nils-herrmann/clean_scirepeval huggingface dataset:
Distributed Incremental Pattern Matching on Streaming Graphs

Big data has shifted the computing paradigm of data analysis. While some of the data can be treated as simple texts or independent data records, many other applications have data with structural patterns which are modeled as a graph, such as social media, road network traffic and smart grid, etc. However, there is still limited amount of work has been done to address the velocity problem of graph processing. In this work, we aim to develop a distributed processing system for solving pattern matching queries on streaming graphs where graphs evolve over time upon the arrives of streaming graph update events. To achieve the goal, we proposed an incremental pattern matching algorithm and implemented it on GPS, a vertex centric distributed graph computing framework. We also extended the GPS framework to support streaming graph, and adapted a subgraphcentric data model to further reduce communication overhead and system performance. Our evaluation using real wiki trace shows that our approach achieves a 3x -- 10x speedup over the batch algorithm, and significantly reduces network and memory usage.
“SEIS” – SECURITY IN EMBEDDED IP-BASED SYSTEMS

results in complex and cost-intensive E/E architectures. For this reason the innovation alliance for automobile electronics E|ENOVA initiated the research project “SEIS – Safety in Embedded IP-based Systems”, with the aim of creating a consistent security solution for internet protocol based communication inside the vehicle and for the vehicle’s communication with the environment. The project partners now report for the first time on the success of the security initiative, which was started one year ago. “SEIS” – SECURITY IN EMBEDDED IP-BASED SYSTEMS Michael Glass works in the Department Hardware/Software CoDesign at the University of Erlangen-Nuremberg in Erlangen (Germany).
Electrically small omni-directional antenna of circular polarization

A compact omni-directional antenna of circular polarization (CP) is presented for 2.4 GHz WLAN access-point applications. The antenna consists of four bended monopoles and a feeding network simultaneously exciting these four monopoles. The electrical size of the CP antenna is only λ<sub>0</sub>/5×λ<sub>0</sub>/5×λ<sub>0</sub>/13. The impedance bandwidth (|S<sub>11</sub>|<;-10 dB) is 3.85% (2.392 GHz to 2.486 GHz) and the axial ratio in the azimuth plane is lower than 0.5 dB in the operating band.
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari

Evolution Strategies (ES) have recently been demonstrated to be a viable alternative to reinforcement learning (RL) algorithms on a set of challenging deep RL problems, including Atari games and MuJoCo humanoid locomotion benchmarks. While the ES algorithms in that work belonged to the specialized class of natural evolution strategies (which resemble approximate gradient RL algorithms, such as REINFORCE), we demonstrate that even a very basic canonical ES algorithm can achieve the same or even better performance. This success of a basic ES algorithm suggests that the state-of-the-art can be advanced further by integrating the many advances made in the field of ES in the last decades. We also demonstrate qualitatively that ES algorithms have very different performance characteristics than traditional RL algorithms: on some games, they learn to exploit the environment and perform much better while on others they can get stuck in suboptimal local minima. Combining their strengths with those of traditional RL algorithms is therefore likely to lead to new advances in the state of the art.
Co-change Clusters: Extraction and Application on Assessing Software Modularity

The traditional modular structure defined by the package hierarchy suffers from the dominant decomposition problem and it is widely accepted that alternative forms of modularization are necessary to increase developer’s productivity. In this paper, we propose an alternative form to understand and assess package modularity based on co-change clusters, which are highly inter-related classes considering cochange relations. We evaluate how co-change clusters relate to the package decomposition of four real-world systems. The results show that the projection of co-change clusters to packages follows different patterns in each system. Therefore, we claim that modular views based on co-change clusters can improve developers’ understanding on how well-modularized are their systems, considering that modularity is the ability to confine changes and evolve components in parallel.
Plans and resource-bounded practical reasoning

An architecture for a rational agent must allow for means end reason ing for the weighing of competing alternatives and for interactions between these two forms of reasoning Such an architecture must also address the problem of resource boundedness We sketch a solution of the rst problem that points the way to a solution of the second In particular we present a high level speci cation of the practical reasoning component of an archi tecture for a resource bounded rational agent In this architecture a major role of the agent s plans is to constrain the amount of further practical reasoning she must perform Bratman Israel and Pollack
Toward Fast and Accurate Neural Discourse Segmentation

Discourse segmentation, which segments texts into Elementary Discourse Units, is a fundamental step in discourse analysis. Previous discourse segmenters rely on complicated hand-crafted features and are not practical in actual use. In this paper, we propose an endto-end neural segmenter based on BiLSTMCRF framework. To improve its accuracy, we address the problem of data insufficiency by transferring a word representation model that is trained on a large corpus. We also propose a restricted self-attention mechanism in order to capture useful information within a neighborhood. Experiments on the RST-DT corpus show that our model is significantly faster than previous methods, while achieving new stateof-the-art performance.
Treatment of oral mucocele-scalpel versus CO2 laser.

To compare the results obtained after oral mucocele resection with the scalpel versus the CO2 laser, based on the complications and recurrences after surgery.



Of the 68 patients we studied who have mucocele, 38 were resected with a scalpel and the remaining 30 with the CO2 laser (5-7 W). Patient sex and age were documented, along with location of the lesion as well as size, symptoms, duration, etiological factors, type of treatment, complications and recurrences after surgical removal.



The sample comprised 40 males and 28 females, aged between 6-65 years. The histological diagnosis was extravasation mucocele in 95% of the cases. The most frequent location was the lower lip (73.5%). The mean lesion diameter was 9 mm, and in most cases no evident etiological factor was recorded. The mean duration of the lesion was 4 months. Among the cases of conventional surgical removal of mucocele, recurrence was recorded in 8.8% of the cases, and 13.2% of the patients suffered postoperative complications--the most frequent being the presence of fibrous scars. There were no complications or relapses after a minimum follow-up of 12 months in the cases subjected to CO2 laser treatment.



Oral mucocele ablation with the CO2 laser offers more predictable results and fewer complications and recurrences than conventional resection with the scalpel.
A Comparison of Sender-Initiated and Receiver-Initiated Reliable Multicast Protocols

Sender-initiated reliable multicast protocols, based on the use of positive acknowledgments (ACKs), lead to an ACK implosion problem at the sender as the number of receivers increases. Briefly, the ACK implosion problem refers to the significant overhead incurred by the sending host due to the processing of ACKs from each receiver. A potential solution to this problem is to shift the burden of providing reliable data transfer to the receivers—thus resulting in a receiver-initiated multicast error control protocol based on the use of negative acknowledgments (NAKs). In this paper we determine the maximum throughputs of the sending and receiving hosts for generic sender-initiated and receiver-initiated protocols. We show that the receiver-initiated error control protocols provide substantially higher throughputs than their sender-initiated counterparts. We further demonstrate that the introduction of random delays prior to generating NAKs coupled with the multicasting of NAKs to all receivers has the potential for an additional substantial increase in the throughput of receiver-initiated error control protocols over sender-initiated protocols.
Non-Negative Patch Alignment Framework

In this paper, we present a non-negative patch alignment framework (NPAF) to unify popular non-negative matrix factorization (NMF) related dimension reduction algorithms. It offers a new viewpoint to better understand the common property of different NMF algorithms. Although multiplicative update rule (MUR) can solve NPAF and is easy to implement, it converges slowly. Thus, we propose a fast gradient descent (FGD) to overcome the aforementioned problem. FGD uses the Newton method to search the optimal step size, and thus converges faster than MUR. Experiments on synthetic and real-world datasets confirm the efficiency of FGD compared with MUR for optimizing NPAF. Based on NPAF, we develop non-negative discriminative locality alignment (NDLA). Experiments on face image and handwritten datasets suggest the effectiveness of NDLA in classification tasks and its robustness to image occlusions, compared with representative NMF-related dimension reduction algorithms.
Development of a Software Engineering Ontology for Multisite Software Development

This paper aims to present an ontology model of software engineering to represent its knowledge. The fundamental knowledge relating to software engineering is well described in the textbook entitled Software Engineering by Sommerville that is now in its eighth edition (2004) and the white paper, Software Engineering Body of Knowledge (SWEBOK), by the IEEE (203) upon which software engineering ontology is based. This paper gives an analysis of what software engineering ontology is, what it consists of, and what it is used for in the form of usage example scenarios. The usage scenarios presented in this paper highlight the characteristics of the software engineering ontology. The software engineering ontology assists in defining information for the exchange of semantic project information and is used as a communication framework. Its users are software engineers sharing domain knowledge as well as instance knowledge of software engineering.
Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262

The use of machine learning (ML) is on the rise in many sectors of software development, and automotive software development is no different. In particular, Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) are two areas where ML plays a significant role. In automotive development, safety is a critical objective, and the emergence of standards such as ISO 26262 has helped focus industry practices to address safety in a systematic and consistent way. Unfortunately, these standards were not designed to accommodate technologies such as ML or the type of functionality that is provided by an ADS and this has created a conflict between the need to innovate and the need to improve safety. In this report, we take steps to address this conflict by doing a detailed assessment and adaption of ISO 26262 for ML, specifically in the context of supervised learning. First we analyze the key factors that are the source of the conflict. Then we assess each software development process requirement (Part 6 of ISO 26262) for applicability to ML. Where there are gaps, we propose new requirements to address the gaps. Finally we discuss the application of this adapted and extended variant of Part 6 to ML development scenarios.
Generating Fake but Realistic Headlines Using Deep Neural Networks

Social media platforms such as Twitter and Facebook implement filters to detect fake news as they foresee their transition from social media platform to primary sources of news. The robustness of such filters lies in the variety and the quality of the data used to train them. There is, therefore, a need for a tool that automatically generates fake but realistic news. In this paper, we propose a deep learning model that automatically generates news headlines. The model is trained with a corpus of existing headlines from different topics. Once trained, the model generates a fake but realistic headline given a seed and a topic. For example, given the seed “Kim Jong Un” and the topic “Business”, the model generates the headline “kim jong un says climate change is already making money”. In order to better capture and leverage the syntactic structure of the headlines for the task of synthetic headline generation, we extend the architecture Contextual Long Short Term Memory, proposed by Ghosh et al. to also learn a part-of-speech model. We empirically and comparatively evaluate the performance of the proposed model on a real corpora of headlines. We compare our proposed approach and its variants using Long Short Term Memory and Gated Recurrent Units as the building blocks. We evaluate and compare the topical coherence of the generated headlines using a state-of-the-art classifier. We, also, evaluate the quality of the generated headline using a machine translation quality metric and its novelty using a metric we propose for this purpose. We show that the proposed model is practical and competitively efficient and effective.
Do security toolbars actually prevent phishing attacks?

Security toolbars in a web browser show security-related information about a website to help users detect phishing attacks. Because the toolbars are designed for humans to use, they should be evaluated for usability -- that is, whether these toolbars really prevent users from being tricked into providing personal information. We conducted two user studies of three security toolbars and other browser security indicators and found them all ineffective at preventing phishing attacks. Even though subjects were asked to pay attention to the toolbar, many failed to look at it; others disregarded or explained away the toolbars' warnings if the content of web pages looked legitimate. We found that many subjects do not understand phishing attacks or realize how sophisticated such attacks can be.
Unchaining Social Businesses - Blockchain as the Basic Technology of a Crowdlending Platform

Social businesses are increasingly gaining relevance as alternatives to traditional businesses. Nonetheless, such organizations face specific problems. The emerging blockchain technology may represent an opportunity to solve several problems of social businesses and an alternative to established technologies. However, evidence about the potential of blockchain in social businesses is missing. We bridge this gap by designing, developing, and evaluating a blockchain-based crowdlending platform of a social business, following the design science research approach. The evaluation and comparison to a non-blockchain solution allows us to generate generalizable knowledge and derive implications for both research and practice. Our research shows that blockchain enables otherwise unsustainable social business models, mainly by replacing intermediaries and requires changes in software engineering practices. Further, our findings illustrate that blockchain raises challenges and uncertainties and opens promising avenues for further
Differences in energy expenditure during high-speed versus standard-speed yoga: A randomized sequence crossover trial.

To compare energy expenditure and volume of oxygen consumption and carbon dioxide production during a high-speed yoga and a standard-speed yoga program.



Randomized repeated measures controlled trial.



A laboratory of neuromuscular research and active aging.



Sun-Salutation B was performed, for eight minutes, at a high speed versus and a standard-speed separately while oxygen consumption was recorded. Caloric expenditure was calculated using volume of oxygen consumption and carbon dioxide production.



Difference in energy expenditure (kcal) of HSY and SSY.



Significant differences were observed in energy expenditure between yoga speeds with high-speed yoga producing significantly higher energy expenditure than standard-speed yoga (MD=18.55, SE=1.86, p<0.01). Significant differences were also seen between high-speed and standard-speed yoga for volume of oxygen consumed and carbon dioxide produced.



High-speed yoga results in a significantly greater caloric expenditure than standard-speed yoga. High-speed yoga may be an effective alternative program for those targeting cardiometabolic markers.
Gradient Metasurface With Both Polarization-Controlled Directional Surface Wave Coupling and Anomalous Reflection

A gradient metasurface is proposed to obtain both surface wave coupling and anomalous reflection. The unit cell of the gradient metasurface is composed by six electric field coupled resonators in different rotation angle, which provides a phase gradient. The simulation and measured results show that this gradient metasurface can work at 7.8 GHz as a surface wave coupler and at 10.288 GHz providing a phenomenon of anomalous reflection. At the two frequencies, the direction of the reflection is polarization-controlled, and the efficiencies are polarization-invariant. At left-handed polarization incidence, the direction of the coupled surface wave and the anomalous reflection are opposite to the situation at right-handed polarization incidence.
Affine systems in L 2 ( IR d ) : the analysis of the analysis operator

Discrete affine systems are obtained by applying dilations to a given shift-invariant system. The complicated structure of the affine system is due, first and foremost, to the fact that it is not invariant under shifts. Affine frames carry the additional difficulty that they are “global” in nature: it is the entire interaction between the various dilation levels that determines whether the system is a frame, and not the behaviour of the system within one dilation level. We completely unravel the structure of the affine system with the aid of two new notions: the affine product, and a quasi-affine system. This leads to a characterization of affine frames; the induced characterization of tight affine frames is in terms of exact orthogonality relations that the wavelets should satisfy on the Fourier domain. Several results, such as a general oversampling theorem follow from these characterizations. Most importantly, the affine product can be factored during a multiresolution analysis construction, and this leads to a complete characterization of all tight frames that can be constructed by such methods. Moreover, this characterization suggests very simple sufficient conditions for constructing tight frames from multiresolution. Of particular importance are the facts that the underlying scaling function does not need to satisfy any a priori conditions, and that the freedom offered by redundancy can be fully exploited in these constructions. AMS (MOS) Subject Classifications: Primary 42C15, Secondary 42C30
Elephants don't play chess

Rodney A. Brooks was born in Adelaide, Australia. He studied Mathematics at the Flinders University of South Australia and received a Ph.D. from Stanford in Computer Science in 1981. Since then he has held research associate positions at Carnegie Mellon University and the Massachusetts Institute of Technology and faculty positions at Stanford and M.I.T. He is currently an Associate Professor of Electrical Engineering and Computer Science at M.I.T. and a member of the Artificial Intelligence Laboratory where he leads the mobile robot group. He has authored two books, numerous scientific papers, and is the editor of the International Journal of Computer Vision.
Machine Ethics and Automated Vehicles

Road vehicle travel at a reasonable speed involves some risk, even when using computer-controlled driving with failure-free hardware and perfect sensing. A fully-automated vehicle must continuously decide how to allocate this risk without a human driver’s oversight. These are ethical decisions, particularly in instances where an automated vehicle cannot avoid crashing. In this chapter, I introduce the concept of moral behavior for an automated vehicle, argue the need for research in this area through responses to anticipated critiques, and discuss relevant applications from machine ethics and moral modeling research. 1 Ethical Decision Making for Automated Vehicles Vehicle automation has progressed rapidly this millennium, mirroring improvements in machine learning, sensing, and processing. Media coverage often focuses on the anticipated safety benefits from automation, as computers are expected to be more attentive, precise, and predictable than human drivers. Mentioned less often are the novel problems from automated vehicle crash. The first problem is liability, as it is currently unclear who would be at fault if a vehicle crashed while self-driving. The second problem is the ability of an automated vehicle to make ethically-complex decisions when driving, particularly prior to a crash. This chapter focuses on the second problem, and the application of machine ethics to vehicle automation. Driving at any significant speed can never be completely safe. A loaded tractor trailer at 100 km/hr requires eight seconds to come to a complete stop, and a passenger car requires three seconds . Truly safe travel requires accurate predictions of other vehicle behavior over this time frame, something that is simply not possible given the close proximities of road vehicles. To ensure its own safety, an automated vehicle must continually assess risk: the risk of traveling a certain speed on a certain curve, of crossing the centerline to
Information leakage from optical emanations

A previously unknown form of compromising emanations has been discovered. LED status indicators on data communication equipment, under certain conditions, are shown to carry a modulated optical signal that is significantly correlated with information being processed by the device. Physical access is not required; the attacker gains access to all data going through the device, including plaintext in the case of data encryption systems. Experiments show that it is possible to intercept data under realistic conditions at a considerable distance. Many different sorts of devices, including modems and Internet Protocol routers, were found to be vulnerable. A taxonomy of compromising optical emanations is developed, and design changes are described that will successfully block this kind of "Optical Tempest" attack.
Audio Event Detection and classification using extended R-FCN Approach

In this study, we present a new audio event detection and classification approach based on R-FCN—a state-of-the-art fully convolutional network framework for visual object detection. Spectrogram features of audio signals are used as the input of the approach. The proposed approach consists of two stages like R-FCN network. In the first stage, we detect whether there are audio events by sliding convolutional kernel in time axis, and then proposals which possibly contain audio events are generated by RPN (Region Proposal Networks). In the second stage, time and frequency domain information are integrated to classify these proposals and refine their boundaries. Our approach can output the positions of audio events directly which can input a two-dimensional representation of arbitrary length sound without any size regularization.