nils-herrmann/clean_scirepeval huggingface dataset:
Image registration methods: a survey

This paper aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying images (two or more) of the same scene taken at different times, from different viewpoints, and/or by different sensors. The registration geometrically align two images (the reference and sensed images). The reviewed approaches are classified according to their nature (areabased and feature-based) and according to four basic steps of image registration procedure: feature detection, feature matching, mapping function design, and image transformation and resampling. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of image registration and outlook for the future research are discussed too. The major goal of the paper is to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas. q 2003 Elsevier B.V. All rights reserved.
Binary Input Layer: Training of CNN models with binary input data

For the efficient execution of deep convolutional neural networks (CNN) on edge devices, various approaches have been presented which reduce the bit width of the network parameters down to 1 bit. Binarization of the first layer was always excluded, as it leads to a significant error increase. Here, we present the novel concept of binary input layer (BIL), which allows the usage of binary input data by learning bit specific binary weights. The concept is evaluated on three datasets (PAMAP2, SVHN, CIFAR-10). Our results show that this approach is in particular beneficial for multimodal datasets (PAMAP2) where it outperforms networks using full precision weights in the first layer by 1.92 percentage points (pp) while consuming only 2% of the chip area.
Programming with Abstract Data Types

The motivation behind the work in very-high-level languages is to ease the programming task by providing the programmer with a language containing primitives or abstractions suitable to his problem area. The programmer is then able to spend his effort in the right place; he concentrates on solving his problem, and the resulting program will be more reliable as a result. Clearly, this is a worthwhile goal.
 Unfortunately, it is very difficult for a designer to select in advance all the abstractions which the users of his language might need. If a language is to be used at all, it is likely to be used to solve problems which its designer did not envision, and for which the abstractions embedded in the language are not sufficient.
 This paper presents an approach which allows the set of built-in abstractions to be augmented when the need for a new data abstraction is discovered. This approach to the handling of abstraction is an outgrowth of work on designing a language for structured programming. Relevant aspects of this language are described, and examples of the use and definitions of abstractions are given.
D2R Server - Publishing Relational Databases on the Semantic Web

D2R Server is a tool for publishing the content of relational databases on the Semantic Web. Database content is mapped to RDF by a declarative mapping which specifies how resources are identified and how property values are generated from database content. Based on this mapping, D2R Server allows Web agents to retrieve RDF and XHTML representations of resources and to query non-RDF databases using the SPARQL query language over the SPARQL protocol. The generated representations are richly interlinked on RDF and XHTML level in order to enable browsers and crawlers to navigate database content.
An In Vitro Study on the Effects of Post-Core Design and Ferrule on the Fracture Resistance of Endodontically Treated Maxillary Central Incisors

Endodontically treated teeth have significantly different physical and mechanical properties compared to vital teeth and are more prone to fracture. The study aims to compare the fracture resistance of endodontically treated teeth with and without post reinforcement, custom cast post-core and prefabricated post with glass ionomer core and to evaluate the ferrule effect on endodontically treated teeth restored with custom cast post-core.



A total of 40 human maxillary central incisors with similar dimensions devoid of any root caries, restorations, previous endodontic treatment or cracks were selected from a collection of stored extracted teeth. An initial silicone index of each tooth was made. They were treated endodontically and divided into four groups of ten specimens each. Their apical seal was maintained with 4 mm of gutta-percha. Root canal preparation was done and then post core fabrication was done. The prepared specimens were subjected to load testing using a computer coordinated UTM. The fracture load results were then statistically analyzed. One-way ANOVA was followed by paired t-test.



1. Reinforcement of endodontically treated maxillary central incisors with post and core, improved their fracture resistance to be at par with that of endodontically treated maxillary central incisor, with natural crown. 2. The fracture resistance of endodontically treated maxillary central incisors is significantly increased when restored with custom cast post-core and 2 mm ferrule.



With 2 mm ferrule, teeth restored with custom cast post-core had a significantly higher fracture resistance than teeth restored with custom cast post-core or prefabricated post and glass ionomer core without ferrule.
Short-term traffic flow prediction with Conv-LSTM

The accurate short-term traffic flow prediction can provide timely and accurate traffic condition information which can help one to make travel decision and mitigate the traffic jam. Deep learning (DL) provides a new paradigm for the analysis of big data generated by the urban daily traffic. In this paper, we propose a novel end-to-end deep learning architecture which consists of two modules. We combine convolution and LSTM to form a Conv-LSTM module which can extract the spatial-temporal information of the traffic flow information. Furthermore, a Bi-directional LSTM module is also adopted to analyze historical traffic flow data of the prediction point to get the traffic flow periodicity feature. The experimental results on the real dataset show that the proposed approach can achieve a better prediction accuracy compared with the existing approaches.
Comparison of Collision Avoidance Systems and Applicability to Rail Transport

The paper presents an overview of the state of the art in collision avoidance related with transportation systems like the automatic identification system (AIS) for maritime transportation, traffic alert and collision avoidance system/automatic dependent surveillance-broadcast (TCAS/ADS-B) for aircraft, and the car-2-car communication system (C2C) for road transportation. The examined systems rely on position detection and direct communication among vehicles. Alike a collision avoidance system for railway transportation "RCAS" is introduced. Focussing on the communication aspects, possible applicability of the examined state of the art systems to RCAS is studied. The analysis are performed at different communication system layers, namely application (APP) layer, media access control (MAC) layer and physical layer (PHY), which are the most relevant for a single hop network broadcast system as favorized in RCAS. Since multihop and addressed communication are not foreseen in a first RCAS approach, the network layer is not taken into account.
A Review of Substrate Integrated Waveguide End-Fire Antennas

Substrate integrated waveguide (SIW) is a planar waveguide structure, which offers the advantages of low profile, ease of fabrication, low insertion loss, and compatibility with other planar circuits. SIW end-fire antennas have drawn broad interests due to the potential applications in aircraft, missile, and radar systems. However, this planar structure suffers from narrow bandwidth due to severe impedance mismatch at the radiating aperture. Meanwhile, the narrow radiating aperture of SIW end-fire antennas also deteriorates the radiation performance. This paper presents a detailed review upon the most recent research efforts concerning the improvement of antenna performances. They are discussed and classified into three different categories from the aspect of polarization properties: horizontally polarized, vertically polarized, and circularly polarized SIW end-fire antennas. Some practical difficulties for the development of SIW end-fire antennas are pointed out and effective approaches are also provided. A wide variety of antenna examples are presented with respect to theoretical and experimental results.
An acute bout of self-myofascial release increases range of motion without a subsequent decrease in muscle activation or force.

Foam rolling is thought to improve muscular function, performance, overuse, and joint range of motion (ROM); however, there is no empirical evidence demonstrating this. Thus, the objective of the study was to determine the effect of self-myofascial release (SMR) via foam roller application on knee extensor force and activation and knee joint ROM. Eleven healthy male (height 178.9 ± 3.5 cm, mass 86.3 ± 7.4 kg, age 22.3 ± 3.8 years) subjects who were physically active participated. Subjects' quadriceps maximum voluntary contraction force, evoked force and activation, and knee joint ROM were measured before, 2 minutes, and 10 minutes after 2 conditions: (a) 2, 1-minute trials of SMR of the quadriceps via a foam roller and (b) no SMR (Control). A 2-way analysis of variance (condition × time) with repeated measures was performed on all dependent variables recorded in the precondition and postcondition tests. There were no significant differences between conditions for any of the neuromuscular dependent variables. However, after foam rolling, subjects' ROM significantly (p < 0.001) increased by 10° and 8° at 2 and 10 minutes, respectively. There was a significant (p < 0.01) negative correlation between subjects' force and ROM before foam rolling, which no longer existed after foam rolling. In conclusion, an acute bout of SMR of the quadriceps was an effective treatment to acutely enhance knee joint ROM without a concomitant deficit in muscle performance.
Quantifying driver stress: developing a system for collecting and processing bio-metric signals in natural situations.

A system for quantifying the physiological features of emotional stress is being developed for use during a driving task. Two prototypes, using sensors that measure the driver's skin conductance, respiration, muscle activity, and heart activity are presented. The first system allows sampling rates of 200 Hz on two fast channels and 20 Hz on six additional channels. It uses a wearable computer to do real-time processing on the signals and has an attached digital camera which was used to capture images of the driver's facial expression once every minute. The second system uses a car-based computer that allows a sampling rate of 1984 samples per second on eight channels. This system uses multiple video cameras to continuously capture the driver's facial expression and road conditions. The data is then synchronized with the physiological signals using a video quad-splitter. The methods for extracting physiological features in the driving environment are discussed, including measurement of the skin conductance orienting response, muscle activity, pulse, and respiration patterns. Preliminary studies show how using multiple modalities of sensors can help discriminate reactions to driving events and how individual's response to similar driving conditions can vary from day to day.
Abductive Matching in Question Answering

We study question-answering over semi-structured data. We introduce a new way to apply the technique of semantic parsing by applying machine learning only to provide annotations that the system infers to be missing; all the other parsing logic is in the form of manually authored rules. In effect, the machine learning is used to provide non-syntactic matches, a step that is ill-suited to manual rules. The advantage of this approach is in its debuggability and in its transparency to the end-user. We demonstrate the effectiveness of the approach by achieving state-of-the-art performance of 40.42% on a standard benchmark dataset over tables from Wikipedia.
Comparison between Auditory and Visual Simple Reaction Times

The purpose of this study was to find out whether the simple reaction time was faster for auditory or visual stimulus and the factors responsible for improving the performance of the athlete.  14 subjects were assigned randomly into groups consisting of 2 members. Both the members from each group performed both the visual and auditory tests. The tests were taken from the DirectRT software program from a laptop. The DirectRT software consists of Testlabvisual and Testlabsounds to test the reaction times to visual and auditory stimuli. The 2 members from each group completed both the visual and auditory reaction times, the data was taken and the mean reaction time was calculated excluding the first and last values.  The results show that the mean visual reaction time is around 331 milliseconds as compared to the mean auditory reaction time of around 284 milliseconds.  This shows that the auditory reaction time is faster than the visual reaction time. And also males have faster reaction times when compared to females for both auditory as well as visual stimuli.
Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern

Retaining users and facilitating continuance usage are crucial to the success of mobile social network services (SNS). This research examines the continuance usage of mobile SNS in China by integrating both the perspectives of social influence and privacy concern. Social influence includes three processes: compliance, identification and internalization, which are respectively represented by subjective norm, social identity, and group norm. The results indicate that these three factors and privacy concern have significant effects on continuance usage. The results suggest that service providers should address the issues of social influence and privacy concern to encourage mobile SNS continuance usage.
Predictive Analytics On Public Data - The Case Of Stock Markets

This work examines the predictive power of public data by aggregating information from multiple online sources. Our sources include microblogging sites like Twitter, online message boards like Yahoo! Finance, and traditional news articles. The subject of prediction are daily stock price movements from Standard & Poor’s 500 index (S&P 500) during a period from June 2011 to November 2011. To forecast price movements we filter messages by stocks, apply state-of-the-art sentiment analysis to message texts, and aggregate message sentiments to generate trading signals for daily buy and sell decisions. We evaluate prediction quality through a simple trading model considering real-world limitations like transaction costs or broker commission fees. Considering 833 virtual trades, our model outperformed the S&P 500 and achieved a positive return on investment of up to ~0.49% per trade or ~0.24% when adjusted by market, depending on supposed trading costs.
Algorithms for the variable sized bin packing problem

In this paper, we consider the variable sized bin packing problem where the objective is to minimize the total cost of used bins when the cost of unit size of each bin does not increase as the bin size increases. Two greedy algorithms are described, and analyzed in three special cases: (a) the sizes of items and bins are divisible, respectively, (b) only the sizes of bins are divisible, and (c) the sizes of bins are not divisible. Here, we say that a list of numbers a1; a2; . . . ; am are divisible when aj exactly divides aj 1, for each 1 < j6m. In the case of (a), the algorithms give optimal solutions, and in the case of (b), each algorithm gives a solution whose value is less than 11 9 CðB Þ þ 4 9 , where CðB Þ is the optimal value. In the case of (c), each algorithm gives a solution whose value is less than 3 2 CðB Þ þ 1.
A Radiation Hard Bandgap Reference Circuit in a Standard 0.13  $\mu$m CMOS Technology

With ongoing CMOS evolution, the gate-oxide thickness steadily decreases, resulting in an increased radiation tolerance of MOS transistors. Combined with special layout techniques, this yields circuits with a high inherent robustness against X-rays and other ionizing radiation. In bandgap voltage references, the dominant radiation-susceptibility is then no longer associated with the MOS transistors, but is dominated by the diodes. This paper gives an analysis of radiation effects in both MOS devices and diodes and presents a solution to realize a radiation-hard voltage reference circuit in a standard CMOS technology. A demonstrator circuit was implemented in a standard 0.13 mum CMOS technology. Measurements show correct operation with supply voltages in the range from 1.4 V down to 0.85 V, a reference voltage of 405 mV plusmn 7.5 mV ( sigma = 6 mV chip-to-chip statistical spread), and a reference voltage shift of only plusmn1.5 mV (around 0.8%) under irradiation up to 44 Mrad (Si).
Leveraging Text and Knowledge Bases for Triple Scoring: An Ensemble Approach - The BOKCHOY Triple Scorer at WSDM Cup 2017

We present our winning solution for the WSDM Cup 2017 triple scoring task. We devise an ensemble of four base scorers, so as to leverage the power of both text and knowledge bases for that task. Then we further refine the outputs of the ensemble by trigger word detection, achieving even better predictive accuracy. The code is available at https://github.com/wsdm-cup-2017/bokchoy.
The LOCATA Challenge Data Corpus for Acoustic Source Localization and Tracking

Algorithms for acoustic source localization and tracking are essential for a wide range of applications such as personal assistants, smart homes, tele-conferencing systems, hearing aids, or autonomous systems. Numerous algorithms have been proposed for this purpose which, however, are not evaluated and compared against each other by using a common database so far. The IEEE-AASP Challenge on sound source localization and tracking (LOCATA) provides a novel, comprehensive data corpus for the objective benchmarking of state-of-the-art algorithms on sound source localization and tracking. The data corpus comprises six tasks ranging from the localization of a single static sound source with a static microphone array to the tracking of multiple moving speakers with a moving microphone array. It contains real-world multichannel audio recordings, obtained by hearing aids, microphones integrated in a robot head, a planar and a spherical microphone array in an enclosed acoustic environment, as well as positional information about the involved arrays and sound sources represented by moving human talkers or static loudspeakers.
A Roadmap for the Value-Loading Problem

We analyze the value-loading problem. This is the problem of robustly encoding moral values into an AI agent interacting with a complex environment. Like many before, we argue that this is both a major concern and an extremely challenging problem. Solving it will likely require years, if not decades, of multidisciplinary work by teams of top scientists and experts. Given how uncertain the timeline of human-level AI research is, we thus argue that a pragmatic partial solution should be designed as
A New Development in Online Marketing : Introducing Digital Inbound Marketing

Particularly in online settings, marketing is undergoing a transformation. Online business can no longer rely on traditional marketing tactics and campaigns to attract, retain and expand consumers because there is a transformation in how people interact with brands and companies, how they shop and buy in online and offline settings. Traditional marketing is no longer a viable option because it focuses on pushing a message out. In online business framework, a new marketing development has arisen, namely digital inbound marketing. This new marketing type is focused on attracting valuable consumers (potential, existing, or aspirational) that choose to interact with a particular company that provides them with something useful. In this paper, we propose a definition for digital inbound marketing and examine the online strategies associated with this concept: brand-focused marketing communications, content marketing, social media marketing, and search engine optimization.
Temperature-Aware Microarchitecture

With power density and hence cooling costs rising exponentially, processor packaging can no longer be designed for the worst case, and there is an urgent need for runtime processor-level techniques that can regulate operating temperature when the package's capacity is exceeded. Evaluating such techniques, however, requires a thermal model that is practical for architectural studies.This paper describes HotSpot, an accurate yet fast model based on an equivalent circuit of thermal resistances and capacitances that correspond to microarchitecture blocks and essential aspects of the thermal package. Validation was performed using finite-element simulation. The paper also introduces several effective methods for dynamic thermal management (DTM): "temperature-tracking" frequency scaling, localized toggling, and migrating computation to spare hardware units. Modeling temperature at the microarchitecture level also shows that power metrics are poor predictors of temperature, and that sensor imprecision has a substantial impact on the performance of DTM.
Monophyly of Primary Photosynthetic Eukaryotes: Green Plants, Red Algae, and Glaucophytes

Between 1 and 1.5 billion years ago, eukaryotic organisms acquired the ability to convert light into chemical energy through endosymbiosis with a Cyanobacterium (e.g.,). This event gave rise to "primary" plastids, which are present in green plants, red algae, and glaucophytes ("Plantae" sensu Cavalier-Smith). The widely accepted view that primary plastids arose only once implies two predictions: (1) all plastids form a monophyletic group, as do (2) primary photosynthetic eukaryotes. Nonetheless, unequivocal support for both predictions is lacking (e.g.,). In this report, we present two phylogenomic analyses, with 50 genes from 16 plastid and 15 cyanobacterial genomes and with 143 nuclear genes from 34 eukaryotic species, respectively. The nuclear dataset includes new sequences from glaucophytes, the less-studied group of primary photosynthetic eukaryotes. We find significant support for both predictions. Taken together, our analyses provide the first strong support for a single endosymbiotic event that gave rise to primary photosynthetic eukaryotes, the Plantae. Because our dataset does not cover the entire eukaryotic diversity (but only four of six major groups in), further testing of the monophyly of Plantae should include representatives from eukaryotic lineages for which currently insufficient sequence information is available.