nils-herrmann/clean_scirepeval huggingface dataset:
What Are Race Conditions? Some Issues and Formalizations

In shared-memory parallel programs that use explicit synchronization, race conditions result when accesses to shared memory are not properly synchronized. Race conditions are often considered to be manifestations of bugs, since their presence can cause the program to behave unexpectedly. Unfortunately, there has been little agreement in the literature as to precisely what constitutes a race condition. Two different notions have been implicitly considered: one pertaining to programs intended to be deterministic (which we call general races) and the other to nondeterministic programs containing critical sections (which we call data races). However, the differences between general races and data races have not yet been recognized. This paper examines these differences by characterizing races using a formal model and exploring their properties. We show that two variations of each type of race exist: feasible general races and data races capture the intuitive notions desired for debugging and apparent races capture less accurate notions implicitly assumed by most dynamic race detection methods. We also show that locating feasible races is an NP-hard problem, implying that only the apparent races, which are approximations to feasible races, can be detected in practice. The complexity of dynamically locating apparent races depends on the type of synchronization used by the program. Apparent races can be exhaustively located efficiently only for weak types of synchronization that are incapable of implementing mutual exclusion. This result has important implications since we argue that debugging general races requires exhaustive race detection and is inherently harder than debugging data races (which requires only partial race detection). Programs containing data races can therefore be efficiently debugged by locating certain easily identifiable races. In contrast, programs containing general races require more complex debugging techniques.
On Blockchain Applications : Hyperledger Fabric And Ethereum

Blockchain is a tamper-proof digital ledger which can be used to record public or private peer to peer network transactions and it cannot be altered retroactively without the alteration of all subsequent blocks of the network. A blockchain is updated via the consensus protocol that ensures a linear, unambiguous ordering of transactions. Blocks guarantee the integrity and consistency of the blockchain across a network of distributed nodes. Different blockchain applications use various consensus protocols for their working. Byzantine fault tolerance (BFT) is one of them and it is a characteristic of a system that tolerates the class of failures known as the Byzantine Generals Problem. Hyperledger, Stellar, and Ripple are three blockchain application which uses BFT consensus. The best variant of BFT is Practical Byzantine Fault tolerance (PBFT). Hyperledger fabric with deterministic transactions can run on the top of PBFT. This paper focuses on a survey of various consensus mechanisms and makes a comparative study of Hyperledger fabric and Ethereum.  consensus; hyperledger fabric; ethereum; byzantine fault tolerance;
Modelling Plastic Distortion in Fingerprint Images

This paper introduces a plastic distortion model to cope with the nonlinear deformations characterizing fingerprint images taken with online acquisition sensors. The problem has a great impact on several practical applications, ranging from the design of robust fingerprint matching algorithms to the generation of synthetic fingerprint images. The experimentation on real data validates the model and demonstrates its efficacy in registering minutiae data from highly distorted fingerprint samples.
The FuzzyLog: A Partially Ordered Shared Log

The FuzzyLog is a partially ordered shared log abstraction. Distributed applications can concurrently append to the partial order and play it back. FuzzyLog applications obtain the benefits of an underlying shared log – extracting strong consistency, durability, and failure atomicity in simple ways – without suffering from its drawbacks. By exposing a partial order, the FuzzyLog enables three key capabilities for applications: linear scaling for throughput and capacity (without sacrificing atomicity), weaker consistency guarantees, and tolerance to network partitions. We present Dapple, a distributed implementation of the FuzzyLog abstraction that stores the partial order compactly and supports efficient appends / playback via a new ordering protocol. We implement several data structures and applications over the FuzzyLog, including several map variants as well as a ZooKeeper implementation. Our evaluation shows that these applications are compact, fast, and flexible: they retain the simplicity (100s of lines of code) and strong semantics (durability and failure atomicity) of a shared log design while exploiting the partial order of the FuzzyLog for linear scalability, flexible consistency guarantees (e.g., causal+ consistency), and network partition tolerance. On a 6-node Dapple deployment, our FuzzyLogbased ZooKeeper supports 3M/sec single-key writes, and 150K/sec atomic cross-shard renames.
The selection of fusion levels in thoracic idiopathic scoliosis.

From the material and data reviewed in our study of 405 patients, it appears that postoperative correction of the thoracic spine approximately equals the correction noted on preoperative side-bending roentgenograms. Selective thoracic fusion can be safely performed on a Type-II curve of less than 80 degrees, but care must be taken to use the vertebra that is neutral and stable so that the lower level of the fusion is centered over the sacrum. The lumbar curve spontaneously corrects to balance the thoracic curve when selective thoracic fusion is performed and the lower level of fusion is properly selected. In Type-III, IV, and V thoracic curves the lower level of fusion should be centered over the sacrum to achieve a balanced, stable spine.
2-hop Blockchain : Combining Proof-of-Work and Proof-of-Stake Securely

Cryptocurrencies like Bitcoin have proven to be a phenomenal success. Bitcoin-like systems use proofof-work mechanism which is therefore considered as 1-hop blockchain, and their security holds if the majority of the computing power is under the control of honest players. However, this assumption has been seriously challenged recently and Bitcoin-like systems will fail when this assumption is broken. We propose the rst provably secure 2-hop blockchain by combining proof-of-work (rst hop) and proof-of-stake (second hop) mechanisms. On top of Bitcoin’s brilliant ideas of utilizing the power of the honest miners, via their computing resources, to secure the blockchain, we further leverage the power of the honest users/stakeholders, via their coins/stake, to achieve this goal. e security of our blockchain holds if the honest players control majority of the collective resources (which consists of both computing power and stake). at said, even if the adversary controls more than 50% computing power, the honest players still have the chance to defend the blockchain via honest stake. ∗An early version with title “Securing Bitcoin-like Blockchains against a Malicious Majority of Computing Power” appeared in ePrint Archive in July 2016. e current version shares the same motivation. But the construction idea and modeling approach have been completely revised.   Jiao Tong University. Most work done while visiting Cryptography Lab at Virginia Commonwealth University.   hszhou@vcu.edu.
Parenting stress in mothers and fathers of toddlers with autism spectrum disorders: associations with child characteristics.

Elevated parenting stress is observed among mothers of older children with autism spectrum disorders (ASD), but little is known about parents of young newly-diagnosed children. Associations between child behavior and parenting stress were examined in mothers and fathers of 54 toddlers with ASD (mean age = 26.9 months). Parents reported elevated parenting stress. Deficits/delays in children's social relatedness were associated with overall parenting stress, parent-child relationship problems, and distress for mothers and fathers. Regulatory problems were associated with maternal stress, whereas externalizing behaviors were associated with paternal stress. Cognitive functioning, communication deficits, and atypical behaviors were not uniquely associated with parenting stress. Clinical assessment of parental stress, acknowledging differences in parenting experiences for mothers and fathers of young children with ASD, is needed.
Attention estimation by simultaneous analysis of viewer and view

This paper introduces a system for estimating the attention of a driver wearing a first person view camera using salient objects to improve gaze estimation. A challenging data set of pedestrians crossing intersections has been captured using Google Glass worn by a driver. A challenge unique to first person view from cars is that the interior of the car can take up a large part of the image. The proposed system automatically filters out the dashboard of the car, along with other parts of the instrumentation. The remaining area is used as a region of interest for a pedestrian detector. Two cameras looking at the driver are used to determine the direction of the driver's gaze, by examining the eye corners and the center of the iris. This coarse gaze estimation is then linked to the detected pedestrians to determine which pedestrian the driver is focused on at any given time.
Ranging and SAR imaging of underground targets using laptop based FMCW RADAR

This paper discusses an experiment on Synthetic Aperture RADAR imaging using a portable laptop based Frequency Modulated Continuous Wave RADAR. The aim of the paper is to examine Ground Penetrating Radar data with the portable FMCW RADAR after Auto Estimation of Soil Permittivity processing. The permittivity of the soil is estimated by iterative algorithm, where the soil is considered as homogeneous. Objects buried under the grounds were detected using the FMCW RADAR and possible novel applications are discussed.
GraphP: Reducing Communication for PIM-Based Graph Processing with Efficient Data Partition

Processing-In-Memory (PIM) is an effective technique that reduces data movements by integrating processing units within memory. The recent advance of “big data” and 3D stacking technology make PIM a practical and viable solution for the modern data processing workloads. It is exemplified by the recent research interests on PIM-based acceleration. Among them, TESSERACT is a PIM-enabled parallel graph processing architecture based on Micron’s Hybrid Memory Cube (HMC), one of the most prominent 3D-stacked memory technologies. It implements a Pregel-like vertex-centric programming model, so that users could develop programs in the familiar interface while taking advantage of PIM. Despite the orders of magnitude speedup compared to DRAM-based systems, TESSERACT generates excessive crosscube communications through SerDes links, whose bandwidth is much less than the aggregated local bandwidth of HMCs. Our investigation indicates that this is because of the restricted data organization required by the vertex programming model. In this paper, we argue that a PIM-based graph processing system should take data organization as a first-order design consideration. Following this principle, we propose GraphP, a novel HMC-based software/hardware co-designed graph processing system that drastically reduces communication and energy consumption compared to TESSERACT. GraphP features three key techniques. 1) “Source-cut” partitioning, which fundamentally changes the cross-cube communication from one remote put per cross-cube edge to one update per replica. 2) “Two-phase Vertex Program”, a programming model designed for the “source-cut” partitioning with two operations: GenUpdate and ApplyUpdate. 3) Hierarchical communication and overlapping, which further improves performance with unique opportunities offered by the proposed partitioning and programming model. We evaluate GraphP using a cycle accurate simulator with 5 real-world graphs and 4 algorithms. The results show that it provides on average 1.7 speedup and 89% energy saving compared to TESSERACT.
A simple way to broaden objects search area for tracking methods based on discriminative correlation filters

We propose a simple way to broaden objects search area for tracking methods based on discriminative correlation filter using two window functions of different bandwidth. Testing at the VOT-2016 Challenge confirmed that this approach provided higher robustness and accuracy of tracking, comparing to standard realizations, where only one window function was used. We created a software implementation of tracking system based on the proposed approach and estimated its performance. The proposed software realization for PC platform and modern ARM platforms can track objects in real-time.
Sector-Based Radio Resource Allocation (SBRRA) Algorithm for Better Quality of Service and Experience in Device-to-Device (D2D) Communication

The mounting content sharing among users has resulted in a considerable rise in wireless data traffic, pressurizing the cellular networks to undergo a suitable upheaval. A competent technology of the fifth-generation (5G) networks for efficiently supporting proximity-based applications is device-to-device (D2D) communication, underlaying cellular networks. Significant advances have been made till date, for allocating resources to D2D users in cellular networks, such that sharing of spectral resources between cellular and D2D users is carried out in a coordinated manner. In this paper, a sector-based radio resource allocation (SBRRA) algorithm for resource block (RB) allocation to D2D pairs has been proposed, where the number of resource blocks (RBs) is allocated to each D2D pair in an adaptive manner, based on the demanded application by each pair. Different applications demand a varying number of RBs, in accordance with their priority. This algorithm focuses on the use of sectored antennas at the base station, for a better performance and low complexity. Extensive simulations are carried out, considering real-time scenario, for ensuring satisfactory quality of service (QoS) and quality of experience (QoE) by the users. The efficiency of the proposed scheme is proved by comparing it with the RB allocation using hidden Markov model.
Collaborating between Local and Global Learning for Distributed Online Multiple Tasks

This paper studies the novel learning scenarios of Distributed Online Multi-tasks (DOM), where the learning individuals with continuously arriving data are distributed separately and meanwhile they need to learn individual models collaboratively. It has three characteristics: distributed learning, online learning and multi-task learning. It is motivated by the emerging applications of wearable devices, which aim to provide intelligent monitoring services, such as health emergency alarming and movement recognition.
 To the best of our knowledge, no previous work has been done for this kind of problems. Thus, in this paper a collaborative learning scheme is proposed for this problem. Specifically, it performs local learning and global learning alternately. First, each client performs online learning using the increasing data locally. Then, DOM switches to global learning on the server side when some condition is triggered by clients. Here, an asynchronous online multi-task learning method is proposed for global learning. In this step, only this client's model, which triggers the global learning, is updated with the support of the difficult local data instances and the other clients' models. The experiments from 4 applications show that the proposed method of global learning can improve local learning significantly. DOM framework is effective, since it can share knowledge among distributed tasks and obtain better models than learning them separately. It is also communication efficient, which only requires the clients send a small portion of raw data to the server.
Extreme Programming and Agile Software Development Methodologies

As a stakeholder of a software project, how does this sound to you? You can have releases as often as you like. The small number of defects is unprecedented. All of the features in the system are the most valuable ones to your business. At anytime, you have access to complete, accurate information as the status of any feature and of the quality of the system as a whole. The team developing your project works in an energized space with constant communication about the project. You are not dependent on any one or even two programmers for the continued success of the project. If your needs change, the development team welcomes the change of direction. As a developer of a software project, how does this sound to you? No one estimates your tasks but you, period! You always have access to a customer to clarify details about the features you are implementing. You are free (and required) to clean up the code whenever necessary. You complete a project every two weeks. You can work in any part of the system that you wish. You can pick who will help you on any given task. You are not required to work constantly long hours. Does this sound to good to be true? Teams are achieving these advantages using a relatively new set of software methodologies. Collectively, they are referred to as Agile Software Development Methodologies. The most pervasive is Extreme Programming. This chapter will introduce you to these exciting, popular, yet controversial new approaches to software development. ____________________________________________________________________________
Power and energy capacity requirements of storages providing frequency control reserves

Due to their fast response time and high ramp rates, storage systems are capable of providing frequency control reserves. However, the limit in energy capacity poses difficulties as frequency control signals are not unbiased. We describe a scheme to recharge or discharge the storage without impeding the quality of the provided service, and formulate an analyzing method to investigate the resulting size of the storage. We show that even small storage sizes are sufficient to provide continuous and reliable primary and secondary frequency control reserves to the grid.
Reuters Tracer: A Large Scale System of Detecting & Verifying Real-Time News Events from Twitter

News professionals are facing the challenge of discovering news from more diverse and unreliable information in the age of social media. More and more news events break on social media first and are picked up by news media subsequently. The recent Brussels attack is such an example. At Reuters, a global news agency, we have observed the necessity of providing a more effective tool that can help our journalists to quickly discover news on social media, verify them and then inform the public.
 In this paper, we describe Reuters Tracer, a system for sifting through all noise to detect news events on Twitter and assessing their veracity. We disclose the architecture of our system and discuss the various design strategies that facilitate the implementation of machine learning models for noise filtering and event detection. These techniques have been implemented at large scale and successfully discovered breaking news faster than traditional journalism
A Procedure for Quantitatively Comparing the Syntactic Coverage of English Grammars

The problem of quantitatively comparing tile performance of different broad-coverage grammars of English has to date resisted solution. Prima facie, known English grammars appear to disagree strongly with each other as to the elements of even tile simplest sentences. For instance, the grammars of Steve Abney (Bellcore), Ezra Black (IBM), Dan Flickinger (IIewlett Packard), Claudia Gdaniec (Logos), Ralph Grishman and Tomek Strzalkowski (NYU), Phil Harrison (Boeing), Don tfindle (AT&T), Bob Ingria (BBN), and Mitch Marcus (U. of Pennsylvania) recognize in common only the following constituents, when each grammarian provides the single parse which he/she would ideally want his/her grammar to specify for three sample Brown Corpus sentences: The famed Yankee Clipper, now retired, has been assisting (as (a batting coach)). One of those cai)ital-gains ventures, ill fact, has saddled him (with Gore Court). lie said this constituted a (very serious) misuse (of the (Criminal court) processes).
The development of cross-language plagiarism detection tool utilising fuzzy swarm-based summarisation

This work presents the design and development of a web-based system that supports cross-language similarity analysis and plagiarism detection. A suspicious document dq in a language Lq is to be submitted to the system via a PHP web-based interface. The system will accept the text through either uploading or pasting it directly to a text-area. In order to lighten large texts and provide an ideal set of queries, we introduce the idea of query document reduction via summarisation. Our proposed system utilised a fuzzy swarm-based summarisation tool originally built in Java. Then, the summary is used as a query to find similar web resources in languages Lx other than Lq via a dictionary-based translation. Thereafter, a detailed similarity analysis across the languages Lq and Lx is performed and friendly report of results is produced. Such report has global similarity score on the whole document, which assures high flexibility of utilisation.
Design of Electronic Throttle Valve Position Control System using Nonlinear PID Controller

In recent years, the use of electronic throttle valve systems has been very popular in the automotive industry. It is used to regulate the amount of air flow into the engine. Due to the existence of multiple nonsmooth nonlinearities, the controller design to the electronic throttle valve becomes difficult task. These nonlinearities including stick–slip friction, backlash, and a discontinuous nonlinear spring involved in the system. In the first part of this paper the electronic throttle valve system is presented first, and then the model is derived for each components of the throttle valve system. Later, the system dimension is reduced to two by ignoring the motor inductance at the end of this part of work. Actually this step enables us to design a nonlinear PID controller electronic throttle valve system. The simulation results, of applying a nonlinear PID controller to the electronic throttle valve system, show the effectiveness of the proposed controller in forcing the angle of the throttle valve to the desired opening angle in presence of nonlinearities and disturbances in throttle valve system model.
Features selection of cotton disease leaves image based on fuzzy feature selection techniques

In the research of identifying and diagnosing cotton disease using computer vision intellectively in the agriculture, feature selection is a key question in pattern recognition and affects the design and performance of the classifier. In this paper, the fuzzy feature selection approach - fuzzy curves (FC) and surfaces (FS) - is proposed to select features of cotton disease leaves image. In order to get best information for diagnosing and identifying, a subset of independent significant features is identified exploiting the fuzzy feature selection approach. Firstly, utilize FC to automatically and quickly isolate a small set of significant features from the set of original features according to their significance and eliminate spurious features; then, use FS to get rid of the features dependent on the significant features. This approach reduces the dimensionality of the feature space so that lead to a simplified classification scheme appropriate for practical classification applications. The results show that the effectiveness of features selected by the FC and FS method is much better than that selected by human randomly or other methods.