nils-herrmann/clean_scirepeval huggingface dataset:
Dead time optimization through loss analysis of an active-clamp flyback converter utilizing GaN devices

This paper presents an analysis of losses that occur during dead time in an active-clamp flyback converter utilizing Gallium Nitride based MOSFETs. This analysis is used to optimize the length of the dead-time period in order to minimize losses in the switching devices. When compared to silicon-based MOSFETs, GaN-based MOSFETs have lower switching losses and much higher reverse conduction losses, so it is not desirable to design for zero-voltage switching (ZVS) over a wide load range. The analysis presented in this paper finds an optimal trade-off between partial ZVS and reverse conduction losses, minimizing overall device switching losses and therefore increasing converter efficiency over the desired load range. A 15-W, four-output active-clamp flyback converter utilizing GaN devices at 1 MHz is designed and implemented using the recommended optimization. The experimental results confirm this analysis and result in a minimization of switching losses and an increase in converter efficiency.
Personal Navi: Benefits of an Augmented Reality Navigational Aid Using a See-Thru 3D Volumetric HUD

Augmented reality (AR) is an interface that can potentially provide more intuitive and immersive experiences, particularly for automotive applications. In this paper we present the Personal Navi, a vehicular AR navigational aid designed for use with a see-thru 3D volumetric Head Up Display (HUD). In one study, we found that the Personal Navi visuals helped participants recognize turn locations earlier than when provided with conventional navigation aids alone. The interface also helped keep users' eyes up and fixated on the driving environment more. In a second study, we tested participants' depth perception of AR visuals provided with our prototype 3D-HUD. We displayed the same visuals with a fixed focal depth display (2D-HUD) and found that for applications such as Personal Navi, where the spatial location of AR visuals are an important component of the interface, a dynamically adjustable focal plane (3D-HUD) is necessary for proper registration. We argue that AR-based HUD navigational aids should be implemented only with 3D-HUDs because of inferior depth perception with 2D-HUDs.
Investigation of Using High Impedance Surfaces for Wide-Angle Scanning Arrays

In this paper, an eight-element linear array is proposed and experimentally studied to illustrate the potential of using high impedance surfaces (HISs) for wide-angle scanning applications. An HIS-based horizontal wire antenna with a broadbeam radiation pattern is implemented as the individual radiating elements of the proposed array. The working mechanism of the HIS-based array is investigated as well. The rectangular-mushroom HIS, operating in surface-wave band, contributes to the broad-beam radiation of the individual antenna element as well as the wide scan performance of the array. Measured results show that with uniform magnitude and progressive phase excitation, the array performs a wide scan angle up to 85° in the elevation plane and a realized gain varying from 13.1 to 10.1 dBi. Meanwhile, the side lobe levels (SLLs) are generally less than -10 dB over the entire scan region. Good agreement is obtained between the measurements and the simulations.
The cognitive neuroscience of creativity.

This article outlines a framework of creativity based on functional neuroanatomy. Recent advances in the field of cognitive neuroscience have identified distinct brain circuits that are involved in specific higher brain functions. To date, these findings have not been applied to research on creativity. It is proposed that there are four basic types of creative insights, each mediated by a distinctive neural circuit. By definition, creative insights occur in consciousness. Given the view that the working memory buffer of the prefrontal cortex holds the content of consciousness, each of the four distinctive neural loops terminates there. When creativity is the result of deliberate control, as opposed to spontaneous generation, the prefrontal cortex also instigates the creative process. Both processing modes, deliberate and spontaneous, can guide neural computation in structures that contribute emotional content and in structures that provide cognitive analysis, yielding the four basic types of creativity. Supportive evidence from psychological, cognitive, and neuroscientific studies is presented and integrated in this article. The new theoretical framework systematizes the interaction between knowledge and creative thinking, and how the nature of this relationship changes as a function of domain and age. Implications for the arts and sciences are briefly discussed.
The Composition of Hemp Seed Oil and Its Potential as an Important Source of Nutrition

The fatty acid and natural product content of hemp seed oil was analyzed by GC-MS and LC-MS. The presence of linoleic acid (LA) and -linolenic acid (LNA) were confirmed in their previously reported ratio of 3:1 LA:LNA. The presence of -caryophyllene (740 mg/L), myrcene (160 mg/L), -sitosterol (100-148 g/L) and trace amounts of methyl salicylate was observed in the oil which had not been previously reported. Trace amounts of cannabidiol (CBD) were also detected. Bioassays were performed with the oil to determine its effectiveness as an antimicrobial agent. Some bioactivity was observed during the primary screening.
Local force cues for strength and stability in a distributed robotic construction system

Construction of spatially extended, self-supporting structures requires a consideration of structural stability throughout the building sequence. For collective construction systems, where independent agents act with variable order and timing under decentralized control, ensuring stability is a particularly pronounced challenge. Previous research in this area has largely neglected considering stability during the building process. Physical forces present throughout a structure may be usable as a cue to inform agent actions as well as an indirect communication mechanism (stigmergy) to coordinate their behavior, as adding material leads to redistribution of forces which then informs the addition of further material. Here we consider in simulation a system of decentralized climbing robots capable of traversing and extending a two-dimensional truss structure, and explore the use of feedback based on force sensing as a way for the swarm to anticipate and prevent structural failures. We consider a scenario in which robots are tasked with building an unsupported cantilever across a gap, as for a bridge, where the goal is for the swarm to build any stable spanning structure rather than to construct a specific predetermined blueprint. We show that access to local force measurements enables robots to build cantilevers that span significantly farther than those built by robots without access to such information. This improvement is achieved by taking measures to maintain both strength and stability, where strength is ensured by paying attention to forces during locomotion to prevent joints from breaking, and stability is maintained by looking at how loads transfer to the ground to ensure against toppling. We show that swarms that take both kinds of forces into account have improved building performance, in both structured settings with flat ground and unpredictable environments with rough terrain.
Scalable matrix inversion using MapReduce

Matrix operations are a fundamental building block of many computational tasks in fields as diverse as scientific computing, machine learning, and data mining. Matrix inversion is an important matrix operation, but it is difficult to implement in today's popular parallel dataflow programming systems, such as MapReduce. The reason is that each element in the inverse of a matrix depends on multiple elements in the input matrix, so the computation is not easily partitionable. In this paper, we present a scalable and efficient technique for matrix inversion in MapReduce. Our technique relies on computing the LU decomposition of the input matrix and using that decomposition to compute the required matrix inverse. We present a technique for computing the LU decomposition and the matrix inverse using a pipeline of MapReduce jobs. We also present optimizations of this technique in the context of Hadoop. To the best of our knowledge, our technique is the first matrix inversion technique using MapReduce. We show experimentally that our technique has good scalability, enabling us to invert a 10^5 x 10^5 matrix in 5 hours on Amazon EC2. We also show that our technique outperforms ScaLAPACK, a state-of-the-art linear algebra package that uses MPI.
On human-aware task and motion planning abilities for a teammate robot

Human-robot collaboration requires to equip the robot with explicit reasoning on the human and on its own capabilities to achieve its tasks in a collaborative way with a human partner. This paper presents and discusses three humanaware planners which can provide to a teammate robot the ability to asynthesize pertinent and acceptable behaviour in an industrial context. The illustrative context is inspired by a realistic project to involve collaborative mobile manipulators in the assembly of some components of the Ariane launcher.
Driving automation : Learning from aviation about design philosophies

Whether we like it or not, automation is gradually taking over the driver’s role. Full vehicle automation is predicted to be on British roads by 2030 (Walker et al., 2001). However, experience in aviation gives us some cause for concern for the ‘drive-by-wire’ car (Stanton & Marsden, 1996). Problems of workload and situation awareness have been attributed as the root cause of some aircraft accidents (Beaty, 1995). These problems may be approached in two different ways, depending on the level of automation used. These two philosophies are exemplified by the positions of the two major aircraft manufacturers. Airbus use a ‘hard protection’ system in their A320 and A340 series, employing automation to prevent error, and hence it can override the pilot. Boeing, on the other hand, opted for ‘soft protection’ in their 777 aircraft, using automation as a tool to aid pilots, and not giving it the authority to override pilot control (Hughes & Dornheim, 1995). This paper speculates whether hard or soft automation provides the best solution for road vehicles, and considers an alternative design philosophy in vehicles of the future based on coordination and cooperation.
Principal direction analysis-based real-time 3D human pose reconstruction from a single depth image

Human pose estimation in real-time is a challenging problem in computer vision. In this paper, we present a novel approach to recover a 3D human pose in real-time from a single depth human silhouette using Principal Direction Analysis (PDA) on each recognized body part. In our work, the human body parts are first recognized from a depth human body silhouette via the trained Random Forests (RFs). On each recognized body part which is presented as a set of 3D points cloud, PDA is applied to estimate the principal direction of the body part. Finally, a 3D human pose gets recovered by mapping the principal directional vector to each body part of a 3D human body model which is created with a set of super-quadrics linked by the kinematic chains. In our experiments, we have performed quantitative and qualitative evaluations of the proposed 3D human pose reconstruction methodology. Our evaluation results show that the proposed approach performs reliably on a sequence of unconstrained poses and achieves an average reconstruction error of 7.46 degree in a few key joint angles. Our 3D pose recovery methodology should be applicable to many areas such as human computer interactions and human activity recognition.
The Neural Career of Sensory-motor Metaphors

The role of sensory-motor systems in conceptual understanding has been controversial. It has been proposed that many abstract concepts are understood metaphorically through concrete sensory-motor domains such as actions. Using fMRI, we compared neural responses with literal action (Lit; The daughter grasped the flowers), metaphoric action (Met; The public grasped the idea), and abstract (Abs; The public understood the idea) sentences of varying familiarity. Both Lit and Met sentences activated the left anterior inferior parietal lobule, an area involved in action planning, with Met sentences also activating a homologous area in the right hemisphere, relative to Abs sentences. Both Met and Abs sentences activated the left superior temporal regions associated with abstract language. Importantly, activation in primary motor and biological motion perception regions was inversely correlated with Lit and Met familiarity. These results support the view that the understanding of metaphoric action retains a link to sensory-motor systems involved in action performance. However, the involvement of sensory-motor systems in metaphor understanding changes through a gradual abstraction process whereby relatively detailed simulations are used for understanding unfamiliar metaphors, and these simulations become less detailed and involve only secondary motor regions as familiarity increases. Consistent with these data, we propose that anterior inferior parietal lobule serves as an interface between sensory-motor and conceptual systems and plays an important role in both domains. The similarity of abstract and metaphoric sentences in the activation of left superior temporal regions suggests that action metaphor understanding is not completely based on sensory-motor simulations but relies also on abstract lexical-semantic codes.
Semantic similarity based evaluation for C programs through the use of symbolic execution

Automatic grading of programs has existed in various fields for many years ago. Within this paper, we propose a method for evaluating C programs. Two approaches are distinguished in this context: static and dynamic analysis methods. Unlike the dynamic analysis that requires an executable program to be evaluated, static analysis could evaluate a program even if it is not totally correct. The proposed method is based on static analysis of programs. It consists of comparing the evaluated program with the evaluator-provided program through their Control Flow Graphs. Here, the great challenge is to deal with the multiplicity of solutions that exists for the same programming problem. As a solution to this weakness, we propose an innovative similarity measure that compares two programs according to their semantic executions. In fact, the evaluated program is compared to the evaluator-provided program called model program by using the symbolic execution technique. The experimentations presented in this work are performed by using a basic implementation of the proposed method. The obtained results reveal a promising realization in the field of automated evaluation of programs. They also show that the proposed method guarantees a considerable approximation to the human program evaluation.
Scalable Edge Computing for Low Latency Data Dissemination in Topic-Based Publish/Subscribe

Advances in Internet of Things (IoT) give rise to a variety of latency-sensitive, closed-loop applications that reside at the edge. These applications often involve a large number of sensors that generate volumes of data, which must be processed and disseminated in real-time to potentially a large number of entities for actuation, thereby forming a closed-loop, publish-process-subscribe system. To meet the response time requirements of such applications, this paper presents techniques to realize a scalable, fog/edge-based broker architecture that balances data publication and processing loads for topic-based, publish-process-subscribe systems operating at the edge, and assures the Quality-of-Service (QoS), specified as the 90th percentile latency, on a per-topic basis. The key contributions include: (a) a sensitivity analysis to understand the impact of features such as publishing rate, number of subscribers, per-sample processing interval and background load on a topic's performance; (b) a latency prediction model for a set of co-located topics, which is then used for the latency-aware placement of topics on brokers; and (c) an optimization problem formulation for k-topic co-location to minimize the number of brokers while meeting each topic's QoS requirement. Here, k denotes the maximum number of topics that can be placed on a broker. We show that the problem is NP-hard for k >=3 and present three load balancing heuristics. Empirical results are presented to validate the latency prediction model and to evaluate the performance of the proposed heuristics.
of Analytical Chemistry Wearable and Implantable Sensors for Biomedical Applications Hatice

Mobile health technologies offer great promise for reducing healthcare costs and improving patient care. Wearable and implantable technologies are contributing to a transformation in the mobile health era in terms of improving healthcare and health outcomes and providing real-time guidance on improved health management and tracking. In this article, we review the biomedical applications of wearable and implantable medical devices and sensors, ranging from monitoring to prevention of diseases, as well as the materials used in the fabrication of these devices and the standards for wireless medical devices and mobile applications. We conclude by discussing some of the technical challenges in wearable and implantable technology and possible solutions for overcoming these difficulties.
Quality Metrics in optical modulation analysis: EVM and its relation to Q-factor, OSNR, and BER

The quality of optical signals is a very important parameter in optical communications. Several metrics are in common use, like optical signal-to-noise power ratio (OSNR), Q-factor, error vector magnitude (EVM) and bit error ratio (BER). A measured raw BER is not necessarily useful to predict the final BER after soft-decision forward error correction (FEC), if the statistics of the noise leading to errors is unknown. In this respect the EVM is superior, as it allows an estimation of the error statistics. We compare various metrics analytically, by simulation, and through experiments. We employ six quadrature amplitude modulation (QAM) formats at symbol rates of 20 GBd and 25 GBd. The signals were generated by a software-defined transmitter. We conclude that for optical channels with additive Gaussian noise the EVM metric is a reliable quality measure. For nondata-aided QAM reception, BER in the range 10-6...10-2 can be reliably estimated from measured EVM.
Redirected Walking in Place

This paper describes a method for allowing people to virtually move around a CAVETM without ever having to turn to face the missing back wall. We describe the method, and report a pilot study of 28 participants, half of whom moved through the virtual world using a hand-held controller, and the other half used the new technique called ‘Redirected Walking in Place’ (RWP). The results show that the current instantiation of the RWP technique does not result in a lower frequency of looking towards the missing wall. However, the results also show that the sense of presence in the virtual environment is significantly and negatively correlated with the amount that the back wall is seen. There is evidence that RWP does reduce the chance of seeing the blank wall for some participants. The increased sense of presence through never having to face the blank wall, and the results of this pilot study show the RWP has promise and merits further development.
The human connectome: Origins and challenges

The human connectome refers to a map of the brain's structural connections, rendered as a connection matrix or network. This article attempts to trace some of the historical origins of the connectome, in the process clarifying its definition and scope, as well as its putative role in illuminating brain function. Current efforts to map the connectome face a number of significant challenges, including the issue of capturing network connectivity across multiple spatial scales, accounting for individual variability and structural plasticity, as well as clarifying the role of the connectome in shaping brain dynamics. Throughout, the article argues that these challenges require the development of new approaches for the statistical analysis and computational modeling of brain network data, and greater collaboration across disciplinary boundaries, especially with researchers in complex systems and network science.
Combating VR sickness through subtle dynamic field-of-view modification

Virtual Reality (VR) sickness can cause intense discomfort, shorten the duration of a VR experience, and create an aversion to further use of VR. High-quality tracking systems can minimize the mismatch between a user's visual perception of the virtual environment (VE) and the response of their vestibular system, diminishing VR sickness for moving users. However, this does not help users who do not or cannot move physically the way they move virtually, because of preference or physical limitations such as a disability. It has been noted that decreasing field of view (FOV) tends to decrease VR sickness, though at the expense of sense of presence. To address this tradeoff, we explore the effect of dynamically, yet subtly, changing a physically stationary person's FOV in response to visually perceived motion as they virtually traverse a VE. We report the results of a two-session, multi-day study with 30 participants. Each participant was seated in a stationary chair, wearing a stereoscopic head-worn display, and used control and FOV-modifying conditions in the same VE. Our data suggests that by strategically and automatically manipulating FOV during a VR session, we can reduce the degree of VR sickness perceived by participants and help them adapt to VR, without decreasing their subjective level of presence, and minimizing their awareness of the intervention.
How games for computing education are evaluated? A systematic literature review

Educational games are assumed to be an effective an d efficient instructional strategy for computing education. However, it is essential to sy stematically evaluate such games in order to obtain sound evidence of their impact. Thu s, the objective of this article is to present the state of the art on how games for compu ting education are evaluated. Therefore, we performed a systematic literature rev iew of a sample of 3,617 articles from which 112 relevant articles have been identified, d escribing 117 studies on the evaluation of games for computing education. Based on these st udies we analyzed how evaluations are defined (the analysis factors evaluated, resear ch designs, evaluation models/methods used, kind of data collection instruments, etc.), h ow they have been executed (sample size and replications) and analyzed (data analysis metho ds used). As a result, we can confirm that most evaluations use a simple research design in which, typically, the game is used and afterwards subjective feedback is collected via questionnaires from the learners. The majority of the evaluations are run with small samp les, without replication, using mostly qualitative methods for data analysis. We also obse rved that most studies do not use a welldefined evaluation model or method. This shows that ere is a need for more rigorous evaluations as well as methodological support in or der to assist game creators and instructors to improve such games as well as to sys tematically support decisions on when or how to include them within instructional units.