nils-herrmann/clean_scirepeval huggingface dataset:
An evaluation of an eye tracker as a device for computer input2

Since humans direct their visual attention by means of eye movements, a device which monitors eye movements should be a natural “pick” device for selecting objects visually present on a monitor. The results from an experimental investigation of an eye tracker as a computer input device are presented. Three different methods were used to select the object looked at; these were a button press, prolonged fixation or “dwell” and an on screen select button. The results show that an eye tracker can be used as a fast selection device providing that the target size is not too small. If the targets are small speed declines and errors increase rapidly.
A Review On Various Interference Effects In A MIMO-OFDM System

The performance of a MIMO-OFDM system is severely degraded in presence of RF impairments like phase noise and I/Q imbalance and other interferences like ICI (intercarrier interference) and NBI (narrowband interference). Low-complexity estimation and compensation techniques that can jointly remove the effect of these impairments are highly desirable. In this paper, we present a study of various interference effects in a MIMO-OFDM system and their compensation techniques.
High accuracy current measurement in the main power converters of the large hadron collider: tutorial 53

In the Large Hadron Collider (LHC) at CERN, the powering of the main dipole and quadrupole circuits is divided into eight separate powering sub sectors due to the very high magnetic energy stored in these circuits and to protection constraints of the superconducting magnets . As a consequence, individual sector currents must be controlled with very high accuracy in amplitude and time to ensure that the beam of particles sees the same magnetic field in all sectors. This results in a requirement for current tracking between the different sectors of better than ± 5 ppm and short term stability of better than ± 2 ppm [1], at 13 kA currents.
Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks

Automated melanoma recognition in dermoscopy images is a very challenging task due to the low contrast of skin lesions, the huge intraclass variation of melanomas, the high degree of visual similarity between melanoma and non-melanoma lesions, and the existence of many artifacts in the image. In order to meet these challenges, we propose a novel method for melanoma recognition by leveraging very deep convolutional neural networks (CNNs). Compared with existing methods employing either low-level hand-crafted features or CNNs with shallower architectures, our substantially deeper networks (more than 50 layers) can acquire richer and more discriminative features for more accurate recognition. To take full advantage of very deep networks, we propose a set of schemes to ensure effective training and learning under limited training data. First, we apply the residual learning to cope with the degradation and overfitting problems when a network goes deeper. This technique can ensure that our networks benefit from the performance gains achieved by increasing network depth. Then, we construct a fully convolutional residual network (FCRN) for accurate skin lesion segmentation, and further enhance its capability by incorporating a multi-scale contextual information integration scheme. Finally, we seamlessly integrate the proposed FCRN (for segmentation) and other very deep residual networks (for classification) to form a two-stage framework. This framework enables the classification network to extract more representative and specific features based on segmented results instead of the whole dermoscopy images, further alleviating the insufficiency of training data. The proposed framework is extensively evaluated on ISBI 2016 Skin Lesion Analysis Towards Melanoma Detection Challenge dataset. Experimental results demonstrate the significant performance gains of the proposed framework, ranking the first in classification and the second in segmentation among 25 teams and 28 teams, respectively. This study corroborates that very deep CNNs with effective training mechanisms can be employed to solve complicated medical image analysis tasks, even with limited training data.
Instant Ray Tracing: The Bounding Interval Hierarchy

We introduce a new ray tracing algorithm that exploits the best of previous methods: Similar to bounding volume hierarchies the memory of the acceleration data structure is linear in the number of objects to be ray traced and can be predicted prior to construction, while the traversal of the hierarchy is as efficient as the one of kd-trees. The construction algorithm can be considered a variant of quicksort and for the first time is based on a global space partitioning heuristic, which is much cheaper to evaluate than the classic surface area heuristic. Compared to spatial partitioning schemes only a fraction of the memory is used and a higher numerical precision is intrinsic. The new method is simple to implement and its high performance is demonstrated by extensive measurements including massive as well as dynamic scenes, where we focus on the total time to image including the construction cost rather than on only frames per second.
Partition Search Revisited

Partition search is a form of game search, proposed by Matthew L. Ginsberg in 1996, who wrote that the method “incorporates dependency analysis, allowing substantial reductions in the portion of the tree that needs to be expanded.” In this paper, some improvements of the partition search algorithm are proposed. The effectiveness of the most important extension we contribute, which we call local partition search, has been verified experimentally. The results obtained (which we present in the paper) show that using this extension, leads, in the case of bridge, to a significant reduction (almost by half) of the search tree size and calculation time. Another extension we proposed allows for more effective usage of the transposition table (using it to narrow the search window or by cutting more than one entry). Additionally, we contribute a formal proof of the correctness of all presented partition search variants. We draw conclusions from it about a possible generalization of partition search by making the definition of a partition system less restrictive. We also provide a formal definition of a partition system for the double dummy bridge.
Leveraging Augmented Reality Training Tool for Medical Education: a Case Study in Central Venous Catheterization

Central venous catheterization is a relatively common bedside medical procedure that involves the placement of a catheter into a patient»s internal jugular vein in order to administer medication or fluids. To learn this technique, medical students traditionally practice on training mannequins under the guidance of a clinical instructor. The objective of this project was to co-develop a standardized augmented reality solution for teaching medical students this procedure, which would enable them to practice independently and at their own pace. Following an iterative design and prototyping process, we compiled a comprehensive set of usability heuristics specific to augmented reality healthcare applications, used to identify unique usability issues associated with augmented reality software. This approach offers a better strategy to improve the usability of augmented reality system and increases the potential to standardize and render medical education more accessible. The benefits of applying augmented reality to simulated medical education come with heavy consequences in the event of poor learning outcomes. The usability of these systems is paramount to ensure the development of clinical competence is facilitated and not hindered.
Epidermal electronics: Skin sweat patch

An ultrathin, stretchable, and conformal sensor system for skin-mounted sweat measurement is characterized and demonstrated in this paper. As an epidermal device, the sweat sensor is mechanically designed for comfortable wear on the skin by employing interdigitated electrodes connected via stretchable serpentine-shaped conductors. Experimental results show that the sensor is sensitive to measuring frequency, sweat level and stretching deformation. It was found that 20kHz signals provide the most sensitive performance: electrical impedance changes 50% while sweat level increases from 20 to 80. In addition, sensor elongation from 15 up to 50% affected the measurement sensitivity of both electrical impedance and capacitance.
Topic Memory Networks for Short Text Classification

Many classification models work poorly on short texts due to data sparsity. To address this issue, we propose topic memory networks for short text classification with a novel topic memory mechanism to encode latent topic representations indicative of class labels. Different from most prior work that focuses on extending features with external knowledge or pre-trained topics, our model jointly explores topic inference and text classification with memory networks in an end-to-end manner. Experimental results on four benchmark datasets show that our model outperforms state-of-the-art models on short text classification, meanwhile generates coherent topics.
Controlling negative and positive power at the ankle with a soft exosuit

The soft exosuit is a new approach for applying assistive forces over the wearer's body through load paths configured by the textile architecture. In this paper, we present a body-worn lower-extremity soft exosuit and a new control approach that can independently control the level of assistance that is provided during negative- and positive-power periods at the ankle. The exosuit was designed to create load paths assisting ankle plantarflexion and hip flexion, and the actuation system transmits forces from the motors to the suit via Bowden cables. A load cell and two gyro sensors per leg are used to measure real-time data, and the controller performs position control of the cable on a step-by-step basis with respect to the power delivered to the wearer's ankle by controlling two force parameters, the pretension and the active force. Human subjects testing results demonstrate that the controller is capable of modulating the amount of power delivered to the ankle joint. Also, significant reductions in metabolic rate (11%-15%) were observed, which indicates the potential of the proposed control approach to provide benefit to the wearer during walking.
Information metrics (iMetrics): a research specialty with a socio-cognitive identity?

“Bibliometrics”, “scientometrics”, “informetrics”, and “webometrics” can all be considered as manifestations of a single research area with similar objectives and methods, which we call “information metrics” or iMetrics. This study explores the cognitive and social distinctness of iMetrics with respect to the general information science (IS), focusing on a core of researchers, shared vocabulary and literature/knowledge base. Our analysis investigates the similarities and differences between four document sets. The document sets are drawn from three core journals for iMetrics research (Scientometrics, . We split JASIST into document sets containing iMetrics and general IS articles. The volume of publications in this representation of the specialty has increased rapidly during the last decade. A core of researchers that predominantly focus on iMetrics topics can thus be identified. This core group has developed a shared vocabulary as exhibited in high similarity of title words and one that shares a knowledge base. The research front of this field moves faster than the research front of information science in general, bringing it closer to Price’s dream.
The big data analytics and applications of the surveillance system using video structured description technology

Recently, the video data has very huge volume, taking one city for example, thousands of cameras are built of which each collects high-definition video over 24–48 GB every day with the rapidly growth; secondly, data collected includes variety of formats involving multimedia, images and other unstructured data; furthermore the valuable information contains in only a few frames called key frames of massive video data; and the last problem caused is how to improve the processing velocity of a large amount of original video with computers, so as to enhance the crime prediction and detection effectiveness of police and users. In this paper, we conclude a novel architecture for next generation public security system, and the “front + back” pattern is adopted to address the problems brought by the redundant construction of current public security information systems which realizes the resource consolidation of multiple IT resources, and provides unified computing and storage environment for more complex data analysis and applications such as data mining and semantic reasoning. Under the architecture, we introduce cloud computing technologies such as distributed storage and computing, data retrieval of huge and heterogeneous data, provide multiple optimized strategies to enhance the utilization of resources and efficiency of tasks. This paper also presents a novel strategy to generate a super-resolution image via multi-stage dictionaries which are trained by a cascade training process. Extensive experiments on image super-resolution validate that the proposed solution can get much better results than some state-of-the-arts ones.
Low-power hardware design for the HEVC Binary Arithmetic Encoder targeting 8K videos

The HEVC (High Efficiency Video Coding) has risen as the state-of-the-art video coding standard, targeting the processing of high quality video. As one of its main components, the entropy encoding is based on the CABAC (Context-adaptive binary arithmetic coding) algorithm, which allows parallelization at higher video data representation (i.e. slices, tiles, and wavefront parallel processing) whereas posing serious challenges for low-level parallelization. Low-power dissipation is a sough-after goal for hardware video encoder designs, along with high performance. This work presents a hardware architecture for the sub-module BAE (Binary Arithmetic Encoder) of the CABAC, featuring low power techniques, such as clock gating and operand isolation. The techniques were inserted after a careful analysis, based on the statistical behavior of CABAC inputs for real video sequences. A 4-cores BAE core structure was implemented in order to provide high performance. As results, power reduction ranging 25-40% was achieved by applying the aforementioned techniques in specific parts of the architecture, while still accomplishing the requirements for UHD 8K real-time processing.
Resource Allocation Optimization for Device-to-Device Communication Underlaying Cellular Networks

Device-to-Device (D2D) communication will become an important technology in future networks with the increase of the requirements of local communication services. The interference between cellular communication and D2D communication can be coordinated by proper power control and resource allocation. In this paper, we analyze the resource allocation methods for D2D communication underlaying cellular networks. A novel resource allocation method that D2D can reuse the resources of more than one cellular user is proposed. After that, we discuss the selection of the optimal resource allocation method from the proposed method and the conventional methods. Finally, the performance of different methods is evaluated through numerical simulation. The simulation results show that the proposed method is the optimal resource allocation method when the D2D pair locates at the most part of the cell area in both uplink and downlink. The proposed method can improve the sum throughput of cellular communication and D2D communication significantly.
A Sub-1V 32nA Process, Voltage and Temperature Invariant Voltage Reference Circuit

This paper presents a novel process, voltage and temperature (PVT) invariant voltage reference generator using subthreshold MOSFETS. The proposed circuit uses weighted average of PTAT and CTAT voltages at zero temperature co-efficient point. The proposed circuit has been designed and optimized in 180nm mixed-mode CMOS technology. Simulation results show that the output voltage of the proposed voltage reference generator varies by only ± 0.85% across process corners and temperature range of 0°C to 100°C. Temperature and power supply sensitivity of the reference voltage is 135ppm/°C and 0.54%/V, respectively. The proposed circuit consumes only 19 nW DC power and operates at supply voltages as low as 600 mV.
High Efficient Interleaved Multi-channel dc/dc Converter Dedicated to Mobile Applications

In the transportation field, the empty weight of the vehicle has to be as light as possible in order to have the highest energetic efficiency. For onboard storage electrical systems, DC/DC converters are usually used to control the power flows in the vehicle. This paper focuses on two different DC/DC converter applications: high current/low voltage on the one hand and low current/high voltage on the other hand. For all power mobile applications, a standard dc/dc converter is not realizable due to mass and volume constraints. As the inductor is usually the biggest and heaviest component in the system, it is important to develop a new structure allowing the reduction of its size and weight. The chosen technology is based on interleaved channels operating in discontinuous mode, also using reverse conduction of power MOSFET transistors. For both of the cases described above, a prototype has been built composed of 8 and 4 channels respectively. The first converter is used for power assistance (250 A/18 V) using the MOS reverse conduction property. In this particular case, efficiency is up to 96.3 %. The second is developed for a mobile solar application (3.8 A/270 V). Efficiencies are up to 98.4 %
Surgical navigation by autostereoscopic image overlay of integral videography

This paper describes an autostereoscopic image overlay technique that is integrated into a surgical navigation system to superimpose a real three-dimensional (3-D) image onto the patient via a half-silvered mirror. The images are created by employing a modified version of integral videography (IV), which is an animated extension of integral photography. IV records and reproduces 3-D images using a microconvex lens array and flat display; it can display geometrically accurate 3-D autostereoscopic images and reproduce motion parallax without the need for special devices. The use of semitransparent display devices makes it appear that the 3-D image is inside the patient's body. This is the first report of applying an autostereoscopic display with an image overlay system in surgical navigation. Experiments demonstrated that the fast IV rendering technique and patient-image registration method produce an average registration accuracy of 1.13 mm. Experiments using a target in phantom agar showed that the system can guide a needle toward a target with an average error of 2.6 mm. Improvement in the quality of the IV display will make this system practical and its use will increase surgical accuracy and reduce invasiveness.
A Review of the Status of Brain Structure Research in Transsexualism

The present review focuses on the brain structure of male-to-female (MtF) and female-to-male (FtM) homosexual transsexuals before and after cross-sex hormone treatment as shown by in vivo neuroimaging techniques. Cortical thickness and diffusion tensor imaging studies suggest that the brain of MtFs presents complex mixtures of masculine, feminine, and demasculinized regions, while FtMs show feminine, masculine, and defeminized regions. Consequently, the specific brain phenotypes proposed for MtFs and FtMs differ from those of both heterosexual males and females. These phenotypes have theoretical implications for brain intersexuality, asymmetry, and body perception in transsexuals as well as for Blanchard's hypothesis on sexual orientation in homosexual MtFs. Falling within the aegis of the neurohormonal theory of sex differences, we hypothesize that cortical differences between homosexual MtFs and FtMs and male and female controls are due to differently timed cortical thinning in different regions for each group. Cross-sex hormone studies have reported marked effects of the treatment on MtF and FtM brains. Their results are used to discuss the early postmortem histological studies of the MtF brain.
Light fidelity (LI-FI) based indoor communication system

Indoor wireless communication is an essential part of next generation wireless communication system.For an indoor communication number of users and their device are increasing very rapidly so as a result capacity of frequency spectrum to accommodate further users in future is limited and also it would be difficult for service providers to provide more user reliable and high speed communication so this short come can be solve in future by using Li-Fi based indoor communication system. Li-Fi which is an emerging branch of optical wireless communication can be useful in future as a replacement and backup of Wireless Fidelity (Wi-Fi)for indoor communication because it can provide high data rate of transmission along with high capacity to utilize more users as its spectrum bandwidth is much broader than the radio spectrum. In this paper we will look at the different aspects of the Li-Fi based indoor communication system,summarizes some of the research conducted so far andwe will also proposed a Li-Fi based communication model keeping in mind coverage area for multiple user and evaluate its performance under different scenarios .
Diffusion maps for high-dimensional single-cell analysis of differentiation data

Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages.



Here, we propose the use of diffusion maps to deal with the problem of defining differentiation trajectories. We adapt this method to single-cell data by adequate choice of kernel width and inclusion of uncertainties or missing measurement values, which enables the establishment of a pseudotemporal ordering of single cells in a high-dimensional gene expression space. We expect this output to reflect cell differentiation trajectories, where the data originates from intrinsic diffusion-like dynamics. Starting from a pluripotent stage, cells move smoothly within the transcriptional landscape towards more differentiated states with some stochasticity along their path. We demonstrate the robustness of our method with respect to extrinsic noise (e.g. measurement noise) and sampling density heterogeneities on simulated toy data as well as two single-cell quantitative polymerase chain reaction datasets (i.e. mouse haematopoietic stem cells and mouse embryonic stem cells) and an RNA-Seq data of human pre-implantation embryos. We show that diffusion maps perform considerably better than Principal Component Analysis and are advantageous over other techniques for non-linear dimension reduction such as t-distributed Stochastic Neighbour Embedding for preserving the global structures and pseudotemporal ordering of cells.



The Matlab implementation of diffusion maps for single-cell data is available at https://www.helmholtz-muenchen.de/icb/single-cell-diffusion-map.



fbuettner.phys@gmail.com, fabian.theis@helmholtz-muenchen.de



Supplementary data are available at Bioinformatics online.