nils-herrmann/clean_scirepeval huggingface dataset:
Erratum to: Eye–hand coordination in a sequential target contact task

Most object manipulation tasks involve a series of actions demarcated by mechanical contact events, and gaze is typically directed to the locations of these events as the task unfolds. Here, we examined the timing of gaze shifts relative to hand movements in a task in which participants used a handle to contact sequentially five virtual objects located in a horizontal plane. This task was performed both with and without visual feedback of the handle position. We were primarily interested in whether gaze shifts, which in our task shifted from a given object to the next about 100 ms after contact, were predictive or triggered by tactile feedback related to contact. To examine this issue, we included occasional catch contacts where forces simulating contact between the handle and object were removed. In most cases, removing force did not alter the timing of gaze shifts irrespective of whether or not vision of handle position was present. However, in about 30% of the catch contacts, gaze shifts were delayed. This percentage corresponded to the fraction of contacts with force feedback in which gaze shifted more than 130 ms after contact. We conclude that gaze shifts are predictively controlled but timed so that the hand actions around the time of contact are captured in central vision. Furthermore, a mismatch between the expected and actual tactile information related to the contact can lead to a reorganization of gaze behavior for gaze shifts executed greater than 130 ms after a contact event.
Teaching Virtualization by Building a Hypervisor

Virtual machines (VMs) are an increasingly ubiquitous feature of modern computing, yet the interested student or professional has limited resources to learn how VMs work. In particular, there is a lack of "hands-on" exercises in constructing a virtual machine monitor (VMM, or hypervisor), which are both simple enough to understand completely but realistic enough to capture the practical challenges in using this technology. This paper describes a set of assignments to extend a small, pedagogical operating system (OS) to form a hypervisor and host itself. This pedagogical hypervisor, called HOSS, adds roughly 1,000 lines of code to the MIT JOS source, and includes a set of guided exercises. Initial results with HOSS in an upper-level virtualization course indicate that students enjoyed the assignments and were able to apply what they learned to solve different virtualization-related problems. HOSS is publicly available.
An integrated 122GHz differential frequency doubler with 37GHz bandwidth in 130 nm SiGe BiCMOS technology

This paper describes an integrated frequency multiplier, implemented as a Gilbert cell based frequency doubler in a 130 nm SiGe BiCMOS technology. The circuit demonstrates a 3 dB bandwidth of 97–134GHz with peak output power of 1 dBm for 1 dBm input power. The fundamental suppression, measured at the single-ended output, is better than 21 dBc while the frequency doubler consumes 69mW from a 3.3V supply. The doubler is preceded by a differential amplifier functioning as an active balun to generate a differential signal for the Gilbert cell.
Improving OCR performance with background image elimination

One critical procedure in OCR is to detect text characters from a document image. However, some documents might come with embedded background images which often mislead the algorithms of character detection. For example, small dots or sharp edges from the background image are often bound-boxed as characters and passed to the next stage of the OCR pipeline, which causes an error chain. Motivated by this observation, we present a novel and cost-effective image preprocessing method to accomplish the task. We first enhance the document images before OCR by utilizing the brightness and chromaticity as contrast parameters. Then we convert color images to gray and threshold it. This way, background images can be removed effectively without losing the quality of text characters. The method was tested using Tesseract (an open source OCR engine) and compared with two commercial OCR software ABBYY Finereader and HANWANG (OCR software for Chinese characters). The experimental results show that the recognition accuracies are improved significantly after removing background images.
Spatio-temporal avalanche forecasting with Support Vector Machines

This paper explores the use of the Support Vector Machine (SVM) as a data exploration tool and a predictive engine for spatio-temporal forecasting of snow avalanches. Based on the historical observations of avalanche activity, meteorological conditions and snowpack observations in the field, an SVM is used to build a data-driven spatio-temporal forecast for the local mountain region. It incorporates the outputs of simple physics-based and statistical approaches used to interpolate meteorological and snowpack-related data over a digital elevation model of the region. The interpretation of the produced forecast is discussed, and the quality of the model is validated using observations and avalanche bulletins of the recent years. The insight into the model behaviour is presented to highlight the interpretability of the model, its abilities to produce reliable forecasts for individual avalanche paths and sensitivity to input data. Estimates of prediction uncertainty are obtained with ensemble forecasting. The case study was carried out using data from the avalanche forecasting service in the Locaber region of Scotland, where avalanches are forecast on a daily basis during the winter months.  Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-52743 Published Version Originally published at: Pozdnoukhov, Alexei; Matasci, Giona; Kanevski, Mikhail; Purves, Ross S (2011). Spatio-temporal avalanche forecasting with support vector machines. Natural Hazards and Earth System Sciences, 11(2):367-382.  2011
iSpot analysed: participatory learning and reputation

We present an analysis of activity on iSpot, a website supporting participatory learning about wildlife through social networking. A sophisticated and novel reputation system provides feedback on the scientific expertise of users, allowing users to track their own learning and that of others, in an informal learning context. We find steeply unequal long-tail distributions of activity, characteristic of social networks, and evidence of the reputation system functioning to amplify the contribution of accredited experts. We argue that there is considerable potential to apply such a reputation system in other participatory learning contexts.
The diverse CB1 and CB2 receptor pharmacology of three plant cannabinoids: delta9-tetrahydrocannabinol, cannabidiol and delta9-tetrahydrocannabivarin.

Cannabis sativa is the source of a unique set of compounds known collectively as plant cannabinoids or phytocannabinoids. This review focuses on the manner with which three of these compounds, (-)-trans-delta9-tetrahydrocannabinol (delta9-THC), (-)-cannabidiol (CBD) and (-)-trans-delta9-tetrahydrocannabivarin (delta9-THCV), interact with cannabinoid CB1 and CB2 receptors. Delta9-THC, the main psychotropic constituent of cannabis, is a CB1 and CB2 receptor partial agonist and in line with classical pharmacology, the responses it elicits appear to be strongly influenced both by the expression level and signalling efficiency of cannabinoid receptors and by ongoing endogenous cannabinoid release. CBD displays unexpectedly high potency as an antagonist of CB1/CB2 receptor agonists in CB1- and CB2-expressing cells or tissues, the manner with which it interacts with CB2 receptors providing a possible explanation for its ability to inhibit evoked immune cell migration. Delta9-THCV behaves as a potent CB2 receptor partial agonist in vitro. In contrast, it antagonizes cannabinoid receptor agonists in CB1-expressing tissues. This it does with relatively high potency and in a manner that is both tissue and ligand dependent. Delta9-THCV also interacts with CB1 receptors when administered in vivo, behaving either as a CB1 antagonist or, at higher doses, as a CB1 receptor agonist. Brief mention is also made in this review, first of the production by delta9-THC of pharmacodynamic tolerance, second of current knowledge about the extent to which delta9-THC, CBD and delta9-THCV interact with pharmacological targets other than CB1 or CB2 receptors, and third of actual and potential therapeutic applications for each of these cannabinoids.
Autonomia: an autonomic computing environment

The prolifeation of Internet technologies, services and devices, have made the current networked system designs, and management tools incapable of designing reliable, secure networked systems and services. In fact, we have reached a level of complexity, heterogeneity, and a rapid change rate that our information infiastructure is becoming unmanageable and insecure. This had led researchers to consider alternative designs and management techniques that are based on strategies used by biological systems to deal with complexity, heterogeneity and uncertainty. The approach is referred to as autonomic computing. An autonomic computing system is the system that has the capabilities of being sevdefining, self-healing, self-configwing, self-optimizing, etc. In this paper, we present our approach to implement an autonomic computing infastructure, Autonomia that provides dynamically programmable control and management services to support the development and deployment of smart (intelligent) applications. The A UTONOMIA environment provides the application developers with all the tools required to specifj, the appropriate control and management schemes to maintain any quality of service requirement or application attribute/firnctionality (e.g., perjormance, fault, security, etc.) and the core autonomic middleware services to maintain the autonomic requirements of a wide range of network applications and services. We have successfully implemented a proof-of-concept prototype system that can support the self-configuring, self-deploying and selfhealing of any networked application.
How Does He Saw Me ? A Recommendation Engine for Picking Heroes in Dota 2

In this paper, we present a hero recommendation engine for the popular computer game Dota 2. We detail previous efforts at hero recommendation, building on these to provide a more complete exploration of machine learning algorithms applied to this problem. In addition to discussing the details behind the machine learning algorithms we use, we also provide insight into our method of data collection and feature selection. In doing so, the outcome of our efforts is two-fold. First, we provide the first public survey of machine learning algorithms applied to Dota 2–in the process gaining further insight into the algorithms we explore. Second, we provide a tool that we believe will be useful for both the casual and competitive sides of Dota 2’s 6 million unique player base.
Self-Oscillating Fluxgate-Based Quasi-Digital Sensor for DC High-Current Measurement

A quasi-digital dc current sensor with rated current of ±600 A while overload current of about ±750 A is proposed in this paper. The new sensor is based on the open-loop self-oscillating fluxgate technology, but its originality is using a microcontroller unit to detect the duty cycle of the exciting voltage of the fluxgate. Compared with the published similar method, the whole signal chain of the new sensor is quasi-digital and without low-pass filter and analog-to-digital converter required when connected to digital systems. A precisely theoretical equation with respect to the linear dependence between the duty cycle and the current to be measured is established. Based on the equation, factors affecting the sensor sensitivity, accuracy, and resolution are determined, which constitutes the theoretical basis on the optimization design of the new sensor. The sensor linearity is improved using the least-squares polynomial fitting method. Some key specifications including the linearity, repeatability, and power supply effect of the sensor are characterized. The measurement results show that the linearity of the new sensor with the theoretical equation is better than 1.7% in the full scale of ±600 A, and can be improved to 0.3% when the fifth-order polynomial fitting method is used.
The Design and Implementation of FFTW3

FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the hardware in order to maximize performance. This paper shows that such an approach can yield an implementation that is competitive with hand-optimized libraries, and describes the software structure that makes our current FFTW3 version flexible and adaptive. We further discuss a new algorithm for real-data DFTs of prime size, a new way of implementing DFTs by means of machine-specific single-instruction, multiple-data (SIMD) instructions, and how a special-purpose compiler can derive optimized implementations of the discrete cosine and sine transforms automatically from a DFT algorithm.
Characterizing Audio Adversarial Examples Using Temporal Dependency

Recent studies have highlighted adversarial examples as a ubiquitous threat to different neural network models and many downstream applications. Nonetheless, as unique data properties have inspired distinct and powerful learning principles, this paper aims to explore their potentials towards mitigating adversarial inputs. In particular, our results reveal the importance of using the temporal dependency in audio data to gain discriminate power against adversarial examples. Tested on the automatic speech recognition (ASR) tasks and three recent audio adversarial attacks, we find that (i) input transformation developed from image adversarial defense provides limited robustness improvement and is subtle to advanced attacks; (ii) temporal dependency can be exploited to gain discriminative power against audio adversarial examples and is resistant to adaptive attacks considered in our experiments. Our results not only show promising means of improving the robustness of ASR systems, but also offer novel insights in exploiting domain-specific data properties to mitigate negative effects of adversarial examples.
An Efficient, Distributed Stochastic Gradient Descent Algorithm for Deep-Learning Applications

Parallel and distributed processing is employed to accelerate training for many deep-learning applications with large models and inputs. As it reduces synchronization and communication overhead by tolerating stale gradient updates, asynchronous stochastic gradient descent (ASGD), derived from stochastic gradient descent (SGD), is widely used. Recent theoretical analyses show ASGD converges with linear asymptotic speedup over SGD.Oftentimes glossed over in theoretical analysis are communication overhead and practical learning rates that are critical to the performance of ASGD. After analyzing the communication performance and convergence behavior of ASGD using the Downpour algorithm as an example, we demonstrate the challenges for ASGD to achieve good practical speedup over SGD. We propose a distributed, bulk-synchronous stochastic gradient descent algorithm that allows for sparse gradient aggregation from individual learners. The communication cost is amortized explicitly by a gradient aggregation interval, and global reductions are used instead of a parameter server for gradient aggregation. We prove its convergence and show that it has superior communication performance and convergence behavior over popular ASGD implementations such as Downpour and EAMSGD for deep-learning applications.
A data-centric approach to synchronization

Concurrency-related errors, such as data races, are frustratingly difficult to track down and eliminate in large object-oriented programs. Traditional approaches to preventing data races rely on protecting instruction sequences with synchronization operations. Such control-centric approaches are inherently brittle, as the burden is on the programmer to ensure that all concurrently accessed memory locations are consistently protected. Data-centric synchronization is an alternative approach that offloads some of the work on the language implementation. Data-centric synchronization groups fields of objects into atomic sets to indicate that these fields must always be updated atomically. Each atomic set has associated units of work, that is, code fragments that preserve the consistency of that atomic set. Synchronization operations are added automatically by the compiler. We present an extension to the Java programming language that integrates annotations for data-centric concurrency control. The resulting language, called AJ, relies on a type system that enables separate compilation and supports atomic sets that span multiple objects and that also supports full encapsulation for more efficient code generation. We evaluate our proposal by refactoring classes from standard libraries, as well as a number of multithreaded benchmarks, to use atomic sets. Our results suggest that data-centric synchronization is easy to use and enjoys low annotation overhead, while successfully preventing data races. Moreover, experiments on the SPECjbb benchmark suggest that acceptable performance can be achieved with a modest amount of tuning.
A Simplification-Translation-Restoration Framework for Cross-Domain SMT Applications

Integration of domain specific knowledge into a general purpose statistical machine translation (SMT) system poses challenges due to insufficient bilingual corpora. In this paper we propose a simplification-translation-restoration (STR) framework for domain adaptation in SMT by simplifying domain specific segments of a text. For an in-domain text, we identify the critical segments and modify them to alleviate the data sparseness problem in the out-domain SMT system. After we receive the translation result, these critical segments are then restored according to the provided in-domain knowledge. We conduct experiments on an English-toChinese translation task in the medical domain and evaluate each step of the STR framework. The translation results show significant improvement of our approach over the out-domain and the naïve in-domain SMT systems. 用於跨領域統計式機器翻譯系統之簡化-翻譯-還原架構
Incredible high performance SAW resonator on novel multi-layerd substrate

High Q and low TCF are elemental characteristics for SAW resonator, in order to realize high performance filters and duplexers coping with new LTE frequency bands. Authors focus on the acoustic energy confinement in SAW propagation surface and electrical characteristics have been investigated theoretically and experimentally. A new multi-layered structure substrate have realized incredible high performances such as both three times Q and one fifth TCF compared with conventional structure. Band25 duplexer using the new structure has been developed successfully with low loss and good temperature stability.
A Nonlinear Dynamic Model of a Vinyl Acetate Process

This paper discusses a public domain model of a vinyl acetate (VAC) process. The VAC process is large enough to be representative in its essential features of many chemical processes. The process model contains 246 states, 26 manipulated variables, and 43 measurements. Parts of the model, e.g. the azeotropic distillation tower, are highly non-linear. An earlier model of the same process was published, but it was implemented in proprietary software. Both the source code used to generate the results in this paper and a compiled version are available to the public and the paper discusses how they can be obtained. The modeling approach used and differences with the earlier VAC model are discussed in detail. Simulations are presented which show the agreement with earlier results. The goal of the paper is to provide a readily available simulation that can be used as a testbed for advanced control approaches, such as plantwide control design and optimization, model predictive control and process monitoring.
A DOUBLE-DIF ERENTIAL-INPUT / DIF ERENTIAL-OUTPUT FUL Y COMPLEMENTARY AND SELF-BIASED ASYNCHRONOUS CMOS COMPARATOR

A novel fully complementary and fully differential asynchronous CMOS comparator architecture, that consists of a two-stage preamplifier cascaded with a latch, achieves a sub-100 ps propagation delay for a 50mVpp and higher input signal amplitudes under 1.1V supply and 2.1mW power consumption. The proposed voltage comparator topology features two differential pairs of inputs (four in total) thus increasing signal-to-noise ratio (SNR) and noise immunity through rejection of the coupled noise components, reduced evenorder harmonic distortion, and doubled output voltage swing. In addition to that, the comparator is truly self-biased via negative feedback loop thereby eliminating the need for a voltage reference and suppressing the influence of process, supply voltage and ambient temperature variations. The described analog comparator prototype occupies 0.001mm in a purely digital 40 nm LP (low power) CMOS process technology. All the above mentioned merits make it highly attractive for use as a building block in implementation of the leadingedge system-on-chip (SoC) data transceivers and data converters.
Cutting Corners and Working Overtime: Quality Erosion in the Service Industry

The erosion of service quality throughout the economy is a frequent concern in the popular press. The American Customer Satisfaction Index for services fell in 2000 to 69.4%, down 5 percentage points from 1994. We hypothesize that the characteristics of services— inseparability, intangibility, and labor intensity—interact with management practices to bias service providers toward reducing the level of service they deliver, often locking entire industries into a vicious cycle of eroding service standards. To explore this proposition we develop a formal model that integrates the structural elements of service delivery. We use econometric estimation, interviews, observations, and archival data to calibrate the model for a consumer-lending service center in a major bank in the United Kingdom. We find that temporary imbalances between service capacity and demand interact with decision rules for effort allocation, capacity management, overtime, and quality aspirations to yield permanent erosion of the service standards and loss of revenue. We explore policies to improve performance and implications for organizational design in the service sector. (Organizational Learning; Service Management Performance; Service Operations; Service Quality; Simulation; System Dynamics)
An information-centric energy infrastructure: The Berkeley view

We describe an approach for how to design an essentially more scalable, flexible and resilient electric power infrastructure – one that encourages efficient use, integrates local generation, and manages demand through omnipresent awareness of energy availability and use over time. We are inspired by how the Internet has revolutionized communications infrastructure, by pushing intelligence to the edges while hiding the diversity of underlying technologies through well-defined interfaces. Any end device is a traffic source or sink and intelligent endpoints adapt their traffic to what the infrastructure can
Machine-to-Machine Communication in LTE-A

Wireless equipped machines are increasing greatly in recent years, among which the cellular network based machine-to-machine communication (M2M) has shown the advantages of better coverage and lower network deployment cost. However, the current cellular network is designed for human-to-human communication, targeting the voice/media transmission with low access delay and high throughput, so the machines in GSM and UMTS are designed like a screenless phone. To extend the market to machine type communication, it is envisaged that the specific optimizations for M2M will be introduced in LTE-A, especially when M2M communication accounts for the considerable part in the total networking activities. In this paper, some of the considerations of the network side improvements are presented, from the physical layer, MAC to core network.