nils-herrmann/clean_scirepeval huggingface dataset:
Autonomous Driving System Design for Formula Student Driverless Racecar

This paper summarizes the work of building the autonomous system including detection system and path tracking controller for a formula student autonomous racecar. A LIDAR-vision cooperating method of detecting traffic cone which is used as track mark is proposed. Detection algorithm of the racecar also implements a precise and high rate localization method which combines the GPS-INS data and LIDAR odometry. Besides, a track map including the location and color information of the cones is built simultaneously. Finally, the system and vehicle performance on a closed loop track is tested. This paper also briefly introduces the Formula Student Autonomous Competition (FSAC) in 2017.
Low-Cost Circularly Polarized Origami Antenna

In this letter, we present a novel circularly polarized (CP) origami antenna. We fold paper in the form of an origami tetrahedron to serve as the substrate of the antenna. The antenna comprises two triangular monopole elements that are perpendicular to each other. Circular polarization characteristics are achieved by exciting both elements with equal magnitudes and with a phase difference of 90°. In this letter, we explain the origami folding steps in detail. We also verify the proposed concept of the CP origami antenna by performing simulations and measurements using a fabricated prototype. The antenna exhibits a 10-dB impedance bandwidth of 70.2% (2.4–5 GHz), and a 3-dB axial-ratio bandwidth of 8% (3.415–3.7 GHz). The measured left-hand circular polarization gain of the antenna is in the range of 5.2–5.7 dBi for the 3-dB axial-ratio bandwidth.
Automatic Categorization of Privacy Policies: A Pilot Study

Privacy policies are a nearly ubiquitous feature of websites and online services, and the contents of such policies are legally binding for users. However, the obtuse language and sheer length of most privacy policies tend to discourage users from reading them. We describe a pilot experiment to use automatic text categorization to answer simple categorical questions about privacy policies, as a first step toward developing automated or semi-automated methods to retrieve salient features from these policies. Our results tentatively demonstrate the feasibility of this approach for answering selected questions about privacy policies, suggesting that further work toward user-oriented analysis of these policies could be fruitful.
WRPN: Wide Reduced-Precision Networks

For computer vision applications, prior works have shown the efficacy of reducing numeric precision of model parameters (network weights) in deep neural networks. Activation maps, however, occupy a large memory footprint during both the training and inference step when using mini-batches of inputs. One way to reduce this large memory footprint is to reduce the precision of activations. However, past works have shown that reducing the precision of activations hurts model accuracy. We study schemes to train networks from scratch using reduced-precision activations without hurting accuracy. We reduce the precision of activation maps (along with model parameters) and increase the number of filter maps in a layer, and find that this scheme matches or surpasses the accuracy of the baseline full-precision network. As a result, one can significantly improve the execution efficiency (e.g. reduce dynamic memory footprint, memory bandwidth and computational energy) and speed up the training and inference process with appropriate hardware support. We call our scheme WRPN wide reduced-precision networks. We report results and show that WRPN scheme is better than previously reported accuracies on ILSVRC-12 dataset while being computationally less expensive compared to previously reported reduced-precision networks.
Cellular engineering for therapeutic protein production: product quality, host modification, and process improvement.

Recombinant proteins offer many therapeutic advantages unavailable in traditional small molecule drugs, but the need for cellular versus chemical synthesis complicates production. Avenues for producing therapeutic biologics are continuously expanding, and developments in biochemistry, cell biology, and bioengineering fuel new discoveries that promise safer, more efficient, and cheaper drugs for consumers. Numerous approaches to express recombinant proteins exist, but Escherichia coli, Saccharomyces cerevisiae, and mammalian systems (e.g. Chinese hamster ovary cells, CHO) are the most widely utilized. Improvements to production in these hosts have focused on novel expression cassettes, cell line modifications, engineering secretion pathways, and media design. Here, we describe recent developments for improving protein production in E. coli, S. cerevisiae, and CHO systems and compare recent advancements to previous knowledge in the field. With the expanding importance and prevalence of protein therapeutics, these improvements will serve as the framework for future discoveries.
Few-shot Learning of Homogeneous Human Locomotion Styles

Using neural networks for learning motion controllers from motion capture data is becoming popular due to the natural and smooth motions they can produce, the wide range of movements they can learn and their compactness once they are trained. Despite these advantages, these systems require large amounts of motion capture data for each new character or style of motion to be generated, and systems have to undergo lengthy retraining, and often reengineering, to get acceptable results. This can make the use of these systems impractical for animators and designers and solving this issue is an open and rather unexplored problem in computer graphics. In this paper we propose a transfer learning approach for adapting a learned neural network to characters that move in different styles from those on which the original neural network is trained. Given a pretrained character controller in the form of a Phase-Functioned Neural Network for locomotion, our system can quickly adapt the locomotion to novel styles using only a short motion clip as an example. We introduce a canonical polyadic tensor decomposition to reduce the amount of parameters required for learning from each new style, which both reduces the memory burden at runtime and facilitates learning from smaller quantities of data. We show that our system is suitable for learning stylized motions with few clips of motion data and synthesizing smooth motions in real-time. CCS Concepts •Computing methodologies → Animation; Neural networks; Motion capture;
Ultra low-voltage, rail-to-rail input/output stage Operational Transconductance Amplifier (OTA) with high linearity and its application in a Gm-C filter

This paper presents an ultra low-voltage, rail-to-rail input/output stage Operational Transconductance Amplifier (OTA) which uses quasi floating gate input transistors. This OTA works with ±0.3v and consumes 57µw. It has near zero variation in small/large-signal behavior (i.e. transconductance and slew rate) in whole range of the common mode voltage of input signals. Using source degeneration technique for linearity improvement, make it possible to obtain −42.7 dB, HD3 for 0.6vP-P sine wave input signal with the frequency of 1MHz. The used feedback amplifier in input stage also enhances common mode rejection ratio (CMRR), such that in DC, CMRR is 146 dB. OTA is used for implementation of a wide-tunable third-order elliptic filter with 237 KHz–2.18 MHz cutoff frequencies. Proposed OTA and filter have been simulated in 0.18µm TSMC CMOS technology with Hspice.
Separation of Speech by Computational Auditory Scene Analysis

The term auditory scene analysis (ASA) refers to the ability of human listeners to form perceptual representations of the constituent sources in an acoustic mixture, as in the well-known ‘cocktail party’ effect. Accordingly, computational auditory scene analysis (CASA) is the field of study which attempts to replicate ASA in machines. Some CASA systems are closely modelled on the known stages of auditory processing, whereas others adopt a more functional approach. However, all are broadly based on the principles underlying the perception and organisation of sound by human listeners, and in this respect they differ from ICA and other approaches to sound separation. In this paper, we review the principles underlying ASA and show how they can be implemented in CASA systems. We also consider the link between CASA and automatic speech recognition, and draw distinctions between the CASA and ICA approaches.
Functional Encryption: Definitions and Challenges

We initiate the formal study of functional encryption by giving precise definitions of the concept and its security. Roughly speaking, functional encryption supports restricted secret keys that enable a key holder to learn a specific function of encrypted data, but learn nothing else about the data. For example, given an encrypted program the secret key may enable the key holder to learn the output of the program on a specific input without learning anything else about the program. We show that defining security for functional encryption is non-trivial. First, we show that a natural game-based definition is inadequate for some functionalities. We then present a natural simulation-based definition and show that it (provably) cannot be satisfied in the standard model, but can be satisfied in the random oracle model. We show how to map many existing concepts to our formalization of functional encryption and conclude with several interesting open problems in this young area. ∗Supported by NSF, MURI, and the Packard foundation. †Supported by NSF CNS-0716199, CNS-0915361, and CNS-0952692, Air Force Office of Scientific Research (AFO SR) under the MURI award for “Collaborative policies and assured information sharing” (Project PRESIDIO), Department of Homeland Security Grant 2006-CS-001-000001-02 (subaward 641), and the Alfred P. Sloan Foundation.
Analysing e-mail text authorship for forensic purposes

E-mail has become the most popular Internet application and with its rise in use has come an inevitable increase in the use of e-mail for criminal purposes. It is possible for an e-mail message to be sent anonymously or through spoof ed servers. Computer forensics analysts need a tool that can be used to identify th e author of such e-mail messages. This thesis describes the development of such a tool using te chniques from the fields of stylometry and machine learning. An author’s style can be reduced to a pattern by making measurements of various stylometric feat ur s from the text. E-mail messages also contain macro-structural features that can b e measured. These features together can be used with the Support Vector Machine learnin g algorithm to classify or attribute authorship of e-mail messages to an author prov iding a suitable sample of messages is available for comparison. In an investigation, the set of authors may need to be reduced from an initial large list of possible suspects. This research has trialled autho rship characterisation based on sociolinguistic cohorts, such as gender and language bac kground, as a technique for profiling the anonymous message so that the suspect list can b e reduced.
TIMERS: Error-Bounded SVD Restart on Dynamic Networks

Singular Value Decomposition (SVD) is a popular approach in various network applications, such as link prediction and network parameter characterization. Incremental SVD approaches are proposed to process newly changed nodes and edges in dynamic networks. However, incremental SVD approaches suffer from serious error accumulation inevitably due to approximation on incremental updates. SVD restart is an effective approach to reset the aggregated error, but when to restart SVD for dynamic networks is not addressed in literature. In this paper, we propose TIMERS, Theoretically Instructed Maximum-Error-bounded Restart of SVD, a novel approach which optimally sets the restart time in order to reduce error accumulation in time. Specifically, we monitor the margin between reconstruction loss of incremental updates and the minimum loss in SVD model. To reduce the complexity of monitoring, we theoretically develop a lower bound of SVD minimum loss for dynamic networks and use the bound to replace the minimum loss in monitoring. By setting a maximum tolerated error as a threshold, we can trigger SVD restart automatically when the margin exceeds this threshold. We prove that the time complexity of our method is linear with respect to the number of local dynamic changes, and our method is general across different types of dynamic networks. We conduct extensive experiments on several synthetic and real dynamic networks. The experimental results demonstrate that our proposed method significantly outperforms the existing methods by reducing 27% to 42% in terms of the maximum error for dynamic network reconstruction when fixing the number of restarts. Our method reduces the number of restarts by 25% to 50% when fixing the maximum error tolerated.
AlphaGomoku: An AlphaGo-based Gomoku Artificial Intelligence using Curriculum Learning

In this project, we combine AlphaGo algorithm with Curriculum Learning to crack the game of Gomoku. Modifications like Double Networks Mechanism and Winning Value Decay are implemented to solve the intrinsic asymmetry and short-sight of Gomoku. Our final AI AlphaGomoku, through two days’ training on a single GPU, has reached humans’ playing level.
Benefits of Information Visualization Systems for Administrative Data Analysts

This paper reports results from a study on the adoption of an information visualization system by administrative data analysts. Despite the fact that the system was neither fully integrated with their current software tools nor with their existing data analysis practices, analysts identified a number of key benefits that visualization systems provide to their work. These benefits for the most part occurred when analysts went beyond their habitual and well-mastered data analysis routines and engaged in creative discovery processes. We analyze the conditions under which these benefits arose, to inform the design of visualization systems that can better assist the work of administrative data analysts.
Constructing places from spatial footprints

Place is an essential concept in human discourse. It is people's interaction and experience with their surroundings that identify place from non-place in space. This paper explores the use of spatial footprints as a record of human interaction with the environment. Specifically, we use geotagged photos collected in Flickr to provide a collective view of sense of place, in terms of significance and location. Spatial footprints associated with photographs can not only describe individual place locations and spatial extents but also the relationship between places, such as hierarchy. This type of information about place may be utilized to study the way people understand their landscape, or can be incorporated into existing gazetteers for geographic information retrieval and location-based services. Other sources of user-generated geographic information, such as Foursquare and Twitter, may also be harvested and aggregated to study place in a similar way.
Implementation of an incampus fire alarm system using ZigBee

Nearly all our buildings and workspaces are protected against fire breaks, which may occur due to some fault in the electric circuitries and power sources. The immediate alarming and aid to extinguish the fire in such situations of fire breaks are provided using embedded systems installed in the buildings. But as the area being monitored against such fire threats becomes vast, these systems do not provide a centralized solution. For the protection of such a huge area, like a college campus or an industrial park, a centralized wireless fire control system using Wireless sensor network technology is developed. The system developed connects the five dangers prone zones of the campus with a central control room through a ZigBee communication interface such that in case of any fire break in any of the building, a direct communication channel is developed that will send an immediate signal to the control room. In case if any of the emergency zone lies out of reach of the central node, multi hoping technique is adopted for the effective transmitting of the signal. The five nodes maintains a wireless interlink among themselves as well as with the central node for this purpose. Moreover a hooter is attached along with these nodes to notify the occurrence of any fire break such that the persons can leave the building immediately and with the help of the signal received in the control room, the exact building where the fire break occurred is identified and fire extinguishing is done. The real time system developed is implemented in Atmega32 with temperature, fire and humidity sensors and ZigBee module.
Integrating MPI with Docker for HPC

Container technology has the potential to considerably simplify the management of the software stack of High Performance Computing (HPC) clusters. However, poor integration with established HPC technologies is still preventing users and administrators to reap the benefits of containers. Message Passing Interface (MPI) is a pervasive technology used to run scientific software, often written in Fortran and C/C++, that presents challenges for effective integration with containers. This work shows how an existing MPI implementation can be extended to improve this integration.
Neuroanatomical correlates of phonological processing of Chinese characters and alphabetic words: a meta-analysis.

We used the activation likelihood estimation (ALE) method to quantitatively synthesize data from 19 published brain mapping studies of phonological processing in reading, six with Chinese and 13 with alphabetic languages. It demonstrated high concordance of cortical activity across multiple studies in each written language system as well as significant differences of activation likelihood between languages. Four neural systems for the phonological processing of Chinese characters included: (1) a left dorsal lateral frontal system at Brodmann area (BA) 9; (2) the dorsal aspect of left inferior parietal system; (3) a bilateral ventral-occipitotemporal system including portions of fusiform gyrus and middle occipital gyrus; and (4) a left ventral prefrontal system covering the superior aspect of inferior frontal gyrus. For phonological processing of written alphabetic words, cortical areas identified here are consistent with the three neural systems proposed previously in the literature: (1) a ventral prefrontal system involving superior portions of left inferior frontal gyrus; (2) a left dorsal temporoparietal system including mid-superior temporal gyri and the ventral aspect of inferior parietal cortex (supramarginal region); and (3) a left ventral occipitotemporal system. Contributions of each of these systems to phonological processing in reading were discussed, and a covariant learning hypothesis is offered to account for the findings that left middle frontal gyrus is responsible for addressed phonology in Chinese whereas left temporoparietal regions mediate assembled phonology in alphabetic languages. Language form, cognitive process, and learning strategy drive the development of functional neuroanatomy.
Low-profile wideband high gain ME dipole antenna with SIW side walls surrounding

This paper introduces a simple method to improve the radiation pattern of the low profile magneto-electric (ME) dipole antenna by adding a substrate integrated waveguide (SIW) side-walls structure around. Compared with the original ME dipole antenna, gain enhancement of about 3dB on average is achieved without deteriorating the impedance bandwidth. The antenna operates at 15GHz with 63.3% -10dB impedance bandwidth from 10.8GHz to 18.4GHz and the gain is 12.3dBi at 17GHz on a substrate with fixed thickness of 3mm (0.15λ0) and aperture of 35mm×35mm (1.75λ0). This antenna is a good choice in the wireless communication application for its advantages of low-profile, wide bandwidth, high gain and low cost fabrication.
Toward a definition of competency-based education in medicine: a systematic review of published definitions.

Competency-based education (CBE) has emerged in the health professions to address criticisms of contemporary approaches to training. However, the literature has no clear, widely accepted definition of CBE that furthers innovation, debate, and scholarship in this area.



To systematically review CBE-related literature in order to identify key terms and constructs to inform the development of a useful working definition of CBE for medical education.



We searched electronic databases and supplemented searches by using authors' files, checking reference lists, contacting relevant organizations and conducting Internet searches. Screening was carried out by duplicate assessment, and disagreements were resolved by consensus. We included any English- or French-language sources that defined competency-based education. Data were analyzed qualitatively and summarized descriptively.



We identified 15,956 records for initial relevancy screening by title and abstract. The full text of 1,826 records was then retrieved and assessed further for relevance. A total of 173 records were analyzed. We identified 4 major themes (organizing framework, rationale, contrast with time, and implementing CBE) and 6 sub-themes (outcomes defined, curriculum of competencies, demonstrable, assessment, learner-centred and societal needs). From these themes, a new definition of CBE was synthesized.



This is the first comprehensive systematic review of the medical education literature related to CBE definitions. The themes and definition identified should be considered by educators to advance the field.
Package Design : Colour Harmony and Consumer Expectations

Colour plays an important role in design. It is a trigger to arouse viewers’ emotions and a carrier that designers use to deliver information. Colours that are viewed together and produce pleasing affective responses are considered to be in harmony (Burchett, 2002). In product design, it has been suggested that positive emotion would not only add extra value to a product but can further increase the possibility of a product being purchased (Cho & Lee, 2005; Desmet, Overbeeke, & Tax, 2001; Jordan, 1998). Therefore, when designing products, designers endeavour to establish emotional connections among ideas, products, services and brands (Crossley, 2003). Using harmonic colours is one way to create positive emotional connections. Most of the extant colour harmony principles found in art or design textbooks are based on well-controlled, simple, uniform colours. How well these principles are applicable to contexts that are more representative of real design situations is largely unknown. The context within which colours are used also affects how colours are perceived. For instance, the colour brown may associate with natural and warm feelings when involving wooden materials in interior design. However, the same colour may associate with different feelings such as elegant and dignified when used for a coat. More examples can be seen in a recent study examining the affective responses for 2-dimensional coloured shapes and 3-dimensional objects (Lee, Luo, & Ou, 2009). Therefore, if we are to examine how the use of colours might associate with different psychological responses or encourage positive emotions with the goal of obtaining information useful for future applications in product design, a pre-selected context (e.g., wooden products or clothes) should be used consistently for all the colours examined.