nils-herrmann/clean_scirepeval huggingface dataset:
Computerized classification of intraductal breast lesions using histopathological images

In the diagnosis of preinvasive breast cancer, some of the intraductal proliferations pose a special challenge. The continuum of intraductal breast lesions includes the usual ductal hyperplasia (UDH), atypical ductal hyperplasia (ADH), and ductal carcinoma in situ (DCIS). The current standard of care is to perform percutaneous needle biopsies for diagnosis of palpable and image-detected breast abnormalities. UDH is considered benign and patients diagnosed UDH undergo routine follow-up, whereas ADH and DCIS are considered actionable and patients diagnosed with these two subtypes get additional surgical procedures. About 250 000 new cases of intraductal breast lesions are diagnosed every year. A conservative estimate would suggest that at least 50% of these patients are needlessly undergoing unnecessary surgeries. Thus, improvement in the diagnostic reproducibility and accuracy is critically important for effective clinical management of these patients. In this study, a prototype system for automatically classifying breast microscopic tissues to distinguish between UDH and actionable subtypes (ADH and DCIS) is introduced. This system automatically evaluates digitized slides of tissues for certain cytological criteria and classifies the tissues based on the quantitative features derived from the images. The system is trained using a total of 327 regions of interest (ROIs) collected across 62 patient cases and tested with a sequestered set of 149 ROIs collected across 33 patient cases. An overall accuracy of 87.9% is achieved on the entire test data. The test accuracy of 84.6% is obtained with borderline cases (26 of the 33 test cases) only, when compared against the diagnostic accuracies of nine pathologists on the same set (81.2% average), indicates that the system is highly competitive with the expert pathologists as a stand-alone diagnostic tool and has a great potential in improving diagnostic accuracy and reproducibility when used as a “second reader” in conjunction with the pathologists.
Unified Model for Contrast Enhancement and Denoising

In this paper, we attempt a challenging task to unify two important complementary operations, i.e. contrast enhancement and denoising, that is required in most image processing applications. The proposed method is implemented using practical analog circuit configurations that can lead to near real-time processing capabilities useful to be integrated with vision sensors. Metrics used for performance includes estimation of Residual Noise Level (RNL), Structural Similarity Index Measure (SSIM), Output-to-Input Contrast Ratio (CRo_i), and its combined score (SCD). The class of contrast stretching methods has resulted in higher noise levels (RNL ≥ 7) along with increased contrast measures (CRo-i ≥ eight times than that of the input image) and SSIM ≤ 0.52. Denoising methods generates images with lesser noise levels (RNL ≤ 0.2308), poor contrast enhancements (CRo-i ≤ 1.31) and with best structural similarity (SSIM ≥ 0.85). In contrast, the proposed model offers best contrast stretching (CRo-i = 5.83), least noise (RNL = 0.02), a descent structural similarity (SSIM = 0.6453) and the highest combined score (SCD = 169).
Validation of the five-factor model of personality across instruments and observers.

Two data sources--self-reports and peer ratings--and two instruments--adjective factors and questionnaire scales--were used to assess the five-factor model of personality. As in a previous study of self-reports (McCrae & Costa, 1985b), adjective factors of neuroticism, extraversion, openness to experience, agreeableness-antagonism, and conscientiousness-undirectedness were identified in an analysis of 738 peer ratings of 275 adult subjects. Intraclass correlations among raters, ranging from .30 to .65, and correlations between mean peer ratings and self-reports, from .25 to .62, showed substantial cross-observer agreement on all five adjective factors. Similar results were seen in analyses of scales from the NEO Personality Inventory. Items from the adjective factors were used as guides in a discussion of the nature of the five factors. These data reinforce recent appeals for the adoption of the five-factor model in personality research and assessment.
A Full English Sentence Database for Off-line Handwriting Recognition

In this paper we present a new database for off-line handwriting recognition, together with a few preprocessing and text segmentation procedures. The database is based on the Lancaster-Oslo/Bergen(LOB) corpus. This corpus is a collection of texts that were used to generate forms, which subsequently were filled out by persons with their handwriting. Up to now (December 1998) the database includes 556 forms produced by approximately 250 different writers. The database consists of full English sentences. It can serve as a basis for a variety of handwriting recognition tasks. The main focus, however, is on recognition techniques that use linguistic knowledge beyond the lexicon level. This knowledge can be automatically derived from the corpus or it can be supplied from external sources.
The Interplay of Institutional Logics in it Public?Private Partnerships

Public-private partnerships (PPPs) offer a popular means by which the public sector can obtain infor-mation technology (IT) innovations and management know-how from private firms. However, these IT PPPs are extremely difficult to realize, especially considering the divergent interests of public- and private-side stake-holders. Our case study of an IT PPP reveals public- and private-side differences that initially impeded the establishment of a partnership; using institutional logics theory as meta-theoretical lens, we propose a model that explains how public and private parties managed to negotiate their mode of collaboration by balancing their competing institutional norms and practices which ultimately resulted in the convergence of the two divergent logics. Our paper contributes to theory and practice by (1) elucidating the theoretical foundations and role of institutional logics for IT project management that we found dominated by public and private norms and practices, (2) explaining why collaboration in IT PPPs is so diffi-cult, and (3) how eventually an IT PPP can be estab-lished. We discuss theoretical and practical implica-tions in the paper.
Understanding Blog author's emotions with hierarchical Bayesian models

The research of inferring emotions in natural language is confronted with two major challenges: the lack of basic knowledge in emotion expressions and the co-occurrence of separate emotions through all language unites. In this paper, we propose a Bayesian inference method to explore the basic knowledge with respect to emotion expression in different semantic dimensions, and to infer the co-occurrence of multiple emotion labels through words to the document. Specifically, we incorporate emotions and semantic dimensions as the latent factors in determining the distribution of observed words in a corpus of Blog articles. For each Blog article, we further generalize emotions from words to the document by incorporating a document specific hierarchy in the emotion distributions. The basic knowledge and co-occurred emotion labels in words and documents are obtained through a Gibbs sampling inference. Our experiment is performed on the well-developed Chinese emotion corpus, i.e. Ren-CECps, which indicates both higher accuracy and better robustness in our word and document emotion predictions compared with those generated by the state-of-the-art emotion prediction algorithms, and demonstrates a distribution of emotions in different word semantic dimensions.
Certificates of virginity and reconstruction of the hymen.

Virginity in women has traditionally been associated with the integrity of the hymen, the incomplete membrane occluding the lower end of the vagina. The hymen is often ruptured during the first coitus, which may cause bleeding of varying intensity. In certain communities, the bed-sheet, now soiled with blood, is shown as proof that the first sexual intercourse has taken place and that the bride was indeed a virgin up to that point. Thus, the sullied sheet constitutes evidence that the ‘honour’ of the woman and that of her family remain intact. Literature data concerning the frequency of bleeding at defloration are amazingly scarce. Olga Loeber conducted a retrospective survey among women of diverse ethnic origin and with different cultural and religious background aborted at one centre in The Netherlands. Somewhat less than half of these women reported that they had not bled during their first coitus! The Jewish, Christian and Muslim faiths all attach considerable importance to premarital virginity, particularly that of women. Yet, the social valorization of virginity dates back to a much earlier time than the imposition of chastity upon unmarried women in Muslim communities. Neither the Koran nor Hadiths state that virginity is a precondition to marriage. Patriarchal societies aim to control the sexuality of women in order to regulate lines of descent and transfer. Islam has only translated a social into a religious norm. It is worth remembering that until the 1960s, moral and behavioural norms kept even European atheists from engaging in premarital sex. These constraints have only been gradually lifted in the last 50 years as a result of the liberalization of sexuality and the improved social status of women.
Color texture classification by integrative Co-occurrence matrices

Integrative Co-occurrence matrices are introduced as novel features for color texture classi"cation. The extended Co-occurrence notation allows the comparison between integrative and parallel color texture concepts. The information pro"t of the new matrices is shown quantitatively using the Kolmogorov distance and by extensive classi"cation experiments on two datasets. Applying them to the RGB and the LUV color space the combined color and intensity textures are studied and the existence of intensity independent pure color patterns is demonstrated. The results are compared with two baselines: gray-scale texture analysis and color histogram analysis. The novel features improve the classi"cation results up to 20% and 32% for the "rst and second baseline, respectively. ? 2003 Pattern Recognition Society.
Time series contextual anomaly detection for detecting market manipulation in stock market

Anomaly detection in time series is one of the fundamental issues in data mining that addresses various problems in different domains such as intrusion detection in computer networks, irregularity detection in healthcare sensory data and fraud detection in insurance or securities. Although, there has been extensive work on anomaly detection, majority of the techniques look for individual objects that are different from normal objects but do not take the temporal aspect of data into consideration. We are particularly interested in contextual outlier detection methods for time series that are applicable to fraud detection in securities. This has significant impacts on national and international securities markets. In this paper, we propose a prediction-based Contextual Anomaly Detection (CAD) method for complex time series that are not described through deterministic models. The proposed method improves the recall from 7% to 33% compared to kNN and Random Walk without compromising the precision.
Vection and simulator sickness.

Simulator sickness has been identified as a form of motion sickness in which users of simulators exhibit symptoms characteristic of true motion sickness. In a fixed-base simulator, visual and vestibular sources of information specifying dynamic orientation are in conflict to the extent that the optical flow pattern viewed by the pilot creates a compelling illusion of self-motion, which is not corroborated by the inertial forces transmitted through the vestibular sense organs. Visually induced illusory self-motion is known as vection, and a strict interpretation of sensory conflict theory of motion sickness suggests that vection in a fixed-base simulator would be a necessary precondition for simulator sickness. Direct confirmation of this relation is reported in this article.
Knowledge Management Issues in Malaysian Organizations : the Perceptions of Leaders

Knowledge management is a relatively young topic to other older strategic tools, and it has been attracting the attention of researchers and academics over the past decade or so. In this regard globalization is already in many countries including Malaysia like many other developing countries, Malaysia is also striving to fulfil its vision of becoming a developed nation. It is a fast growing country in terms of both economy and technology. However, obstacles for successful knowledge management initiatives will be there for this country, as well. Thus, exploration of the potential barriers is essential before any Malaysian company embarks on a knowledge management journey. This research has shed light to some of the important issues and challenges with reference to knowledge management in Malaysia by providing a more thorough and clear picture of the knowledge management status amongst Malaysian organizations. This could in turn help top managers and decision makers to develop a more insightful agenda to ensure success for their respective knowledge management initiatives.
D Targets for Evaluating Fingerprint Readers

Standard calibration targets are typically used for calibrating the imaging pathway of fingerprint readers. However, there is no standard method for evaluating fingerprint readers in the operational setting where variations in finger placement by the user are encountered. The goal of this research is to design 3D targets for repeatable operational evaluation of fingerprint readers. 2D calibration patterns with known characteristics (e.g. sinusoidal gratings of pre-specified orientation and frequency, synthetic fingerprints with known singular points and minutiae) are projected onto a generic 3D finger surface to create electronic 3D targets. A state-of-the-art 3D printer (Stratasys Objet350 Connex) is used to fabricate the 3D targets with material similar in hardness and elasticity to the human finger skin. Our experimental results show that the (i) fabricated 3D targets can be imaged using three different (500/1000 ppi) commercial optical fingerprint readers, (ii) salient features in the 2D calibration patterns are preserved during the synthesis and fabrication of 3D targets, and (iii) intra-class variability between multiple impressions of the 3D targets captured using the optical fingerprint readers does not degrade the recognition accuracy. We also conduct experiments to demonstrate that the fabricated 3D targets can be used for operational evaluation of fingerprint readers. Keywords—3D targets, fingerprint reader evaluation, 2D calibration patterns, 3D printing, 2D pattern to 3D surface projection.
Violence during pregnancy in Jordan: its prevalence and associated risk and protective factors.

This study estimates the lifetime prevalence of physical violence during pregnancy and examines risk and protective factors among women (N = 390) attending reproductive health clinics in Jordan. Approximately 15% reported physical violence during pregnancy. The husband was the sole perpetrator in 83% of the cases. A high frequency of quarreling, the husband's use of alcohol, attitudes supportive of a woman's duty to obey her husband, infrequent communication between the respondent and her family, and exposure to violence as a child increased the risk of violence. Consanguinity (marriage to a blood relative) and higher education levels were protective against violence during pregnancy.
An Efficient Algorithm for Fractal Analysis of Textures

In this paper we propose a new and efficient texture feature extraction method: the Segmentation-based Fractal Texture Analysis, or SFTA. The extraction algorithm consists in decomposing the input image into a set of binary images from which the fractal dimensions of the resulting regions are computed in order to describe segmented texture patterns. The decomposition of the input image is achieved by the Two-Threshold Binary Decomposition (TTBD) algorithm, which we also propose in this work. We evaluated SFTA for the tasks of content-based image retrieval (CBIR) and image classification, comparing its performance to that of other widely employed feature extraction methods such as Haralick and Gabor filter banks. SFTA achieved higher precision and accuracy for CBIR and image classification. Additionally, SFTA was at least 3.7 times faster than Gabor and 1.6 times faster than Haralick with respect to feature extraction time.
Boosting Optical Character Recognition: A Super-Resolution Approach

Text image super-resolution is a challenging yet open research problem in the computer vision community. In particular, low-resolution images hamper the performance of typical optical character recognition (OCR) systems. In this article, we summarize our entry to the ICDAR2015 Competition on Text Image Super-Resolution. Experiments are based on the provided ICDAR2015 TextSR dataset  and the released Tesseract-OCR 3.02 system . We report that our winning entry of text image super-resolution framework has largely improved the OCR performance with low-resolution images used as input, reaching an OCR accuracy score of 77.19%, which is comparable with that of using the original high-resolution images (78.80%).
A single neuron PID control for twin rotor MIMO system

This paper presents an intelligent control scheme which utilizes a single neuron PID controller to an experimental propeller setup called the twin rotor multi-input multi-output system (TRMS). The control objective is to make the TRMS move quickly and accurately to the desired attitudes. The pitch angle and the azimuth angle in the conditions of decoupled and cross-coupled between vertical and horizontal axes are considered. It is difficult to design a suitable controller because of the influence between two axes and nonlinear movement. For easy demonstrate the movement on the vertical plane and horizontal plane separately, the TRMS is decoupled first by the main rotor and tail rotor. After successful simulations in decoupled condition, the more difficult simulations of cross-coupled condition are performed. Simulation results show that the new approach can improve the tracking performance.
Managing Technical Debt in Enterprise Software Packages

We develop an evolutionary model and theory of software technical debt accumulation to facilitate a rigorous and balanced analysis of its benefits and costs in the context of a large commercial enterprise software package. Our theory focuses on the optimization problem involved in managing technical debt, and illustrates the different tradeoff patterns between software quality and customer satisfaction under early and late adopter scenarios at different lifecycle stages of the software package. We empirically verify our theory utilizing a ten year longitudinal data set drawn from 69 customer installations of the software package. We then utilize the empirical results to develop actionable policies for managing technical debt in enterprise software product adoption.
A Novel Wideband Microstrip Line to Ridge Gap Waveguide Transition Using Defected Ground Slot

In this letter design of a novel, wideband and low loss microstrip line transition to ridge gap waveguide is described. The transition is made up of two sections. The first section is a microstrip line that feeds a slot on the ground plane. The microstrip line is placed inside a metal box. The second part is the slot to ridge gap waveguide matching section. The proposed design has a broadband coupling to ridge gap waveguide and covers the whole stop-band of the periodic gap structure. The design optimization is performed for the microstrip line, slot size and ridge gap waveguide matching ridges. A prototype in Ku-band is manufactured and measured that shows a return loss less than 14 dB and a back-to-back insertion loss smaller than 0.5 dB for the given bandwidth. The microstrip transition enables integration of monolithic microwave integrated circuits (MMICs) in ridge gap waveguide technology.
CHAPTER 12 WORKFLOW ENGINE FOR CLOUDS

A workflow models a process as consisting of a series of steps that simplifies the complexity of execution and management of applications. Scientific workflows in domains such as high-energy physics and life sciences utilize distributed resources in order to access, manage, and process a large amount of data from a higher level. Processing and managing such large amounts of data require the use of a distributed collection of computation and storage facilities. These resources are often limited in supply and are shared among many competing users. The recent progress in virtualization technologies and the rapid growth of cloud computing services have opened a new paradigm in distributed computing for utilizing existing (and often cheaper) resource pools for ondemand and scalable scientific computing.  Management Systems (WfMS) need to adapt to this new paradigm in order to leverage the benefits of cloud services. Cloud services vary in the levels of abstraction and hence the type of service they present to application users. Infrastructure virtualization enables providers such as Amazon to offer virtual hardware for use in computeand dataintensive workflow applications. Platform-as-a-Service (PaaS) clouds expose a higher-level development and runtime environment for building and deploying workflow applications on cloud infrastructures. Such services may also expose domain-specific concepts for rapid-application development. Further up in the cloud stack are Software-as-a-Service providers who offer end users with
Auditing and Assessment of Data Traffic Flows in an IoT Architecture

Recent advances in the development of the Internet of Things and ICT have completely changed the way citizens interact with Smart City environments increasing the demand of more services and infrastructures in many different contexts. Furthermore, citizens require to be active users in a flexible smart living lab, with the possibility to access Smart City data, analyze them, perform actions and receive notifications based on automated decision-making processes. Critical problems could arise if the continuity of data flows and communication among connected IoT devices and data-driven applications is interrupted or lost, due to some devices or system malfunction or unexpected behavior. The proposed solution is a set of instruments, aimed at real-time collecting and storing IoT and Smart City data (data shadow), as well as auditing data traffic flows in an IoT Smart City Architecture, with the purpose of quantitatively monitoring the status and detecting potential anomalies and malfunctions at level of single IoT device and/or service. These instruments are the DevDash and AMMA tools, designed and realized within the Snap4City framework. Specific use cases have been provided to highlight the capabilities of these instruments in terms of data indexing, monitoring and analysis.