nils-herrmann/clean_scirepeval huggingface dataset:
Porcelain laminate veneers. A retrospective evaluation after 1 to 10 years of service: Part II--Clinical results.

The objective of this study was to evaluate the clinical quality of 191 porcelain laminate veneers and to explore the gingival response in a long-term survey.



The clinical examination was made by two calibrated examiners following modified California Dental Association/Ryge criteria. In addition, margin index, papillary bleeding index, sulcus probing depth, and increase in gingival recession were recorded. Two age groups were formed to evaluate the influence of wearing time upon the clinical results. The results were statistically evaluated using the Kaplan-Meier survival estimation method, Chi-squared test, and Kruskal-Wallis test.



A failure rate of 4% was found. Six of the total of seven failures were seen when veneers were partially bonded to dentin. Marginal integrity was acceptable in 99% and was rated as excellent in 63%. Superficial marginal discoloration was present in 17%. Slight marginal recession was detected in 31%, and bleeding on probing was found in 25%.



Porcelain laminate veneers offer a predictable and successful treatment modality that preserves a maximum of sound tooth structure. An increased risk of failure is present only when veneers are partially bonded to dentin. The estimated survival probability over a period of 10 years is 91%.
Suicidal strangulation by plastic lock tie.

A case of self-strangulation with a rare kind of ligature material is reported and discussed. The merit of the case lies in the 'self-retaining' nature of the ligature material deployed. The case subject was a 50 year old man found dead in an open field with a unique ligature material of 'plastic lock tie' in-situ at neck. Forensic autopsy revealed ligature mark above the level of thyroid cartilage, evidence of bleeding through mouth and nostrils along with generalized features of congestion. Toxicological analysis of blood and viscera detected organophosphorus poison in stomach contents. Cause of death was opined as mechanical asphyxia due to compression of neck by self-strangulation. The importance of a scrupulous forensic autopsy supplemented by ancillary investigations and circumstantial evidences are highlighted. The relevance of the visit of autopsy surgeon to the scene of occurrence is emphasized.
Advanced Modeling Techniques for Computer Graphics

In the past thirty years, modeling techniques in computer graphics have evolved significantly as the field has matured and attempted to portray the complexities of nature. Polygonal models, patches, points, and lines are insufficient to represent the complexities of natural objects and intricate man-made objects in a manageable and controllable fashion. Higher-level modeling techniques have been developed to provide an abstraction of the model, encode classes of objects, and allow high-level control and specification of the model. The goal of these advanced modeling techniques is to provide a concise, efficient, flexible, and controllable mechanism for specifying and animating models of complex objects and natural phenomena. Most of these advanced modeling techniques can be considered procedural modeling techniques: code segments or algorithms are used to abstract and encode the details of the model instead of explicitly storing vast numbers of low-level primitives. The use of algorithms unburdens the modeler/animator of low-level control, provides great flexibility, and allows amplification of his efforts through parametric control: a few parameters to the model yield large amounts of geometric details (Smith [1984] called this “database amplification”). This survey examines several types of procedural techniques, including fractals, grammar-based models, volumetric procedural models, implicit surfaces, and particle systems.
Active ESD protection circuit design against charged-device-model ESD event in CMOS integrated circuits

CDM ESD event has become the main ESD reliability concern for integrated-circuits products using nanoscale CMOS technology. A novel CDM ESD protection design, using self-biased current trigger (SBCT) and source pumping, has been proposed and successfully verified in 0.13-lm CMOS technology to achieve 1-kV CDM ESD robustness.
Supporting Process Model Validation through Natural Language Generation

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.
A comprehensive overview of methodologies and performance evaluation frameworks in 3D mesh segmentation

3D mesh segmentation has become a crucial part of many applications in 3D shape analysis. In this paper, a comprehensive survey on 3D mesh segmentation methods is presented. Analysis of the existing methodologies is addressed taking into account a new categorization along with the performance evaluation frameworks which aim to support meaningful benchmarks not only qualitatively but also in a quantitative manner. This survey aims to capture the essence of current trends in 3D mesh segmentation.
Efficient bayesian hierarchical user modeling for recommendation system

A content-based personalized recommendation system learns user specific profiles from user feedback so that it can deliver information tailored to each individual user's interest. A system serving millions of users can learn a better user profile for a new user, or a user with little feedback, by borrowing information from other users through the use of a Bayesian hierarchical model. Learning the model parameters to optimize the joint data likelihood from millions of users is very computationally expensive. The commonly used EM algorithm converges very slowly due to the sparseness of the data in IR applications. This paper proposes a new fast learning technique to learn a large number of individual user profiles. The efficacy and efficiency of the proposed algorithm are justified by theory and demonstrated on actual user data from Netflix and MovieLens.
The IIT Bombay English-Hindi Parallel Corpus

We present the IIT Bombay English-Hindi Parallel Corpus. The corpus is a compilation of parallel corpora previously available in the public domain as well as new parallel corpora we collected. The corpus contains 1.49 million parallel segments, of which 694k segments were not previously available in the public domain. The corpus has been pre-processed for machine translation, and we report baseline phrase-based SMT and NMT translation results on this corpus. This corpus has been used in two editions of shared tasks at the Workshop on Asian Language Translation (2016 and 2017). The corpus is freely available for non-commercial research. To the best of our knowledge, this is the largest publicly available English-Hindi parallel corpus.
Paving the Way for NFV: Simplifying Middlebox Modifications Using StateAlyzr

Important Network Functions Virtualization (NFV) scenarios such as ensuring middlebox fault tolerance or elasticity require redistribution of internal middlebox state. While many useful frameworks exist today for migrating/cloning internal state, they require modications to middlebox code to identify needed state. is process is tedious and manual, hindering the adoption of such frameworks. We present a framework-independent system, StateAlyzr, that embodies novel algorithms adapted from program analysis to provably and automatically identify all state that must be migrated/cloned to ensure consistent middlebox output in the face of redistribution. We nd that StateAlyzr reducesman-hours required for code modication by nearly 20 . We apply StateAlyzr to four open source middleboxes and nd its algorithms to be highly precise. We nd that a large amount of, but not all, live state matters toward packet processing in these middleboxes. StateAlyzr’s algorithms can reduce the amount of state that needs redistribution by 6008000 compared to naive schemes.
Mining logs files for data-driven system management

With advancement in science and technology, computing systems are becoming increasingly more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming increasingly more difficult to monitor, manage and maintain. Traditional approaches to system management have been largely based on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. This has been well known and experienced as a cumber-some, labor intensive, and error prone process. In addition, this process is difficult to keep up with the rapidly changing environments. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing systems.A popular approach to system management is based on analyzing system log files. However, some new aspects of the log files have been less emphasized in existing methods from data mining and machine learning community. The various formats and relatively short text messages of log files, and temporal characteristics in data representation pose new challenges. In this paper, we will describe our research efforts on mining system log files for automatic management. In particular, we apply text mining techniques to categorize messages in log files into common situations, improve categorization accuracy by considering the temporal characteristics of log messages, and utilize visualization tools to evaluate and validate the interesting temporal patterns for system management.
A Prestressed Soft Gripper: Design, Modeling, Fabrication, and Tests for Food Handling

This study presented a prestressed soft gripper fabricated with 3-D printing technology. The gripper can realize a large contact area while grasping and simultaneously generate large initial opening without deflating the soft actuators. The soft actuator was 3-D printed as two separate parts: the soft chambers with a rigid connector and a cover to seal the chambers. The chamber part was stretched longitudinally and sealed by gluing the cover onto it. The actuator was then released, and an initial curl occurred due to the remaining prestress. Finite element (FE) simulations were performed to validate this concept and the designed structure. Actuator fabrication and experimental tests were presented, and agreements between the FE simulations and test results were achieved. A gripper consisting of four prestressed actuators was constructed and experimentally tested by picking-and-placing food materials in different weights and different sized containers. To adapt to objects of different sizes and shapes, the gripper base was designed to have two configurations and two openings. The results showed that the prestressed gripper could stably handle various types of food and still remain compact with a simple supporting system.
Substrate Integrated Folded Waveguide Filter with Out-of-Band Rejection Controlled by Resonant-Mode Suppression

This letter presents a new filter, based on substrate integrated folded waveguide (SIFW) technology, which exhibits compact size and good out-of-band rejection. The filter is based on a SIFW cavity, which guarantees size reduction, and the out-of-band rejection is controlled by the suppression and tuning of the high-order cavity modes. A detailed investigation of the cavity mode spectrum is presented, to illustrate the operation principle and the design of the filter. The interesting feature of this filter is the possibility to design the pass band and the return band by simply tuning the mode spectrum of the cavity, which is practically unaffected by the connection to the excitation ports. The fabrication and testing of a prototype operating at 4.5 GHz validate the proposed filter topology.
Automatic personality assessment: A systematic review

Personality Assessment is an emerging research area. In recent years, the interest of the scientific community towards personality assessment has grown incredibly. Personality is a psychological model that can be used to explain the wide variety of human behaviors with the help of individual characteristics. The applications of personality assessment range from behavior analysis to disease diagnosis, counseling, employee recruitment, social network analysis, security systems, mood prediction, and many others. Automatic personality assessment consists of the automatic classification of users' personality traits from the data such as video, speech and text. Despite growing number of works in personality assessment, it is still very difficult to say what the current state-of-the-art is. The objective of this survey paper is to discuss various approaches used for personality assessment and to present current state-of-art related to it. It also provides guidelines for further research.
The anatomical basis of functional localization in the cortex

The functions of a cortical area are determined by its extrinsic connections and intrinsic properties. Using the database CoCoMac, we show that each cortical area has a unique pattern of cortico-cortical connections — a 'connectional fingerprint'. We present examples of such fingerprints and use statistical analysis to show that no two areas share identical patterns. We suggest that the connectional fingerprint underlies the observed cell-firing differences between areas during different tasks. We refer to this pattern as a 'functional fingerprint' and present examples of such fingerprints. In addition to electrophysiological analysis, functional fingerprints can be determined by functional brain imaging. We argue that imaging provides a useful way to define such fingerprints because it is possible to compare activations across many cortical areas and across a wide range of tasks.
Weather forecasting model using Artificial Neural Network

Weather forecasting has become an important field of research in the last few decades. In most of the cases the researcher had attempted to establish a linear relationship between the input weather data and the corresponding target data. But with the discovery of nonlinearity in the nature of weather data, the focus has shifted towards the nonlinear prediction of the weather data. Although, there are many literatures in nonlinear statistics for the weather forecasting, most of them required that the nonlinear model be specified before the estimation is done. But since the weather data is nonlinear and follows a very irregular trend, Artificial Neural Network (ANN) has evolved out to be a better technique to bring out the structural relationship between the various entities. The paper examines the applicability of ANN approach by developing effective and reliable nonlinear predictive models for weather analysis also compare and evaluate the performance of the developed models using different transfer functions, hidden layers and neurons to forecast maximum, temperature for 365 days of the year.
Classification cost: An empirical comparison among traditional classifier, Cost-Sensitive Classifier, and MetaCost

Loan fraud is a critical factor in the insolvency of financial institutions, so companies make an effort to reduce the loss from fraud by building a model for proactive fraud prediction. However, there are still two critical problems to be resolved for the fraud detection: (1) the lack of cost sensitivity between type I error and type II error in most prediction models, and (2) highly skewed distribution of class in the dataset used for fraud detection because of sparse fraud-related data. The objective of this paper is to examine whether classification cost is affected both by the cost-sensitive approach and by skewed distribution of class. To that end, we compare the classification cost incurred by a traditional cost-insensitive classification approach and two cost-sensitive classification approaches, Cost-Sensitive Classifier (CSC) and MetaCost. Experiments were conducted with a credit loan dataset from a major financial institution in Korea, while varying the distribution of class in the dataset and the number of input variables. The experiments showed that the lowest classification cost was incurred when the MetaCost approach was used and when non-fraud data and fraud data were balanced. In addition, the dataset that includes all delinquency variables was shown to be most effective on reducing the classification cost.
The efficacy of dance movement therapy group on improvement of quality of life : A randomized controlled trial

This study examines the treatment outcome of a ten weeks dance movement therapy intervention on quality of life (QOL). The multicentred study used a subject-design with pre-test, post-test, and six months follow-up test. 162 participants who suffered from stress were randomly assigned to the dance movement therapy treatment group (TG) (n = 97) and the wait-listed control group (WG) (65). The World Health Organization Quality of Life Questionnaire 100 (WHOQOL-100) and Munich Life Dimension List were used in both groups at all three measurement points. Repeated measures ANOVA revealed that dance movement therapy participants in all QOL dimensions always more than the WG. In the short term, they significantly improved in the Psychological domain (p > .001, WHOQOL; p > .01, Munich Life Dimension List), Social relations/life (p > .10, WHOQOL; p > .10, Munich Life Dimension List), Global value (p > .05, WHOQOL), Physical health (p > .05, Munich Life Dimension List), and General life (p > .10, Munich Life Dimension List). In the long term, dance movement therapy significantly enhanced the psychological domain (p > .05, WHOQOL; p > .05, Munich Life Dimension List), Spirituality (p > .10, WHOQOL), and General life (p > .05, Munich Life Dimension List). Dance movement therapy is effective in the shortand long-term to improve QOL.
Model-driven reverse engineering of legacy graphical user interfaces

Businesses are more and more modernizing the legacy systems they developed with Rapid Application Development (RAD), so that they can benefit from the new platforms and technologies. In these systems, the Graphical User Interface (GUI) layout is implicitly given by the position of the GUI elements (i.e. coordinates). However, taking advantage of current features of GUI technologies often requires an explicit, high-level layout model. We propose a Model-Driven Engineering process to perform reverse engineering of RAD-built GUIs, which is focused on discovering the implicit layout, and produces a GUI model where the layout is explicit. Based on the information we obtain, other reengineering activities can be performed, for example, to adapt the GUI for mobile device screens.
Knowledge Management: Concepts, Methodologies, Tools and Applications

Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark.  Resource retrieval addresses the problem of finding best matches to a request among available resources, with both the request and the resources described with respect to a shared interpretation of the knowledge domain the resource belongs to. The problem of resource matching and retrieval arises in several scenarios, among them, personnel recruitment and job assignment, dating agencies, but also generic electronic marketplaces, Web services discovery and composition, resource matching in the Grid. All these scenarios share a common purpose: given a request, find among available descriptions those best fulfilling it, or at " worse, " when nothing better exists, those that fulfill at least some of the requirements. Exact, or full, matches are usually rare and the true matchmaking process is aimed at providing one or more " promising " matches to be explored. Non-exact matches should take into account both missing information—details that could be positively assessed in a second phase—and conflicting information—details that could leverage negotiation if the proposed match is worth enough pursuing. Because of its intangibility, it is now a widely shared opinion that knowledge has to be modeled to make unambiguous the interpretation of any information domain. This disambiguation process is usually obtained through an ontology, that is, a specification of a representational vocabulary for a shared domain of discourse—definitions of classes, relations, functions, and other objects (Gruber, 1993). Once a knowledge domain has been mod-eled, and several different resources have been described using such a model, issues that need to be faced for efficient knowledge management are: What, if any, kind of retrieval is possible on these resources? How could we benefit both of the model and formalisms used to build the model, in order to perform a " smart " search of described resources matching a request? The above questions focus on important aspects of knowledge-based retrieval: • formalisms used to model a knowledge domain • retrieval services that fully use the expres-siveness of the formalism to infer new knowledge from the model in order to perform a knowledge-based search Knowledge domain is modeled with a formalism , whose expressiveness is used in the retrieval process to infer not elicited information from the model. …
Aerodynamics of wind turbine wakes Literature review

This report reviews the available literature on the aerodyn amics of wind turbines and wind farms. Firstly, two introductory chapters are devoted to the physi cs of the flow around a wind turbine and the existing engineering models for blade and wake aerod ynamics. The focus of this work is however on the numerical modeling of wakes. The difficulti es in solving the Navier-Stokes equations are discussed, and the different existing models for the description of the rotor and the wake are mentioned, along with problems associated with the choice of turbulence models and inflow conditions. The purpose of this overview is to include the latest develop ments in the numerical computation of wind turbine aerodynamics.
Rule-Based Prediction of Medical Claims' Payments: A Method and Initial Application to Medicaid Data

Imperfections in healthcare revenue cycle management systems cause discrepancies between submitted claims and received payments. This paper presents a method for deriving attributional rules that can be used to support the preparation and screening of claims prior to their submission to payers. The method starts with unsupervised analysis of past payments to determine normal levels of payments for services. Then, supervised machine learning is used to derive sets of attributional rules for predicting potential discrepancies in claims. New claims can be then classified using the created models. The method was tested on a subset of Obstetrics claims for payment submitted by one hospital to Medicaid. One year of data was used to create models, which were tested using the following year's data. Results indicate that rule-based models are able to detect abnormal claims prior to their submission.