nils-herrmann/clean_scirepeval huggingface dataset:
Monte Carlo calculations of kQ, the beam quality conversion factor.

To use EGSnrc Monte Carlo simulations to directly calculate beam quality conversion factors,kQ, for 32 cylindrical ionization chambers over a range of beam qualities and to quantify the effect of systematic uncertainties on Monte Carlo calculations of kQ. These factors are required to use the TG-51 or TRS-398 clinical dosimetry protocols for calibrating external radiotherapy beams.



Ionization chambers are modeled either from blueprints or manufacturers' user's manuals. The dose-to-air in the chamber is calculated using the EGSnrc user-code egs_chamber using 11 different tabulated clinical photon spectra for the incident beams. The dose to a small volume of water is also calculated in the absence of the chamber at the midpoint of the chamber on its central axis. Using a simple equation,kQ is calculated from these quantities under the assumption that W/e is constant with energy and compared to TG-51 protocol and measured values.



Polynomial fits to the Monte Carlo calculatedkQ factors as a function of beam quality expressed as %dd(10)x and TPR1020 are given for each ionization chamber. Differences are explained between Monte Carlo calculated values and values from the TG-51 protocol or calculated using the computer program used for TG-51 calculations. Systematic uncertainties in calculated kQ values are analyzed and amount to a maximum of one standard deviation uncertainty of 0.99% if one assumes that photon cross-section uncertainties are uncorrelated and 0.63% if they are assumed correlated. The largest components of the uncertainty are the constancy of W/e and the uncertainty in the cross-section for photons in water.



It is now possible to calculatekQ directly using Monte Carlo simulations. Monte Carlo calculations for most ionization chambers give results which are comparable to TG-51 values. Discrepancies can be explained using individual Monte Carlo calculations of various correction factors which are more accurate than previously used values. For small ionization chambers with central electrodes composed of high-Z materials, the effect of the central electrode is much larger than that for the aluminum electrodes in Farmer chambers.
ICDAR2017 Competition on Handwritten Text Recognition on the READ Dataset

This paper describes the fourth edition of the Handwritten Text Recognition (HTR) competition that was prepared this time in the context of the International Conference on Document Analysis and Recognition (ICDAR) 2017. Previous editions of this competition were conducted, first, with datasets from the tranScriptorium project in ICFHR 2014, and ICDAR 2015, and then, with datasets from the "Recognition and Enrichment of Archival Documents (READ)" European project in ICFHR 2016. This competition aims to bring together researchers working on off-line HTR and provides them a suitable benchmark to compare their techniques on the task of transcribing typical and difficult historical handwritten documents. The competition proposed for ICDAR 2017 aims at introducing a usual scenario for some collections in which there exist transcripts at page level for many pages useful for training, but these transcripts are not aligned with line images. Two tracks with different conditions on the use of training data were proposed. Most of the data comes from the Alfred Escher Letter Collection. But handwritten images were drawn from other German collections written by several hands.
A comparison of machine learning algorithms for regional wheat yield prediction using NDVI time series of SPOT-VGT

This study compares two machine learning algorithms to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Periods of high influence spanning from March to June were detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for yield forecasting. BRT seems to consistently outperform SVM.
Clinical measurement of craniovertebral angle by electronic head posture instrument: a test of reliability and validity.

The study was a cross-sectional reliability study with the objective of assessing the reliability and validity of the Electronic Head Posture Instrument (EHPI) in measuring the craniovertebral (CV) angle for subjects with or without neck pain. Twenty-six subjects (mean age=36.88, SD+/-9.95) with chronic neck pain and 27 subjects (mean age=31.85, SD+/-7.63) without neck pain were recruited. The CV angle was measured by the EHPI which consists of an electronic angle finder, a transparent plastic base and a camera stand. Two therapists were recruited to assess the intra- and inter-rater reliability of the EHPI in two separate sessions of measurement. The difference in CV angle between the two groups was determined. The CV angle of the patient group (mean 43.94, SD+/-3.61) was significantly smaller (p<0.001) than that of the normal group (mean 50.58, SD+/-2.09). Intra-rater (intra-class correlation coefficient (ICC) ranged from 0.86 to 0.94) and inter-rater (ICC ranged from 0.85 to 0.91) reliability of the EHPI in measuring CV angle for both groups of subjects were high. In conclusion the EHPI was found to be reliable and valid in measuring the CV angle for subjects with or without neck pain.
Answering Schrödinger's question: A free-energy formulation

The free-energy principle (FEP) is a formal model of neuronal processes that is widely recognised in neuroscience as a unifying theory of the brain and biobehaviour. More recently, however, it has been extended beyond the brain to explain the dynamics of living systems, and their unique capacity to avoid decay. The aim of this review is to synthesise these advances with a meta-theoretical ontology of biological systems called variational neuroethology, which integrates the FEP with Tinbergen's four research questions to explain biological systems across spatial and temporal scales. We exemplify this framework by applying it to Homo sapiens, before translating variational neuroethology into a systematic research heuristic that supplies the biological, cognitive, and social sciences with a computationally tractable guide to discovery.
Checking Business Process Evolution

Business processes support the modeling and the implementation of software as workflows of local and inter-process activities. Taking over structuring and composition, evolution has become a central concern in software development. We advocate it should be taken into account as soon as the modeling of business processes, which can thereafter be made executable using process engines or model-to-code transformations. We show here that business process evolution needs formal analysis in order to compare different versions of processes, identify precisely the differences between them, and ensure the desired consistency. To reach this objective, we first present a model transformation from the BPMN standard notation to the LNT process algebra. We then propose a set of relations for comparing business processes at the formal model level. With reference to related work, we propose a richer set of comparison primitives supporting renaming, refinement, propertyand context-awareness. Thanks to an implementation of our approach that can be used through a Web application, we put the checking of evolution within the reach of business process designers.
Matching Web Tables with Knowledge Base Entities: From Entity Lookups to Entity Embeddings

Web tables constitute valuable sources of information for various applications, ranging from Web search to Knowledge Base (KB) augmentation. An underlying common requirement is to annotate the rows of Web tables with semantically rich descriptions of entities published in Web KBs. In this paper, we evaluate three unsupervised annotation methods: (a) a lookup-based method which relies on the minimal entity context provided in Web tables to discover correspondences to the KB, (b) a semantic embeddings method that exploits a vectorial representation of the rich entity context in a KB to identify the most relevant subset of entities in the Web table, and (c) an ontology matching method, which exploits schematic and instance information of entities available both in a KB and a Web table. Our experimental evaluation is conducted using two existing benchmark data sets in addition to a new large-scale benchmark created using Wikipedia tables. Our results show that: 1) our novel lookup-based method outperforms state-of-theart lookup-based methods, 2) the semantic embeddings method outperforms lookup-based methods in one benchmark data set, and 3) the lack of a rich schema in Web tables can limit the ability of ontology matching tools in performing high-quality table annotation. As a result, we propose a hybrid method that significantly outperforms individual methods on all the benchmarks.
The end of the end of ideology.

The "end of ideology" was declared by social scientists in the aftermath of World War II. They argued that (a) ordinary citizens' political attitudes lack the kind of stability, consistency, and constraint that ideology requires; (b) ideological constructs such as liberalism and conservatism lack motivational potency and behavioral significance; (c) there are no major differences in content (or substance) between liberal and conservative points of view; and (d) there are few important differences in psychological processes (or styles) that underlie liberal versus conservative orientations. The end-of-ideologists were so influential that researchers ignored the topic of ideology for many years. However, current political realities, recent data from the American National Election Studies, and results from an emerging psychological paradigm provide strong grounds for returning to the study of ideology. Studies reveal that there are indeed meaningful political and psychological differences that covary with ideological self-placement. Situational variables--including system threat and mortality salience--and dispositional variables--including openness and conscientiousness--affect the degree to which an individual is drawn to liberal versus conservative leaders, parties, and opinions. A psychological analysis is also useful for understanding the political divide between "red states" and "blue states."
Advances in Reversed Nested Miller Compensation

The use of two frequency compensation schemes for three-stage operational transconductance amplifiers, namely the reversed nested Miller compensation with nulling resistor (RN-MCNR) and reversed active feedback frequency compensation (RAFFC), is presented in this paper. The techniques are based on the basic RNMC and show an inherent advantage over traditional compensation strategies, especially for heavy capacitive loads. Moreover, they are implemented without entailing extra transistors, thus saving circuit complexity and power consumption. A well-defined design procedure, introducing phase margin as main design parameter, is also developed for each solution. To verify the effectiveness of the techniques, two amplifiers have been fabricated in a standard 0.5-mum CMOS process. Experimental measurements are found in good agreement with theoretical analysis and show an improvement in small-signal and large-signal amplifier performances. Finally, an analytical comparison with the nonreversed counterparts topologies, which shows the superiority of the proposed solutions, is also included.
Deep feature for text-dependent speaker verification

Recently deep learning has been successfully used in speech recognition, however it has not been carefully explored and widely accepted for speaker verification. To incorporate deep learning into speaker verification, this paper proposes novel approaches of extracting and using features from deep learning models for text-dependent speaker verification. In contrast to the traditional short-term spectral feature, such as MFCC or PLP, in this paper, outputs from hidden layer of various deep models are employed as deep features for text-dependent speaker verification. Fours types of deep models are investigated: deep Restricted Boltzmann Machines, speech-discriminant Deep Neural Network (DNN), speaker-discriminant DNN, and multi-task joint-learned DNN. Once deep features are extracted, they may be used within either the GMM-UBM framework or the identity vector (i-vector) framework. Joint linear discriminant analysis and probabilistic linear discriminant analysis are proposed as effective back-end classifiers for identity vector based deep features. These approaches were evaluated on the RSR2015 data corpus. Experiments showed that deep feature based methods can obtain significant performance improvements compared to the traditional baselines, no matter if they are directly applied in the GMM-UBM system or utilized as identity vectors. The EER of the best system using the proposed identity vector is 0.10%, only one fifteenth of that in the GMM-UBM baseline.
A Sequential Importance Sampling Algorithm for Generating Random Graphs with Prescribed Degrees

Random graphs with a given degree sequence are a useful model capturing several features absent in the classical Erdős-Rényi model, such as dependent edges and non-binomial degrees. In this paper, we use a characterization due to Erdős and Gallai to develop a sequential algorithm for generating a random labeled graph with a given degree sequence. The algorithm is easy to implement and allows surprisingly efficient sequential importance sampling. Applications are given, including simulating a biological network and estimating the number of graphs with a given degree sequence.
Alopecia areata incognita

Alopecia areata incognita, also known as diffuse alopecia areata, is a rare form of alopecia areata described predominantly in young women. In cases of alopecia areata incognita, the typical patchy distribution of hair loss in classical alopecia areata is absent, but abrupt and intense hair loss is characteristic. While the clinical picture presented by this disease closely resembles that of telogen effluvium, specific clinical and dermoscopic findings of alopecia areata are invariably present along the disease course. Prognosis is generally favorable, especially as compared to certain variants of alopecia areata, namely, alopecia areata totalis, universalis and ophiasic areata.
2395-1621 Hand Gesture Recognition Using Flex Sensors

ARTICLE INFO In this system an electro-mechanical robot is designed and controlled using hand gesture in real time. The system is designed on microcontroller platform using Keil and MPLAB tools. Hand gesture recognition is done on the principle of resistance change sensed through flex sensor. These sensors are integrated in a hand gloves from which input to the system is given. The designed system is divided into two sections as transmitter and receiver. The transmitter section will be in hand gloves from which the data is sensed and processed through PIC16F7487 and send serially to the receiver section. RF technology is used to transmit the data at the receiver section at the frequency of 2.4 GHz. ARM 7 (LPC2148) processor is used to receive the data. Here from the received data, the character is predicted and matched with the closet character from which the character is identified and displayed on LCD. The various case studies is prepared for the designed system and tested in real time. The proposed system can be used for the various applications such as in unmanned machines, industries, handicapped personnel etc.  a Sensor gloves, flex sensors, PIC controller, ARM processor etc Article History Received:20 th September 2015 Received in revised form :
Single-Phase Seven-Level Grid-Connected Inverter for Photovoltaic System

This paper proposes a single-phase seven-level inverter for grid-connected photovoltaic systems, with a novel pulsewidth-modulated (PWM) control scheme. Three reference signals that are identical to each other with an offset that is equivalent to the amplitude of the triangular carrier signal were used to generate the PWM signals. The inverter is capable of producing seven levels of output-voltage levels (Vdc, 2Vdc/3, Vdc/3, 0, -Vdc, -2Vdc/3, -Vdc/3) from the dc supply voltage. A digital proportional-integral current-control algorithm was implemented in a TMS320F2812 DSP to keep the current injected into the grid sinusoidal. The proposed system was verified through simulation and implemented in a prototype.
A Survey on Survey of Migration of Legacy Systems

Legacy systems are mission critical complex systems which are hard to maintain owing to shortage of skill sets and monolithic code architecture with tightly coupled tiers, all of which are indication of obsoleteness of the system technology. Thus, they have to be migrated to the latest technology(ies). Migration is an offspring research in Software Engineering which is almost three decades old research and numerous publications have emerged in many topics in the migration domain with focus areas of code migration, architecture migration, case study on migration and effort estimation on migration. In addition, various survey works surveying different aspects of migration have also emerged. This paper provides a survey of these survey works in order to provide a consolidation of these survey works. As an outcome of the survey on survey of migration, a road map of migration evolution from the early stages to the recent works on migration comprising of significant milestones in migration research has been presented in this work.
The Ideology of Interactivity (or Video Games and Taylorization of Leisure)

Interactivity is one of the key conceptual apparatuses through which video games have been theorized thus far. As many writers have noted, video games are distinct from other forms of media because player actions seem to have direct, immediate consequences in the world depicted onscreen. But in many ways, this “interactive” feature of video games tends to manifest itself as a relentless series of demands, or a way of disciplining player behavior. In this sense, it seems more accurate to describe the human-machine interface made possible by gaming as an aggressive form of “interpellation” or hailing. Drawing primarily upon the work of Louis Althusser, I argue that traditional theories of interactivity fail to acknowledge the work of video games—in other words, the extent to which video games define and reconstitute players as subjects of ideology.
Neural systems behind word and concept retrieval

Using both the lesion method and functional imaging (positron emission tomography) in large cohorts of subjects investigated with the same experimental tasks, we tested the following hypotheses: (A) that the retrieval of words which denote concrete entities belonging to distinct conceptual categories depends upon partially segregated regions in higher-order cortices of the left temporal lobe; and (B) that the retrieval of conceptual knowledge pertaining to the same concrete entities also depends on partially segregated regions; however, those regions will be different from those postulated in hypothesis A, and located predominantly in the right hemisphere (the second hypothesis tested only with the lesion method). The analyses provide support for hypothesis A in that several regions outside the classical Broca and Wernicke language areas are involved in name retrieval of concrete entities, and that there is a partial segregation in the temporal lobe with respect to the conceptual category to which the entities belong, and partial support for hypothesis B in that retrieval of conceptual knowledge is partially segregated from name retrieval in the lesion study. Those regions identified here are seen as parts of flexible, multi-component systems serving concept and word retrieval for concrete entities belonging to different conceptual categories. By comparing different approaches the article also addresses a number of method issues that have surfaced in recent studies in this field.
Robotic Self-replication in Structured Environments: Physical Demonstrations and Complexity Measures

In this paper we define a complexity ratio that measures the degree to which a robot is self-replicating based on the number and complexity of subsystems that it can assemble to form a functional replica. We also quantify how structured the environment must be in order for a robot to function. This calculation uses Sanderson’s concept of parts entropy. Together, the complexity measure of the robot and environmental entropy provide quantitative benchmarks to assess the state of the art in the subfield of self-replicating robotic systems, and provide goals for the design of future systems. We demonstrate these principles with three prototype systems that show different degrees of robotic self-replication. The first robot is controlled by a microprocessor and consists of five subsystems. The second has no microprocessor and is implemented as a finite-state machine consisting of discrete logic chips that are distributed over five subsystems. The third design consists of six subsystems and is able to handle greater environmental entropy. These systems demonstrate the desired progression towards self-replicating robots consisting of greater numbers of subsystems, each of lower complexity, and which are able to function in environments with increasing levels of disorder. robotic self-replication, self-assembly, modular robots, distributed robotic systems
A Generic Layered Architecture for Context Aware Applications

As pervasive computing is at its preliminary stage a number of computing solutions were proposed and more are still under experimentation. In this paper a four layered generic architecture is proposed with a recommended components so as to support context awareness for pervasive applications. Detail of each layer is described sufficiently to insight the process of context generation from low level contextual data up to high level context reporting scheme in a given pervasive environment. The implementation section of this article describes how the context reasoning component employee different level of reasoning techniques such as knowledge acquisition, context based rule execution and the application of ontology in pervasive computing.
INTELLIGENT SYSTEMS IN TOURISM A Social Science Perspective

Intelligent systems sense their environment and learn from the actions they implement to reach specific goals. They are increasingly used to support tourist information search and decision making as well as work processes. In order to model the tourism domain, these systems require a profound understanding of its nature. Looking at existing literature in tourism, this paper discusses critical gaps in the knowledge of the field to be filled so that intelligent system design can be informed and impacts understood. Specifically, it discusses the need to better conceptualize technology in tourism research and argues for a focus on uses and interactions. It challenges simplistic views of tourist information search and decisionmaking processes and calls for more research on potential impacts.
How Affective Is a "Like"?: The Effect of Paralinguistic Digital Affordances on Perceived Social Support

A national survey asked 323 U.S. adults about paralinguistic digital affordances (PDAs) and how these forms of lightweight feedback within social media were associated with their perceived social support. People perceived PDAs (e.g., Likes, Favorites, and Upvotes) as socially supportive both quantitatively and qualitatively, even without implicit meaning associated with them. People who are highly sensitive about what others think of them and have high self-esteem are more likely to perceive higher social support from PDAs.