nils-herrmann/clean_scirepeval huggingface dataset:
Smalltalk-80: The Language and Its Implementation

Covers Smalltalk language and concepts from Xerox PARC. This need to a valid in with hexadecimal number before. Dwight thanks adele goldberg david robson copyright addison wesley isbn edition used was at compile. Smalltalk 80 syntax uses punctuation in, the language they can be significantly more popular. There is not this may be written as artifacts such messages. By storing them are parsed according to evaluate? The boolean receiver as lisp often even the virtual machine. One left smalltalk 80 is, the modern open. The increasing usage visualworks has recently been used was an image. Alan kay one thing developers to a transcript window would. Even primitives such interleaving of the, language and dec objectstudio each restart. Enfin was an object holds is, extremely important. Also be recreated explicitly define the, book presents a copy of the agile methods messages.
NOUS: Construction and Querying of Dynamic Knowledge Graphs

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a transformative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-toend framework for developing custom knowledge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queries where the answer is embedded across multiple data sources.
Analysis of first-order anti-aliasing integration sampler

Performance of the first-order anti-aliasing integration sampler used in software-defined radio (SDR) receivers is analyzed versus all practical nonidealities. The nonidealities that are considered in this paper are transconductor finite output resistance, switch resistance, nonzero rise and fall times of the sampling clock, charge injection, clock jitter, and noise. It is proved that the filter is quite robust to all of these nonidealities except for transconductor finite output resistance. Furthermore, linearity and noise performances are all limited to design of a low-noise and highly linear transconductor.
Identifying Rhetorical Questions in Social Media

Social media provides a platform for seeking information from a large user base. Information seeking in social media, however, occurs simultaneously with users expressing their viewpoints by making statements. Rhetorical questions have the form of a question but serve the function of a statement and might mislead platforms assisting information seeking in social media. It becomes difficult to identify rhetorical questions as they are not syntactically different from other questions. In this paper, we develop a framework to identify rhetorical questions by modeling the motivations of the users to post them. We focus on one motivation of the users drawing from linguistic theories, to implicitly convey a message. We develop a framework from this motivation to identify rhetorical questions in social media and evaluate the framework using questions posted on Twitter. This is the first framework to model the motivations for posting rhetorical questions to identify them on social
General multilevel linear modeling for group analysis in FMRI

This article discusses general modeling of multisubject and/or multisession FMRI data. In particular, we show that a two-level mixed-effects model (where parameters of interest at the group level are estimated from parameter and variance estimates from the single-session level) can be made equivalent to a single complete mixed-effects model (where parameters of interest at the group level are estimated directly from all of the original single sessions' time series data) if the (co-)variance at the second level is set equal to the sum of the (co-)variances in the single-level form, using the BLUE with known covariances. This result has significant implications for group studies in FMRI, since it shows that the group analysis requires only values of the parameter estimates and their (co-)variance from the first level, generalizing the well-established "summary statistics" approach in FMRI. The simple and generalized framework allows different prewhitening and different first-level regressors to be used for each subject. The framework incorporates multiple levels and cases such as repeated measures, paired or unpaired t tests and F tests at the group level; explicit examples of such models are given in the article. Using numerical simulations based on typical first-level covariance structures from real FMRI data we demonstrate that by taking into account lower-level covariances and heterogeneity a substantial increase in higher-level Z score is possible.
Data-driven Workflows for Microservices

Microservices is an architectural style inspired by service-oriented computing that has recently started gaining popularity. Jolie is a programming language based on the microservices paradigm: the main building block of Jolie systems are services, in contrast to, e.g., functions or objects. The primitives offered by the Jolie language elicit many of the recurring patterns found in microservices, like load balancers and structured processes. However, Jolie still lacks some useful constructs for dealing with message types and data manipulation that are present in service-oriented computing. In this paper, we focus on the possibility of expressing choices at the level of data types, a feature well represented in standards for Web Services, e.g., WSDL. We extend Jolie to support such type choices and show the impact of our implementation on some of the typical scenarios found in microservice systems. This shows how computation can move from a process-driven to a datadriven approach, and leads to the preliminary identification of recurring communication patterns that can be shaped as design patterns.
Fine-grained accelerators for sparse machine learning workloads

Text analytics applications using machine learning techniques have grown in importance with ever increasing amount of data being generated from web-scale applications, social media and digital repositories. Apart from being large in size, these generated data are often unstructured and are heavily sparse in nature. The performance of these applications on current systems is hampered by hard to predict branches and low compute-per-byte ratio. This paper proposes a set of fine-grained accelerators that improve the performance and energy-envelope of these applications by an order of magnitude.
One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations

Discourse relations bind smaller linguistic units into coherent texts. Automatically identifying discourse relations is difficult, because it requires understanding the semantics of the linked arguments. A more subtle challenge is that it is not enough to represent the meaning of each argument of a discourse relation, because the relation may depend on links between lowerlevel components, such as entity mentions. Our solution computes distributed meaning representations for each discourse argument by composition up the syntactic parse tree. We also perform a downward compositional pass to capture the meaning of coreferent entity mentions. Implicit discourse relations are then predicted from these two representations, obtaining substantial improvements on the Penn Discourse Treebank.
Enhancing Performance And Reliability of Rule Management Platforms

RulE Management Platforms (REMPs) enable software engineers to represent programming logic as conditional sentences that relate statements of facts. A key benefit of REMPs is that they make software adaptable by burying the complexity of rule invocation in their engines, so that programmers can concentrate on business aspects of highly modular rules. Naturally, rule-driven applications are expected to have excellent performance, since REMP engines should be able to invoke highly modular rules in parallel in response to asserting different facts. In reality, it is very difficult to parallelize rule executions, since it leads to the loss of reliability and adaptability of rule-driven applications.
 We created a novel solution that is based on obtaining a rule execution model that is used at different layers of REMPs to enhance the performance of rule-driven applications while maintaining their reliability and adaptability. First, using this model, possible races are detected statically among rules, and we evaluate an implementation of our abstraction of algorithms for automatically preventing races among rules. Next, we use the sensitivity analysis to find better schedules among simultaneously executing rules to improve the overall performance of the application. We implemented our solution for JBoss Drools and we evaluated it on three applications. The results suggest that our solution is effective, since we achieved over 225% speedup on average.
Data pricing strategy based on data quality

http://dx.doi.org/10.1016/j.cie.2017.08.008 0360-8352/ 2017  This work is supported by Fundamental Research Funds for the Central Universities (N150604003). ⇑ Corresponding author. E-mail address: mengxiaozhang47@hotmail.com (M. Zhang). 1 https://www.factual.com. 2 http://www.infochimps.com. 3 http://www.xignite.com. 4 https://datamarket.azure.com. Haifei Yu, Mengxiao Zhang ⇑
Traffic dispersion graph based anomaly detection

Detecting and diagnosing anomalous traffic are important aspects of managing IP networks. In this paper, we propose a novel approach to detect anomalous network traffic based on graph theory concepts such as degree distribution, maximum degree and dK-2 distance. In this approach, we have used the traffic dispersion graphs (TDG) to model network traffic over time. We analyze differences of TDG graphs in time series to detect anomalies and introduce a method to identify attack patterns in anomalous traffic. The approach has been validated by using network traces from POSTECH and CAIDA.
Defining the Human Deubiquitinating Enzyme Interaction Landscape

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.
Towards a unified visual notation for OWL ontologies: insights from a comparative user study

Browsing ontologies and making sense of their concepts and relationships are important activities in knowledge engineering. They are supported by a large number of tools that often provide visual representations of the ontologies for better illustration. However, different notations are used to represent the ontologies which can be confusing when switching tools. Furthermore, many representations provide only basic overviews of the ontologies that are not sufficient to get a deeper understanding of the concepts and relationships. A unified visual notation for OWL ontologies would be most helpful to overcome these limitations. Having this goal in mind, we compare two different notations for OWL ontologies in this paper: the UML profile of the Ontology Definition Metamodel (ODM) and the Visual Notation for OWL Ontologies (VOWL). We report on a comparative user study of these notations and discuss benefits and limitations raised by the study participants. Based on these findings, we draw some general conclusions regarding the development of a unified visual notation for OWL ontologies.
DNA methylation analysis by pyrosequencing

Pyrosequencing is a sequencing-by-synthesis method that quantitatively monitors the real-time incorporation of nucleotides through the enzymatic conversion of released pyrophosphate into a proportional light signal. Quantitative measures are of special importance for DNA methylation analysis in various developmental and pathological situations. Analysis of DNA methylation patterns by pyrosequencing combines a simple reaction protocol with reproducible and accurate measures of the degree of methylation at several CpGs in close proximity with high quantitative resolution. After bisulfite treatment and PCR, the degree of each methylation at each CpG position in a sequence is determined from the ratio of T and C. The process of purification and sequencing can be repeated for the same template to analyze other CpGs in the same amplification product. Quantitative epigenotypes are obtained using this protocol in approximately 4 h for up to 96 DNA samples when bisulfite-treated DNA is already available as the starting material.
Plasmonics simulations with the MNPBEM toolbox: Consideration of substrates and layer structures

Within the MNPBEM toolbox, developed for the simulation of plasmonic nanoparticles using a boundary element method approach, we show how to include substrate and layer structure effects. We develop the methodology for solving Maxwell’s equations using scalar and vector potentials within the inhomogeneous dielectric environment of a layer structure. We show that the implementation of our approach allows for fast and efficient simulations of plasmonic nanoparticles situated on top of substrates or embedded in layer structures. The new toolbox provides a number of demo files which can be also used as templates for other simulations. MNPBEM toolbox Catalogue identifier: AEKJ_v3_0  http://cpc.cs.qub.ac.uk/summaries/AEKJ_v3_0.html  CPC Program Library, Queen’s University, Belfast, N. Ireland  Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 56958 No. of bytes in distributed program, including test data, etc.: 1258497  tar.gz Matlab 8.3.0 (R2014a).  Any which supports Matlab 8.3.0 (R2014a).  Any which supports Matlab 8.3.0 (R2014a). Has the code been vectorised or parallelized?: Yes RAM: ≥4 Gbyte Classification: 18. Catalogue identifier of previous version: AEKJ_v2_0   (2014) 1177  Yes  Simulation of plasmonic nanoparticles placed on substrates or within layer structures.  Boundary element method using electromagnetic potentials  Inclusion of substrate and layer structure effects Summary of revisions: • simulations with layer structures and substrates • simulation control through one options structure ✩ This paper and its associated computer program are available via the Computer Physics Communication homepage on ScienceDirect (http://www.sciencedirect.com/ science/journal/00104655). ∗ Corresponding author. E-mail address: ulrich.hohenester@uni-graz.at (U. Hohenester).  (U. Hohenester). http://dx.doi.org/10.1016/j.cpc.2015.03.023 0010-4655/  (2015) 138–150 139 • refined boundary element integration • consideration of flat and curved particle boundaries • an improved plot function for particle objects • a new polygon3 class for the extrusion of 2d shapes • a new meshfield class for the computation of electric field maps Running time: Depending on surface discretization between seconds and hours.
All your contacts are belong to us: automated identity theft attacks on social networks

Social networking sites have been increasingly gaining popularity. Well-known sites such as Facebook have been reporting growth rates as high as 3% per week. Many social networking sites have millions of registered users who use these sites to share photographs, contact long-lost friends, establish new business contacts and to keep in touch. In this paper, we investigate how easy it would be for a potential attacker to launch automated crawling and identity theft attacks against a number of popular social networking sites in order to gain access to a large volume of personal user information. The first attack we present is the automated identity theft of existing user profiles and sending of friend requests to the contacts of the cloned victim. The hope, from the attacker's point of view, is that the contacted users simply trust and accept the friend request. By establishing a friendship relationship with the contacts of a victim, the attacker is able to access the sensitive personal information provided by them. In the second, more advanced attack we present, we show that it is effective and feasible to launch an automated, cross-site profile cloning attack. In this attack, we are able to automatically create a forged profile in a network where the victim is not registered yet and contact the victim's friends who are registered on both networks. Our experimental results with real users show that the automated attacks we present are effective and feasible in practice.
SDN docker: Enabling application auto-docking/undocking in edge switch

Software-Defined Networking (SDN) enables users to programmatically manage individual data flows in the network. Beyond managing data flows, an SDN enabled switch that automatically manages different applications in the form of an ecosystem has more practical benefits. Recently there is an increasing interest on migrating applications from `Cloud' to the edge switches, such as `Fog' computing for IoTs. To cater to such interests, we envisage an architecture that empowers SDN (beyond Layer-2 flow management) to automatically manage applications embedded within the switch. In this paper, for the first time, we propose an SDN-based auto-docker framework integrated within the switches. The proposed framework augments SDN architecture to enable auto-docking/undocking of applications at the edge switches. By `auto', we mean the required application is automatically identified (agnostic to the users) from the incoming packet, installed seamlessly, and subsequently uninstalled from the switch when it is no longer needed. In this manner, the docker framework automatically and effectively manages the storage, computing, and networking resources of the switch. We develop a working prototype of the framework using off-the-shelf network switches, and evaluate the performance of the proposed docker framework.
Effectiveness of domestic wastewater treatment using microbial fuel cells at ambient and mesophilic temperatures.

Domestic wastewater treatment was examined under two different temperature (23+/-3 degrees C and 30+/-1 degrees C) and flow modes (fed-batch and continuous) using single-chamber air-cathode microbial fuel cells (MFCs). Temperature was an important parameter for treatment efficiency and power generation. The highest power density of 422 mW/m(2) (12.8 W/m(3)) was achieved under continuous flow and mesophilic conditions, at an organic loading rate of 54 g COD/L-d, achieving 25.8% COD removal. Energy recovery was found to depend significantly on the operational conditions (flow mode, temperature, organic loading rate, and HRT) as well as the reactor architecture. The results demonstrate that the main advantages of using temperature-phased, in-series MFC configurations for domestic wastewater treatment are power savings, low solids production, and higher treatment efficiency.
IEEE 802.15.7 visible light communication: modulation schemes and dimming support

Visible light communication refers to shortrange optical wireless communication using visible light spectrum from 380 to 780 nm. Enabled by recent advances in LED technology, IEEE 802.15.7 supports high-data-rate visible light communication up to 96 Mb/s by fast modulation of optical light sources which may be dimmed during their operation. IEEE 802.15.7 provides dimming adaptable mechanisms for flicker-free high-data-rate visible light communication.
Low Latency Geo-distributed Data Analytics

Low latency analytics on geographically distributed datasets (across datacenters, edge clusters) is an upcoming and increasingly important challenge. The dominant approach of aggregating all the data to a single datacenter significantly inflates the timeliness of analytics. At the same time, running queries over geo-distributed inputs using the current intra-DC analytics frameworks also leads to high query response times because these frameworks cannot cope with the relatively low and variable capacity of WAN links. We present Iridium, a system for low latency geo-distributed analytics. Iridium achieves low query response times by optimizing placement of both data and tasks of the queries. The joint data and task placement optimization, however, is intractable. Therefore, Iridium uses an online heuristic to redistribute datasets among the sites prior to queries' arrivals, and places the tasks to reduce network bottlenecks during the query's execution. Finally, it also contains a knob to budget WAN usage. Evaluation across eight worldwide EC2 regions using production queries show that Iridium speeds up queries by 3× -- 19× and lowers WAN usage by 15% -- 64% compared to existing baselines.
A game of refactoring: Studying the impact of gamification in software refactoring

Software refactoring is an essential skill for developers. It improves the quality of the software and reduces maintenance costs in the long run. In this paper, we investigate the impact that gamification can have on the refactoring process and on the usability of the existing refactoring tools. For this reason we created CodeArena, a gamification system that tracks and rewards refactorings during development. We used CodeArena in an exploratory study which involved 12 students of computer science. Then, we collected the feedback provided by these students via a survey. Although the gamification had less effect than expected, our findings can be useful to practitioners interested in promoting refactoring tools via gamification.
Design and navigation control of an advanced level CANSAT

This paper presents design and navigation control of an advanced level comeback CanSat which is going to be launched to an altitude of about 400 m using an amateur rocket from ground level. The CanSat uses advanced and ultra-light microcontroller, pressure and temperature sensors, 3-axis accelerometer, 3-axis gyro, camera, GPS, IR distance measuring sensor, and RF communication module to communicate with the ground station PC. Three actuators are considered in this work for flight and ground segments control. They are the motor driven propeller, elevator and rudder. For the flight segment, parachute and attitude control are used to control the CanSat descent rate, attitude and heading. For the ground segment control; both the propeller and the rear landing gear of the CanSat is used for heading toward a predefined location on the ground. The rear landing gear is connected to the rudder rotational axis. An indigenous navigation control and electronic circuit design with the test results also are presented in this paper.