nils-herrmann/clean_scirepeval huggingface dataset:
LED Based Indoor Visible Light Communications: State of the Art

Visible Light Communication (VLC) is an emerging field in Optical Wireless Communication (OWC) which utilizes the superior modulation bandwidth of Light Emitting Diodes (LEDs) to transmit data. In modern day communication systems, the most popular frequency band is Radio Frequency (RF) mainly due to little interference and good coverage. However, the rapidly dwindling RF spectrum along with increasing wireless network traffic has substantiated the need for greater bandwidth and spectral relief. By combining illumination and communication, VLC provides ubiquitous communication while addressing the shortfalls and limitations of RF communication. This paper provides a comprehensive survey on VLC with an emphasis on challenges faced in indoor applications over the period 1979-2014. VLC is compared with infrared (IR) and RF systems and the necessity for using this beneficial technology in communication systems is justified. The advantages of LEDs compared to traditional lighting technologies are discussed and comparison is done between different types of LEDs currently available. Modulation schemes and dimming techniques for indoor VLC are discussed in detail. Methods needed to improve VLC system performance such as filtering, equalization, compensation, and beamforming are also presented. The recent progress made by various research groups in this field is discussed along with the possible applications of this technology. Finally, the limitations of VLC as well as the probable future directions are presented.
Point Signatures: A New Representation for 3D Object Recognition

Few systems capable of recognizing complex objects with free-form (sculptured) surfaces have been developed. The apparent lack of success is mainly due to the lack of a competent modelling scheme for representing such complex objects. In this paper, a new form of point representation for describing 3D free-form surfaces is proposed. This representation, which we call the point signature, serves to describe the structural neighbourhood of a point in a more complete manner than just using the 3D coordinates of the point. Being invariant to rotation and translation, the point signature can be used directly to hypothesize the correspondence to model points with similar signatures. Recognition is achieved by matching the signatures of data points representing the sensed surface to the signatures of data points representing the model surface. The use of point signatures is not restricted to the recognition of a single-object scene to a small library of models. Instead, it can be extended naturally to the recognition of scenes containing multiple partially-overlapping objects (which may also be juxtaposed with each other) against a large model library. No preliminary phase of segmenting the scene into the component objects is required. In searching for the appropriate candidate model, recognition need not proceed in a linear order which can become prohibitive for a large model library. For a given scene, signatures are extracted at arbitrarily spaced seed points. Each of these signatures is used to vote for models that contain points having similar signatures. Inappropriate models with low votes can be rejected while the remaining candidate models are ordered according to the votes they received. In this way, efficient verification of the hypothesized candidates can proceed by testing the most likely model first. Experiments using real data obtained from a range finder have shown fast recognition from a library of fifteen models whose complexities vary from that of simple piecewise quadric shapes to complicated face masks. Results from the recognition of both single-object and multiple-object scenes are presented.
Automatic classification of diabetic macular edema in digital fundus images

Diabetic macular edema is a common complication of diabetic retinopathy due to the presence of exudates in proximity with the fovea. In this paper, an automated method to classify diabetic macular edema is presented. The fovea is localized and the regions of macula are marked based on the Early Treatment Diabetic Retinopathy Studies (ETDRS) grading scale. Extraction method using marker-controlled watershed transformation is adopted and modified from the previous research. The location of the extracted exudates on the marked macular regions is computed to classify diabetic macular edema into normal, stage 1 and stage 2 diabetic macular edema. The performance of the proposed method is evaluated using 88 images of publicly available MESSIDOR database. The overall sensitivity, specificity and accuracy of the proposed method are 80.9%, 90.2% and 85.2%, respectively.
Classifier Fitness Based on Accuracy

In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. The system executes the genetic algorithm in niches defined by the match sets, instead of panmictically. These aspects of XCS result in its population tending to form a complete and accurate mapping X A P from inputs and actions to payoff predictions. Further, XCS tends to evolve classifiers that are maximally general, subject to an accuracy criterion. Besides introducing a new direction for classifier system research, these properties of XCS make it suitable for a wide range of reinforcement learning situations where generalization over states is desirable.
A CUDA-based parallel implementation of K-nearest neighbor algorithm

Recent developments in Graphics Processing Units (GPUs) have enabled inexpensive high performance computing for general-purpose applications. Due to GPU's tremendous computing capability, it has emerged as the co-processor of the CPU to achieve a high overall throughput. CUDA programming model provides the programmers adequate C language like APIs to better exploit the parallel power of the GPU. K-nearest neighbor (KNN) is a widely used classification technique and has significant applications in various domains, especially in text classification. The computational-intensive nature of KNN requires a high performance implementation. In this paper, we present a CUDA-based parallel implementation of KNN, CUKNN, using CUDA multi-thread model, where the data elements are processed in a data-parallel fashion. Various CUDA optimization techniques are applied to maximize the utilization of the GPU. CUKNN outperforms the serial KNN on an HP xw8600 workstation significantly, achieving up to 46.71X speedup including I/O time. It also shows good scalability when varying the dimension of the reference dataset, the number of records in the reference dataset, and the number of records in the query dataset.
A Survey of Maneuvering Target Tracking — Part III : Measurement Models

This is the third part of a series of papers that provide a comprehensive survey of the techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. Part I  and Part II [2] deal with general target motion models and ballistic target motion models, respectively. This part surveys measurement models, including measurement model-based techniques, used in target tracking. Models in Cartesian, sensor measurement, their mixed, and other coordinates are covered. The stress is on more recent advances — topics that have received more attention recently are discussed in greater details.
Design Considerations for Direct-Conversion Receivers

This paper describes the issues and tradeoffs in the design and monolithic implementation of direct-conversion receivers and proposes circuit techniques that can alleviate the drawbacks of this architecture. Following a brief study of heterodyne and image-reject topologies, the direct-conversion architecture is introduced and effects such as dc offset, I=Q mismatch, even-order distortion, flicker noise, and oscillator leakage are analyzed. Related design techniques for amplification and mixing, quadrature phase calibration, and baseband processing are also described.
UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound

We develop a novel transition-based parsing algorithm for the abstract meaning representation parsing task using exact imitation learning, in which the parser learns a statistical model by imitating the actions of an expert on the training data. We then use the imitation learning algorithm DAGGER to improve the performance, and apply an α-bound as a simple noise reduction technique. Our performance on the test set was 60% in F-score, and the performance gains on the development set due to DAGGER was up to 1.1 points of Fscore. The α-bound improved performance by up to 1.8 points.
The Friendship Questionnaire: an investigation of adults with Asperger syndrome or high-functioning autism, and normal sex differences.

Friendship is an important part of normal social functioning, yet there are precious few instruments for measuring individual differences in this domain. In this article, we report a new self-report questionnaire, the Friendship Questionnaire (FQ), for use with adults of normal intelligence. A high score on the FQ is achieved by the respondent reporting that they enjoy close, empathic, supportive, caring friendships that are important to them; that they like and are interested in people; and that they enjoy interacting with others for its own sake. The FQ has a maximum score of 135 and a minimum of zero. In Study 1, we carried out a study of n = 76 (27 males and 49 females) adults from a general population, to test for previously reported sex differences in friendships. This confirmed that women scored significantly higher than men. In Study 2, we employed the FQ with n = 68 adults (51 males, 17 females) with Asperger Syndrome or high-functioning autism to test the theory that autism is an extreme form of the male brain. The adults with Asperger Syndrome or high-functioning autism scored significantly lower on the FQ than both the male and female controls from Study 1. The FQ thus reveals both a sex difference in the style of friendship in the general population, and provides support for the extreme male brain theory of autism.
Automatic Human Animation for Non-Humanoid 3D Characters

In this paper, we propose a system, that automatically transfers human body motion captured from an ordinary video camera to an unknown 3D character mesh. In our system, no manual intervention is required for specifying the internal skeletal structure or defining how the mesh surfaces deform. A sparse graph is generated from the input polygons based on their connectivity and geometric distributions. To estimate articulated body parts in the video, a progressive particle filter is used for identifying correspondences. We anticipate our proposed system can bring animation to a new audience with a more intuitive user interface.
A Survey on Recommendations in Location-based Social Networks

Recent advances in position localization techniques have fundamentally enhanced social networking services, allowing users to share their locations and location-related content, such as geo-tagged photos and notes. We refer to these social networks as location-based social networks (LBSNs). Location data both bridges the gap between the physical and digital worlds and enables a deeper understanding of user preferences and behavior. This addition of vast geospatial datasets has stimulated research into novel recommender systems that seek to facilitate users’ travels and social interactions. In this paper, we offer a systematic review of this research, summarizing the contributions of individual efforts and exploring their relations. We discuss the new properties and challenges that location brings to recommendation systems for LBSNs. We present a comprehensive survey of recommender systems for LBSNs, analyzing 1) the data source used, 2) the methodology employed to generate a recommendation, and 3) the objective of the recommendation. We propose three taxonomies that partition the recommender systems according to the properties listed above. First, we categorize the recommender systems by the objective of the recommendation, which can include locations, users, activities, or social media.Second, we categorize the recommender systems by the methodologies employed, including content-based, link analysis-based, and collaborative filtering-based methodologies. Third, we categorize the systems by the data sources used, including user profiles, user online histories, and user location histories. For each category, we summarize the goals and contributions of each system and highlight one representative research effort. Further, we provide comparative analysis of the recommendation systems within each category. Finally, we discuss methods of evaluation for these recommender systems and point out promising research topics for future work. This article presents a panorama of the recommendation systems in location-based social networks with a balanced depth, facilitating research into this important research theme.
A taxonomy for attack graph generation and usage in network security

Attack graphs model possible paths that a potential attacker can use to intrude into a target network. They can be used in determining both proactive and reactive security measures. Attack graph generation is a process that includes vulnerability information processing, collecting network topology and application information, determining reachability conditions among network hosts, and applying the core graph building algorithm. This article introduces a classification scheme for a systematical study of the methods applied in each phase of the attack graph generation process, including the usage of attack graphs for network security. The related works in the literature are stated based on the proposed classification scheme and contributive ideas about potential challenges and open issues for attack graph generation and usage are provided.
Bayesian Online Changepoint Detection

Changepoints are abrupt variations in the generative parameters of a data sequence. Online detection of changepoints is useful in modelling and prediction of time series in application areas such as finance, biometrics, and robotics. While frequentist methods have yielded online filtering and prediction techniques, most Bayesian papers have focused on the retrospective segmentation problem. Here we examine the case where the model parameters before and after the changepoint are independent and we derive an online algorithm for exact inference of the most recent changepoint. We compute the probability distribution of the length of the current “run,” or time since the last changepoint, using a simple message-passing algorithm. Our implementation is highly modular so that the algorithm may be applied to a variety of types of data. We illustrate this modularity by demonstrating the algorithm on three different real-world data sets.
Bang–Bang Control Class-D Amplifiers: Power-Supply Noise

In this paper, the bang-bang control class-D amplifiers (bang-bang amp) is suggested as an alternative to the incumbent pulsewidth-modulation class-D amp for low voltage power-critical applications, including hearing aids. The effects of power supply noise, qualified by power-supply rejection ratio (PSRR), on two bang-bang amps, bang-bang type-I and type-II, are investigated for low signal bandwidth hearing aid applications and for the usual full audio bandwidth applications. By deriving analytical expressions for PSRR of these amps, the important parameters related to PSRR are analyzed. The analyses are verified by means of HSPICE simulations and by measurements on practical circuits. The relationships derived herein provide good practical insight to the design of bang-bang amps, including how various parameters may be varied/optimized to meet a given PSRR specification.
Agent Behavior in the Sharing Economy : Evidence from Airbnb

One of the major differences between markets that follow a " sharing economy " paradigm and traditional two-sided markets is that, in the sharing economy, the supply side includes individual nonprofessional decision makers, in contrast to firms and professional agents. Using a data set of prices and availability of listings on Airbnb, we find that there exist substantial differences in the operational and financial performances between professional and nonprofessional hosts. In particular, properties managed by professional hosts earn 16.9% more in daily revenue, have 15.5% higher occupancy rates, and are 13.6% less likely to exit the market compared with properties owned by nonprofessional hosts, even after controlling for property and market characteristics. We demonstrate that these performance discrepancies between professionals and nonprofessionals can be partly explained by pricing inefficiencies. Specifically, we provide empirical evidence that nonprofessional hosts are less likely to offer different rates across stay dates based on the underlying demand, such as major holidays and conventions. We develop a parsimonious model to analyze the implications of having two such different host groups for a profit-maximizing platform operator and for a social planner. While a profit-maximizing platform operator should charge lower prices to nonprofessional hosts, a social planner would charge the same prices to professionals and nonprofessionals.
Scopes Too Flexible...and Too Stiff

The article investigates how the difficulties caused by the flexibility of the endoscope shaft could be solved and to provide a categorized overview of designs that potentially provide a solution. The following are discussed: paradoxical problem of flexible endoscopy; NOTES or hybrid endoscopy surgery; design challenges; shaft-guidance: guiding principles; virtual track guidance; physical track guidance; shaft-guidance: rigidity control; material stiffening; structural stiffening; and hybrid stiffening.
Design of radio-frequency powered coils for implant instruments

Radio frequency (r.f.) has been investigated as a means of externally powering miniature and long term implant telemetry systems. Optimum power transfer from the transmitter to the receiving coil is desired for total system efficiency. A seven step design procedure for the transmitting and receiving coils is described based on r.f., coil diameter, coil spacing, load and the number of turns of the coil. An inductance tapping circuit and a voltage doubler circuit have been built in accordance with the design procedure. Experimental results were within the desired total system efficiency ranges of 18% and 23%, respectively. On a étudié la fréquence radio (f.r.) en tant que source extérieure permettant de faire fonctionner les systèmes télémétriques d'implants miniatures à long terme. Afin d'assurer une efficacité totale au système, il est nécessaire d'obtenir un transfert de puissance optimum de l'émetteur à la bobine réceptrice. On donne la description d'une technique de conception en sept temps, fondée sur la fréquence radio, le diamètre de la bobine, l'espacement des spires, la charge et le nombre de tours de la bobine. Un circuit de captage de tension par induction et un circuit doubleur de tension ont été construits conformément à la méthode de conception. Les résultats expérimentaux étaient compris dans les limites d'efficacité totale souhaitable pour le système, soit 18% à 23%, respectivement. Hochfrequenz wurde als Mittel zur externen Energieversorgung von Miniatur und langfristigen Implantat-Telemetriesystemen untersucht. Zur Verwirklichung der höchsten Leistungsfähigkeit braucht das System optimale Energieübertragung von Sendegerät zu Empfangsspule. Ein auf Hochfrequenz beruhendes siebenstufiges Konstruktionssystem für Sende- und Empfangsspulen wird beschrieben, mit Hinweisen über Spulendurchmesser, Spulenanordnung, Ladung und die Anzahl der Wicklungen. Ein Induktionsanzapfstromkreis und ein Spannungsverdoppler wurden dem Konstruktionsverfahren entsprechend gebaut. Versuchsergebnisse lagen im Bereich des gewünschten Systemleistungsgrades von 18% und 23%.
A dynamic analysis of a latched CMOS comparator

In the implementation of high-performance CMOS over-sampling A/D converters, high-speed comparators are indispensable. This paper discusses the design and analysis of a low-power regenerative latched CMOS comparator, based on an analytical approach which gives a deeper insight into the associated trade-offs. Calculation details and simulation results for a 20 MHz clocked comparator in a 0.5/spl mu/m technology are presented.
Measuring Problematic Mobile Phone Use: Development and Preliminary Psychometric Properties of the PUMP Scale

This study aimed to develop and assess the psychometric properties of an English language measure of problematic mobile phone use. Participants were recruited from a university campus, health science center, and other public locations. The sample included 244 individuals (68.4% female) aged 18-75. Results supported a unidimensional factor structure for the 20-item self-report Problematic Use of Mobile Phones (PUMP) Scale. Internal consistency was excellent (α = 0.94). Strong correlations (r = .76, P < .001) were found between the PUMP Scale and an existing scale of cellular phone dependency that was validated in Asia, as well as items assessing frequency and intensity of mobile phone use. Results provide preliminary support for the use of the PUMP Scale to measure problematic use of mobile phones.
Modeling and Analysis of Synchronous Reluctance Machines With Circular Flux Barriers Through Conformal Mapping

Synchronous reluctance (SynRel) machines are gaining more and more importance in various fields of application thanks to their known merits like rugged construction, high efficiency, absence of field windings, and no or reduced need for permanent magnets. Out of the possible design variants, in this paper, SynRel motors with uniform mechanical air gap and circularly shaped flux barriers are considered and a conformal-mapping approach to their analytical modeling and simulation is proposed. A suitable conformal transformation is introduced to compute the reluctance of each rotor circularly shaped flux barrier and the result is then used to analytically determine the air-gap flux density distribution and the electromagnetic torque of the machine in arbitrary operating conditions. The accuracy of the methodology proposed is assessed against finite element analysis.
Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community

An online learning community enables learners to access up-to-date information via the Internet anytime–anywhere because of the ubiquity of the World Wide Web (WWW). Students can also interact with one another during the learning process. Hence, researchers want to determine whether such interaction produces learning synergy in an online learning community. In this paper, we take the Technology Acceptance Model as a foundation and extend the external variables as well as the Perceived Variables as our model and propose a number of hypotheses. A total of 436 Taiwanese senior high school students participated in this research, and the online learning community focused on learning English. The research results show that all the hypotheses are supported, which indicates that the extended variables can effectively predict whether users will adopt an online learning community. Finally, we discuss the implications of our findings for the future development of online English learning communities.