nils-herrmann/clean_scirepeval huggingface dataset:
Point Cloud Skeletons via Laplacian Based Contraction

We present an algorithm for curve skeleton extraction via Laplacian-based contraction. Our algorithm can be applied to surfaces with boundaries, polygon soups, and point clouds. We develop a contraction operation that is designed to work on generalized discrete geometry data, particularly point clouds, via local Delaunay triangulation and topological thinning. Our approach is robust to noise and can handle moderate amounts of missing data, allowing skeleton-based manipulation of point clouds without explicit surface reconstruction. By avoiding explicit reconstruction, we are able to perform skeleton-driven topology repair of acquired point clouds in the presence of large amounts of missing data. In such cases, automatic surface reconstruction schemes tend to produce incorrect surface topology. We show that the curve skeletons we extract provide an intuitive and easy-to-manipulate structure for effective topology modification, leading to more faithful surface reconstruction.
Axial Flux Resolver Design Techniques for Minimizing Position Error Due to Static Eccentricities

This paper proposes a design solution for static eccentricity (SE) in axial flux resolvers (AFRs). There are two definitions for SE in AFRs. The first approach is based on the definition of SE in conventional radial flux resolvers, wherein the rotor axis does not coincide with the stator bore, but the rotor rotates around its own shaft. In other words, it is different in the angular inclination of the rotor and stator axis. Thus, the air gap of the motor is not uniform. In the second approach, which is more common in AFRs, when SE occurs, air-gap length remains uniform. Rotor axis remains parallel with the stator axis, although it does not coincide with the stator bore. This means that there is radial misalignment of the rotor and stator axis. In this paper, both definitions are considered, and an innovative design solution is proposed to decrease the effect of both types of SE in the accuracy of detected position. 3-D time stepping finite-element analysis is used to show the success of proposed designs. Finally, both models were evaluated using experimental results.
Practical memory checking with Dr. Memory

Memory corruption, reading uninitialized memory, using freed memory, and other memory-related errors are among the most difficult programming bugs to identify and fix due to the delay and non-determinism linking the error to an observable symptom. Dedicated memory checking tools are invaluable for finding these errors. However, such tools are difficult to build, and because they must monitor all memory accesses by the application, they incur significant overhead. Accuracy is another challenge: memory errors are not always straightforward to identify, and numerous false positive error reports can make a tool unusable. A third obstacle to creating such a tool is that it depends on low-level operating system and architectural details, making it difficult to port to other platforms and difficult to target proprietary systems like Windows. This paper presents Dr. Memory, a memory checking tool that operates on both Windows and Linux applications. Dr. Memory handles the complex and not fully documented Windows environment, and avoids reporting false positive memory leaks that plague traditional leak locating algorithms. Dr. Memory employs efficient instrumentation techniques; a direct comparison with the state-of-the-art Valgrind Memcheck tool reveals that Dr. Memory is twice as fast as Memcheck on average and up to four times faster on individual benchmarks.
Vector boosting for rotation invariant multi-view face detection

In this paper, we propose a novel tree-structured multiview face detector (MVFD), which adopts the coarse-to-fine strategy to divide the entire face space into smaller and smaller subspaces. For this purpose, a newly extended boosting algorithm named vector boosting is developed to train the predictors for the branching nodes of the tree that have multicomponents outputs as vectors. Our MVFD covers a large range of the face space, say, +/-45/spl deg/ rotation in plane (RIP) and +/-90/spl deg/ rotation off plane (ROP), and achieves high accuracy and amazing speed (about 40 ms per frame on a 320 /spl times/ 240 video sequence) compared with previous published works. As a result, by simply rotating the detector 90/spl deg/, 180/spl deg/ and 270/spl deg/, a rotation invariant (360/spl deg/ RIP) MVFD is implemented that achieves real time performance (11 fps on a 320 /spl times/ 240 video sequence) with high accuracy.
Simulating gait assistance of a hip exoskeleton: Case studies for ankle pathologies

We propose a simulation framework for gait assistance with ankle pathologies. We first construct the neu-romuscular walking model, then design the parameters for assistance torques for stance and swing legs. The parameter values are determined by performing dynamic optimizations which takes into account the human-exoskeleton interactive dynamics. The simulated energy expenditure and kinematic data are compared with the real data. Case studies involve abnormal gaits with 1) foot drop, 2) foot drop and plantarflexion failure. We evaluate the gait efficiency and walking speed for the different gait types. Our result shows that each gait type should have a different assistance strategy (timing and magnitude) compared to the assistance strategy of a normal gait.
Improving Deep Neural Network Based Speech Enhancement in Low SNR Environments

We propose a joint framework combining speech enhancement (SE) and voice activity detection (VAD) to increase the speech intelligibility in low signal-noise-ratio (SNR) environments. Deep Neural Networks (DNN) have recently been successfully adopted as a regression model in SE. Nonetheless, the performance in harsh environments is not always satisfactory because the noise energy is often dominating in certain speech segments causing speech distortion. Based on the analysis of SNR information at the frame level in the training set, our approach consists of two steps, namely: (1) a DNN-based VAD model is trained to generate frame-level speech/non-speech probabilities; and (2) the final enhanced speech features are obtained by a weighted sum of the estimated clean speech features processed by incorporating VAD information. Experimental results demonstrate that the proposed SE approach effectively improves short-time objective intelligibility (STOI) by 0.161 and perceptual evaluation of speech quality (PESQ) by 0.333 over the already-good SE baseline systems at -5dB SNR of babble noise.
Pain mechanisms: a new theory.

The nature of pain has been the subject of bitter controversy since the turn of the century (1). There are currently two opposing theories of pain: (i) specificity theory, which holds that pain is a specific modality like vision or hearing, "with its own central and peripheral apparatus" (2), and (ii) pattern theory, which maintains that the nerve impulse pattern for pain is produced by intense stimulation of nonspecific receptors since "there are no specific fibers and no specific endings" (3). Both theories derive from earlier concepts proposed by von Frey (4) and Goldscheider (5) in 1894, and historically they are held to be mutually exclusive. Since it is our purpose here to propose a new theory of pain mechanisms, we shall state explicitly at the outset where we agree and disagree with specificity and pattern theories.
A novel feeding technique for antipodal linearly tapered slot antenna array

A novel feeding system using substrate integrated waveguide (SIW) technique for antipodal linearly tapered slot array antenna (ALTSA) is presented in this paper. After making studies by simulations for a SIW fed ALTSA cell, a 1/spl times/8 ALTSA array fed by SIW feeding system at X-band is fabricated and measured, and the measured results show that this array antenna has a wide bandwidth and good performances.
Data extraction from web pages based on structural-semantic entropy

Most of today's web content is designed for human consumption, which makes it difficult for software tools to access them readily. Even web content that is automatically generated from back-end databases is usually presented without the original structural information. In this paper, we present an automated information extraction algorithm that can extract the relevant attribute-value pairs from product descriptions across different sites. A notion, called structural-semantic entropy, is used to locate the data of interest on web pages, which measures the density of occurrence of relevant information on the DOM tree representation of web pages. Our approach is less labor-intensive and insensitive to changes in web-page format. Experimental results on a large number of real-life web page collections are encouraging and confirm the feasibility of the approach, which has been successfully applied to detect false drug advertisements on the web due to its capacity in associating the attributes of records with their respective values.
Social cognitive theory: an agentic perspective.

The capacity to exercise control over the nature and quality of one's life is the essence of humanness. Human agency is characterized by a number of core features that operate through phenomenal and functional consciousness. These include the temporal extension of agency through intentionality and forethought, self-regulation by self-reactive influence, and self-reflectiveness about one's capabilities, quality of functioning, and the meaning and purpose of one's life pursuits. Personal agency operates within a broad network of sociostructural influences. In these agentic transactions, people are producers as well as products of social systems. Social cognitive theory distinguishes among three modes of agency: direct personal agency, proxy agency that relies on others to act on one's behest to secure desired outcomes, and collective agency exercised through socially coordinative and interdependent effort. Growing transnational embeddedness and interdependence are placing a premium on collective efficacy to exercise control over personal destinies and national life.
Simulink Based Hardware-in-the-Loop Simulator for Rapid Prototyping of UAV Control Algorithms

This paper describes a recently developed architecture for a Hardware-in-the-Loop simulator for Unmanned Aerial Vehicles. The principal idea is to use the advanced modeling capabilities of Simulink rather than hard-coded software as the flight dynamics simulating engine. By harnessing Simulink’s ability to precisely model virtually any dynamical system or phenomena this newly developed simulator facilitates the development, validation and verification steps of flight control algorithms. Although the presented architecture is used in conjunction with a particular commercial autopilot, the same approach can be easily implemented on a flight platform with a different autopilot. The paper shows the implementation of the flight modeling simulation component in Simulink supported with an interfacing software to a commercial autopilot. This offers the academic community numerous advantages for hardware-in-the-loop simulation of flight dynamics and control tasks. The developed setup has been rigorously tested under a wide variety of conditions. Results from hardware-in-the-loop and real flight tests are presented and compared to validate its adequacy and assess its usefulness as a rapid prototyping tool.
Synchronous Programming of Reactive Systems

The te rm "reactive system" was introduced by David Harel and Amir Pnueli [HP85], and is now commonly accepted to designate permanent ly operating systems, and to distinguish them from "trans]ormational systems" i.e, usual programs whose role is to terminate with a result, computed from an initial da ta (e.g., a compiler). In synchronous programming, we understand it in a more restrictive way, distinguishing between "interactive" and "reactive" systems: Interactive systems permanent ly communicate with their environment, but at their own speed. They are able to synchronize with their environment, i.e., making it wait. Concurrent processes considered in operat ing systems or in data-base management , are generally interactive. Reactive systems, in our meaning, have to react to an environment which cannot wait. Typical examples appear when the environment is a physical process. The specific features of reactive systems have been pointed out many times [Ha193,BCG88,Ber89]:
Detecting deception in reputation management

We previously developed a social mechanism for distributed reputation management, in which an agent combines testimonies from several witnesses to determine its ratings of another agent. However, that approach does not fully protect against spurious ratings generated by malicious agents. This paper focuses on the problem of deception in testimony propagation and aggregation. We introduce some models of deception and study how to efficiently detect deceptive agents following those models. Our approach involves a novel application of the well-known weighted majority technique to belief function and their aggregation. We describe simulation experiments to study the number of apparently accurate witnesses found in different settings, the number of witnesses on prediction accuracy, and the evolution of trust networks.
Mutual occlusion between real and virtual elements in Augmented Reality based on fiducial markers

Augmented Reality (AR) systems which use optical tracking with fiducial marker for registration have had an important role in popularizing this technology, since only a personal computer with a conventional webcam is required. However, in most these applications, the virtual elements are shown only in the foreground a real element does not occlude a virtual one. The method presented enables AR environments based on fiducial markers to support mutual occlusion between a real element and many virtual ones, according to the elements position (depth) in the environment.
Greenhouse Monitoring with Wireless Sensor Network

In modern greenhouses, several measurement points are required to trace down the local climate parameters in different parts of the big greenhouse to make the greenhouse automation system work properly. Cabling would make the measurement system expensive and vulnerable. Moreover, the cabled measurement points are difficult to relocate once they are installed. Thus, a wireless sensor network (WSN) consisting of small-size wireless sensor nodes equipped with radio and one or several sensors, is an attractive and cost-efficient option to build the required measurement system. In this work, we developed a wireless sensor node for greenhouse monitoring by integrating a sensor platform provided by sensinode Ltd.  with three commercial sensors capable to measure four climate variables. The feasibility of the developed node was tested by deploying a simple sensor network into Martens Greenhouse Research Foundation's greenhouse in Narpio town in Western Finland. During a one day experiment, we collected data to evaluate the network reliability and its ability to detect the microclimate layers, which typically exist in the greenhouse between lower and upper flora. We were also able to show that the network can detect the local differences in the greenhouse climate caused by various disturbances, such as direct sunshine near the greenhouse walls. This article is our first step in the area of greenhouse monitoring and control, and it is all about the developed sensor network feasibility and reliability.
Adapting Open Information Extraction to Domain-Specific Relations

dent processes and domain-specific knowledge. Until recently, information extraction has leaned heavily on domain knowledge, which requires either manual engineering or manual tagging of examples (Miller et al. 1998; Soderland 1999; Culotta, McCallum, and Betz 2006). Semisupervised approaches (Riloff and Jones 1999, Agichtein and Gravano 2000, Rosenfeld and Feldman 2007) require only a small amount of hand-annotated training, but require this for every relation of interest. This still presents a knowledge engineering bottleneck, when one considers the unbounded number of relations in a diverse corpus such as the web. Shinyama and Sekine (2006) explored unsupervised relation discovery using a clustering algorithm with good precision, but limited scalability. The KnowItAll research group is a pioneer of a new paradigm, Open IE (Banko et al. 2007, Banko and Etzioni 2008), that operates in a totally domain-independent manner and at web scale. An Open IE system makes a single pass over its corpus and extracts a diverse set of relational tuples without requiring any relation-specific human input. Open IE is ideally suited to corpora such as the web, where the target relations are not known in advance and their number is massive.
Survey Of Music Information Needs, Uses, And Seeking Behaviours: Preliminary Findings

User studies focusing upon real-life music information needs, uses and seeking behaviours are still very scarce in the music information retrieval (MIR) and music digital library (MDL) fields. We are conducting a multigroup survey in an attempt to acquire information that can help eradicate false assumptions in designing MIR systems. Our goal is to provide an empirical basis for MIR/MDL system development. In this paper, we present our preliminary findings and analyses based on the 427 user responses we have received to date. Two major themes have been uncovered thus far that could have a significant influence the future development of successful MIR/MDL systems. First, people display “public information-seeking” behaviours by making use of collective knowledge and/or opinions of others about music such as reviews, ratings, recommendations, etc. in their music information-seeking. Second, respondents expressed needs for contextual metadata in addition to traditional bibliographic metadata.
Proofs of ownership in remote storage systems

Cloud storage systems are becoming increasingly popular. A promising technology that keeps their cost down is deduplication, which stores only a single copy of repeating data. Client-side deduplication attempts to identify deduplication opportunities already at the client and save the bandwidth of uploading copies of existing files to the server. In this work we identify attacks that exploit client-side deduplication, allowing an attacker to gain access to arbitrary-size files of other users based on a very small hash signatures of these files. More specifically, an attacker who knows the hash signature of a file can convince the storage service that it owns that file, hence the server lets the attacker download the entire file. (In parallel to our work, a subset of these attacks were recently introduced in the wild with respect to the Dropbox file synchronization service.) To overcome such attacks, we introduce the notion of proofs-of-ownership (PoWs), which lets a client efficiently prove to a server that that the client holds a file, rather than just some short information about it. We formalize the concept of proof-of-ownership, under rigorous security definitions, and rigorous efficiency requirements of Petabyte scale storage systems. We then present solutions based on Merkle trees and specific encodings, and analyze their security. We implemented one variant of the scheme. Our performance measurements indicate that the scheme incurs only a small overhead compared to naive client-side deduplication.
Hardware accelerated ambient occlusion techniques on GPUs

We introduce a visually pleasant ambient occlusion approximation running on real-time graphics hardware. Our method is a multi-pass algorithm that separates the ambient occlusion problem into high-frequency, detailed ambient occlusion and low-frequency, distant ambient occlusion domains, both capable of running independently and in parallel. The high-frequency detailed approach uses an image-space method to approximate the ambient occlusion due to nearby occluders caused by high surface detail. The low-frequency approach uses the intrinsic properties of a modern GPU to greatly reduce the search area for large and distant occluders with the help of a low-detail approximated version of the occluder geometry. Our method utilizes the highly parallel, stream processors (GPUs) to perform real-time visually pleasant ambient occlusion. We show that our ambient occlusion approximation works on a wide variety of applications such as molecular data visualization, dynamic deformable animated models, highly detailed geometry. Our algorithm demonstrates scalability and is well-suited for the current and upcoming graphics hardware.
Exploiting Local and Global Social Context for Recommendation

With the fast development of social media, the information overload problem becomes increasingly severe and recommender systems play an important role in helping online users find relevant information by suggesting information of potential interests. Social activities for online users produce abundant social relations. Social relations provide an independent source for recommendation, presenting both opportunities and challenges for traditional recommender systems. Users are likely to seek suggestions from both their local friends and users with high global reputations, motivating us to exploit social relations from local and global perspectives for online recommender systems in this paper. We develop approaches to capture local and global social relations, and propose a novel framework LOCABAL taking advantage of both local and global social context for recommendation. Empirical results on real-world datasets demonstrate the effectiveness of our proposed framework and further experiments are conducted to understand how local and global social context work for the proposed framework.
The most highly cited Library and Information Science articles: Interdisciplinarity, first authors and citation patterns

Highly cited articles are interesting because of the potential association between high citation counts and high quality research. This study investigates the 82 most highly cited Information Science and Library Science’ (IS&LS) articles (the top 0.1%) in the Web of Science from the perspectives of disciplinarity, annual citation patterns, and first author citation profiles. First, the relative frequency of these 82 articles was much lower for articles solely in IS&LS than for those in IS&LS and at least one other subject, suggesting that that the promotion of interdisciplinary research in IS&LS may be conducive to improving research quality. Second, two thirds of the first authors had an h-index in IS&LS of less than eight, show that much significant research is produced by researchers without a high overall IS&LS research productivity. Third, there is a moderate correlation (0.46) between citation ranking and the number of years between peak year and year of publication. This indicates that high quality ideas and methods in IS&LS often are deployed many years after being published.
A Linear GaN High Power Amplifier MMIC for Ka-Band Satellite Communications

A linear high power amplifier (HPA) monolithic microwave integrated circuit (MMIC) is designed with 0.15 μm gallium nitride (GaN) high electron mobility transistor (HEMT) technology on silicon carbide (SiC) substrate. To keep the linear characteristics of the power stage, 2:4:8 staging ratio of 8 × 50 μm unit transistor is adapted for the 3-stage HPA MMIC. The MMIC delivers P3 dB of 39.5 dBm with a PAE of 35% at 21.5 GHz. Linear output power (PL) meeting IMD3 of -25 dBc is 37.3 dBm with an associated PAE of 29.5%. The MMIC dimensions are 3.4 mm × 2.5 mm, generating an output power density of 1049 mW/mm2.