering algorithms that require parameters such as number of clusters, and due to lack of suitable clustering criteria to evaluate clustering in different subspaces. In this paper we propose a ‘filter’ method that is independent of any clustering algorithm. The proposed method is based on the observation that data with clusters has very different point-to-point distance histogram than that of data without clusters. Using this we propose an entropy measure that is low if data has distinct clusters and high otherwise. The entropy measure is suitable for selecting the most important subset of features because it is invariant with number of dimensions, and is affected only by the quality of clustering. Extensive performance evaluation over synthetic, benchmark, and real datasets shows its effectiveness.
Parasitic-Aware Common-Centroid FinFET Placement and Routing for Current-Ratio Matching

The FinFET technology is regarded as a better alternative for modern high-performance and low-power integrated-circuit design due to more effective channel control and lower power consumption. However, the gate-misalignment problem resulting from process variation and the parasitic resistance resulting from interconnecting wires based on the FinFET technology becomes even more severe compared with the conventional planar CMOS technology. Such gate misalignment and unwanted parasitic resistance may increase the threshold voltage and decrease the drain current of transistors. When applying the FinFET technology to analog circuit design, the variation of drain currents can destroy current-ratio matching among transistors and degrade circuit performance. In this article, we present the first FinFET placement and routing algorithms for layout generation of a common-centroid FinFET array to precisely match the current ratios among transistors. Experimental results show that the proposed matching-driven FinFET placement and routing algorithms can obtain the best current-ratio matching compared with the state-of-the-art common-centroid placer.
Broadband Planar Fully Integrated 8 $\, \times \,$8 Butler Matrix Using Coupled-Line Directional Couplers

An innovative approach that allows for realization of broadband planar fully integrated 8 × 8 Butler matrices is presented. Coupled-line directional couplers have been utilized, which enable broad operational band. A novel arrangement of the network has been proposed that allows the creation of an entirely planar design having two metallization layers and no interconnections between these layers. Four selected crossovers have been realized as a tandem connection of two 3-dB/90° coupled-line directional couplers, which, together with reference lines having appropriate electrical lengths, perform simultaneously crossovers of signal lines, and all needed broadband constant value phase shifters. Moreover, two of the needed 3-dB/90° directional couplers have been designed as tandem connections of two 8.34-dB directional couplers, acting as 3-dB/90° directional couplers having crossed outputs. With such a modification, a fully planar design with no inter-layer connections is possible. The proposed network arrangement has been experimentally tested with the design of an 8 × 8 Butler matrix operating at the center frequency of 3 GHz. The obtained measurement results fully confirm the validity of the proposed approach.
A Case Study on Korean Wave: Focused on K-POP Concert by Korean Idol Group in Paris, June 2011

The study dealt with Korean Wave focusing on K-POP and analyzed its success factors, the changes in Korean Wave and the future directions for development. Also the study has compared the results of the idol groups’ performance, held by SM Entertainment in June 2011 in Paris, and the perspective of Korean and French media. Key reasons were examined to analyze what led K-POP to play a crucial part in spreading the Korean Wave: The expansion of the age of its takers ranging from teens to females in their 20s; the fusion of a variety of cultural elements including oriental dance and occidental pop; the systematic system of idol training; marketing activities based on social media, etc. For the expansion of Korean Wave including K-POP and its successful positioning in the world market, there are several suggestions to make which are inventing the differentiated contents and highly appealing stories, approaching the local customers while considering local features, operating co-marketing with other cultural products.
DA-GAN: Instance-Level Image Translation by Deep Attention Generative Adversarial Networks

Unsupervised image translation, which aims in translating two independent sets of images, is challenging in discovering the correct correspondences without paired data. Existing works build upon Generative Adversarial Networks (GANs) such that the distribution of the translated images are indistinguishable from the distribution of the target set. However, such set-level constraints cannot learn the instance-level correspondences (e.g. aligned semantic parts in object transfiguration task). This limitation often results in false positives (e.g. geometric or semantic artifacts), and further leads to mode collapse problem. To address the above issues, we propose a novel framework for instance-level image translation by Deep Attention GAN (DA-GAN). Such a design enables DA-GAN to decompose the task of translating samples from two sets into translating instances in a highly-structured latent space. Specifically, we jointly learn a deep attention encoder, and the instance-level correspondences could be consequently discovered through attending on the learned instances. Therefore, the constraints could be exploited on both set-level and instance-level. Comparisons against several state-of-the-arts demonstrate the superiority of our approach, and the broad application capability, e.g, pose morphing, data augmentation, etc., pushes the margin of domain translation
Personalizing PageRank for Word Sense Disambiguation

In this paper we propose a new graph-based method that uses the knowledge in a LKB (based on WordNet) in order to perform unsupervised Word Sense Disambiguation. Our algorithm uses the full graph of the LKB efficiently, performing better than previous approaches in English all-words datasets. We also show that the algorithm can be easily ported to other languages with good results, with the only requirement of having a wordnet. In addition, we make an analysis of the performance of the algorithm, showing that it is efficient and that it could be tuned to be faster.
The TNF and TNF Receptor Superfamilies Integrating Mammalian Biology

The receptors and ligands in this superfamily have unique structural attributes that couple them directly to signaling pathways for cell proliferation, survival, and differentiation. Thus, they have assumed prominent roles in the generation of tissues and transient microen-capabilities are crucial in coordinating the proliferation and protective functions of pathogen-reactive cells. Here, we review the organization of the TNF/TNFR SF and how these proteins have been adapted for pro-Bethesda, Maryland 20892 cesses as seemingly disparate as host defense and or-ganogenesis. In interpreting this large and highly active area of research, we have focused on common themes Introduction that unite the actions of these genes in different tissues. We also discuss the evolutionary success of this super-Three decades ago, lymphotoxin (LT) and tumor necro-sis factor (TNF) were identified as products of lympho-family—success that we infer from its expansion across the mammalian genome and from its many indispens-cytes and macrophages that caused the lysis of certain types of cells, especially tumor cells (Granger et al., able roles in mammalian biology.The normal functions of TNF/TNFR SFPs, as well as ally, it became clear that they were members of a gene certain diseases involving them, depend on the obliga-superfamily. Not surprisingly, the receptors for these tory 3-fold symmetry that defines the essential signaling proteins also constitute a TNF receptor (TNFR)-related stoichiometry and structure . The ligands are gene superfamily. Large-scale sequencing of " ex-type 2 proteins that can have both membrane-embed-pressed sequence tags " (ESTs) identified many related ded " pro " as well as cleaved, soluble " mature " forms proteins, collectively referred to here as TNF-and TNFR-(for review, see Idriss and Naismith, 2000). Both forms related superfamily proteins (TNF/TNFR SFPs; reviewed are active as self-assembling noncovalent trimers, whose individual chains fold as compact " jellyroll " ␤ sandwiches and interact at hydrophobic interfaces (Fesik, UCL.ac.uk/users/hester/tnfinfo.html). The familiar as 2000) . The 25%–30% amino acid similarity well as standardized names of these proteins are listed between TNF-like ligands is largely confined to internal in Table 1, together with their gene locations, pheno-aromatic residues responsible for trimer assembly. The types caused by mutations in these genes, and identified external surfaces of ligand trimers show little sequence functions. similarity, which accounts for receptor selectivity (Figure The discovery that cachectin, a protein known to 2). The ligand shape is that of an inverted bell that is cause fever and wasting, was identical to TNF provided …