nils-herrmann/clean_scirepeval huggingface dataset:
FingerSound: Recognizing unistroke thumb gestures using a ring

We introduce FingerSound, an input technology to recognize unistroke thumb gestures, which are easy to learn and can be performed through eyes-free interaction. The gestures are performed using a thumb-mounted ring comprising a contact microphone and a gyroscope sensor. A K-Nearest-Neighbor(KNN) model with a distance function of Dynamic Time Warping (DTW) is built to recognize up to 42 common unistroke gestures. A user study, where the real-time classification results were given, shows an accuracy of 92%-98% by a machine learning model built with only 3 training samples per gesture. Based on the user study results, we further discuss the opportunities, challenges and practical limitations of FingerSound when deploying it to real-world applications in the future.
Just-In-Time Code Reuse: On the Effectiveness of Fine-Grained Address Space Layout Randomization

Fine-grained address space layout randomization (ASLR) has recently been proposed as a method of efficiently mitigating runtime attacks. In this paper, we introduce the design and implementation of a framework based on a novel attack strategy, dubbed just-in-time code reuse, that undermines the benefits of fine-grained ASLR. Specifically, we derail the assumptions embodied in fine-grained ASLR by exploiting the ability to repeatedly abuse a memory disclosure to map an application's memory layout on-the-fly, dynamically discover API functions and gadgets, and JIT-compile a target program using those gadgets -- all within a script environment at the time an exploit is launched. We demonstrate the power of our framework by using it in conjunction with a real-world exploit against Internet Explorer, and also provide extensive evaluations that demonstrate the practicality of just-in-time code reuse attacks. Our findings suggest that fine-grained ASLR may not be as promising as first thought.
A Survey of Empirical Studies of Conflict

Conflict is a common phenomenon in interactions both between individuals, and between groups of individuals. As CSCW is concerned with the design of systems to support such interactions, an examination of conflict, and the various ways of dealing with it, would clearly be of benefit. This chapter surveys the literature that is most relevant to the CSCW community, covering many disciplines that have addressed particular aspects of conflict. The chapter is organised around a series of assertions, representing both commonly held beliefs about conflict, and hypotheses and theories drawn from the literature. In many cases no definitive statement can be made about the truth or falsity of an assertion: the empirical evidence both supporting and opposing is examined, and pointers are provided to further discussion in the literature. One advantage of organising the survey in this way is that it need not be read in order. Each assertion forms a self-contained essay, with cross-references to related assertions. Hence, treat the chapter as a resource to be dipped into rather than read in sequence. This introduction sets the scene by defining conflict, and providing a rationale for studying conflict in relation to CSCW. The assertions are presented in section 2, and form the main body of the chapter. Finally, section 3 relates the assertions to current work on CSCW systems.
CELF++: optimizing the greedy algorithm for influence maximization in social networks

Kempe et al.  (KKT) showed the problem of influence maximization is NP-hard and a simple greedy algorithm guarantees the best possible approximation factor in PTIME. However, it has two major sources of inefficiency. First, finding the expected spread of a node set is #P-hard. Second, the basic greedy algorithm is quadratic in the number of nodes. The first source is tackled by estimating the spread using Monte Carlo simulation or by using heuristics[4, 6, 2, 5, 1, 3]. Leskovec et al. proposed the CELF algorithm for tackling the second. In this work, we propose CELF++ and empirically show that it is 35-55% faster than CELF.
Time and sample efficient discovery of Markov blankets and direct causal relations

Mining with Bayesian Network learning has two important characteristics: under conditions learned edges between variables correspond to casual influences, and second, for every variable T in the network a special subset (Markov Blanket) identifiable by the network is the minimal variable set required to predict T. However, all known algorithms learning a complete BN do not scale up beyond a few hundred variables. On the other hand, all known sound algorithms learning a local region of the network require an exponential number of training instances to the size of the learned region.The contribution of this paper is two-fold. We introduce a novel local algorithm that returns all variables with direct edges to and from a target variable T as well as a local algorithm that returns the Markov Blanket of T. Both algorithms (i) are sound, (ii) can be run efficiently in datasets with thousands of variables, and (iii) significantly outperform in terms of approximating the true neighborhood previous state-of-the-art algorithms using only a fraction of the training size required by the existing methods. A fundamental difference between our approach and existing ones is that the required sample depends on the generating graph connectivity and not the size of the local region; this yields up to exponential savings in sample relative to previously known algorithms. The results presented here are promising not only for discovery of local causal structure, and variable selection for classification, but also for the induction of complete BNs.
New Digital-Controlled Technique for Battery Charger With Constant Current and Voltage Control Without Current Feedback

The main theme of this paper is to present a new digital-controlled technique for battery charger to achieve constant current and voltage control while not requiring current feedback. The basic idea is to achieve constant current charging control by limiting the duty cycle of charger. Therefore, the current feedback signal is not required and thereby reducing the cost of A/D converter, current sensor, and computation complexity required for current control. Moreover, when the battery voltage is increased to the preset voltage level using constant current charge, the charger changes the control mode to constant voltage charge. A digital-controlled charger is designed and implemented for uninterrupted power supply (UPS) applications. The charger control is based upon the proposed control method in software. As a result, the UPS control, including boost converter, charger, and inverter control can be realized using only one low cost MCU. Experimental results demonstrate that the effectiveness of the design and implementation.
Implementation Aspects of Channel Estimation for 3GPP LTE Terminals

In this paper, hardware implementation aspects of the channel estimator in 3GPP LTE terminals are investigated. A channel estimation ASIC, which handles the real-time channel estimation, is presented. Compared to traditional correlatorbased channel estimators, the channel estimator presented boosts the throughput at feasible silicon cost by adopting a recently proposed estimation method named Approximate Linear Minimum Mean Square Error (ALMMSE). In this paper, both the architecture and VLSI implementation of the estimator are elaborated. Implemented using a 65nm CMOS process, the channel estimator supports the full 20MHz bandwidth of 3GPP LTE and consumes only 49kgates.  Johan Eilert is now with ST_Ericsson AT AB, Lund, Sweden
Large-scale joint map matching of GPS traces

We present a robust method for solving the map matching problem exploiting massive GPS trace data. Map matching is the problem of determining the path of a user on a map from a sequence of GPS positions of that user --- what we call a trajectory. Commonly obtained from GPS devices, such trajectory data is often sparse and noisy. As a result, the accuracy of map matching is limited due to ambiguities in the possible routes consistent with trajectory samples. Our approach is based on the observation that many regularity patterns exist among common trajectories of human beings or vehicles as they normally move around. Among all possible connected k-segments on the road network (i.e., consecutive edges along the network whose total length is approximately k units), a typical trajectory collection only utilizes a small fraction. This motivates our data-driven map matching method, which optimizes the projected paths of the input trajectories so that the number of the k-segments being used is minimized. We present a formulation that admits efficient computation via alternating optimization. Furthermore, we have created a benchmark for evaluating the performance of our algorithm and others alike. Experimental results demonstrate that the proposed approach is superior to state-of-art single trajectory map matching techniques. Moreover, we also show that the extracted popular k-segments can be used to process trajectories that are not present in the original trajectory set. This leads to a map matching algorithm that is as efficient as existing single trajectory map matching algorithms, but with much improved map matching accuracy.
American Society for Quality Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter Author ( s ) : Gene

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Scientific software production: incentives and collaboration

Software plays an increasingly critical role in science, including data analysis, simulations, and managing workflows. Unlike other technologies supporting science, software can be copied and distributed at essentially no cost, potentially opening the door to unprecedented levels of sharing and collaborative innovation. Yet we do not have a clear picture of how software development for science fits into the day-to-day practice of science, or how well the methods and incentives of its production facilitate realization of this potential. We report the results of a multiple-case study of software development in three fields: high energy physics, structural biology, and microbiology. In each case, we identify a typical publication, and use qualitative methods to explore the production of the software used in the science represented by the publication. We identify several different production systems, characterized primarily by differences in incentive structures. We identify ways in which incentives are matched and mismatched with the needs of the science fields, especially with respect to collaboration.
Aero Quarterly Qtr_04 | 07 787 No-bleed Systems: Saving Fuel and Enhancing Operational Efficiencies

The Boeing 787 Dreamliner features a unique systems architecture that offers numerous advantages to operators. The new airplane's use of electrical systems reduces fuel usage and increases operational efficiency. the primary differentiating factor in the systems architecture of the 787 is its emphasis on electrical systems, which replace most of the pneumatic systems found on traditional com­ mercial airplanes. one of the advantages of the no­bleed electri­ cal systems architecture is the greater efficiency gained in terms of reduced fuel burn — the 787 systems architecture accounts for predicted fuel savings of about 3 percent. the 787 also offers operators operational efficiencies due to the advantages of electrical systems compared to pneumatic systems in terms of weight and reduced lifecycle costs. this article explores the 787's no­bleed systems architecture and explains how the airplane's efficiencies are realized. reasons Behind the Move to a More eleCtriC airplane recent advances in technology have allowed boeing to incorporate a new no­bleed systems architecture in the 787 that eliminates the traditional pneumatic system and bleed manifold and converts the power source of most functions formerly powered by bleed air to electric power (for example, the air­conditioning packs and wing anti­ ice systems). the no­bleed systems architecture offers operators a number of benefits, including: ■ improved fuel consumption, due to a more efficient secondary power extraction, transfer, and usage. ■ reduced maintenance costs, due to elimination of the maintenance­intensive bleed system. ■ improved reliability due to the use of modern power electronics and fewer components in the engine installation. ■ expanded range and reduced fuel consumption due to lower overall weight. ■ reduced maintenance costs and improved reliability because the architecture uses fewer parts than previous systems. the 787's no­bleed systems architecture will allow the airplane's engines to produce thrust more efficiently — all of the high­speed air pro­ duced by the engines goes to thrust. pneumatic systems that divert high­speed air from the engines rob conventional airplanes of some thrust and increase the engine's fuel consumption. boeing believes that using electrical power is more efficient than engine­generated pneumatic power, and expects the new architecture to extract as much as 35 percent less power from the engines. conventional pneumatic systems generally develop more power than is needed in most conditions, causing excess energy to be dumped overboard.
The OO-method approach for information systems modeling: from object-oriented conceptual modeling to automated programming

Current and future (conventional) notations used in Conceptual Modeling Techniques should have a precise (formal) semantics to provide a well-defined software development process, in order to go from specification to implementation in an automated way. To achieve this objective, the OO-Method approach to Information Systems Modeling presented in this paper attempts to overcome the conventional (informal)/formal dichotomy by selecting the best ideas from both approaches. The OO-Method makes a clear distinction between the problem space (centered on what the system is) and the solution space (centered on how it is implemented as a software product). It provides a precise, conventional graphical notation to obtain a system description at the problem space level, however this notation is strictly based on a formal OO specification language that determines the conceptual modeling constructs needed to obtain the system specification. An abstract execution model determines how to obtain the software representations corresponding to these conceptual modeling constructs. In this way, the final software product can be obtained in an automated way. r 2001
Behavior-based malware detection system for the Android platform

Malware in smartphones is growing at a signi cant rate. There are currently more than 250 million smartphone users in the world and this number is expected to grow in coming years [44]. In the past few years, smartphones have evolved from simple mobile phones into sophisticated computers. This evolution has enabled smartphone users to access and browse the Internet, to receive and send emails, SMS and MMS messages and to connect devices in order to exchange information. All of these features make the smartphone a useful tool in our daily lives, but at the same time they render it more vulnerable to attacks by malicious applications. Given that most users store sensitive information on their mobile phones, such as phone numbers, SMS messages, emails, pictures and videos, smartphones are a very appealing target for attackers and malware developers. The need to maintain security and data con dentiality on the Android platform makes the analysis of malware on this platform an urgent issue. We have based this report on previous approaches to the dynamic analysis of application behavior, and have adapted one approach in order to detect malware on the Android platform. The detector is embedded in a framework to collect traces from a number of real users and is based on crowdsourcing. Our framework has been tested by analyzing data collected at the central server using two types of data sets: data from arti cial malware created for test purposes and data from real malware found in the wild. The method used is shown to be an e ective means of isolating malware and alerting users of downloaded malware, which suggests that it has great potential for helping to stop the spread of detected malware to a larger community. Finally, the report will give a complete review of results for self written and real Android Malware applications that have been tested with the system. This thesis project shows that it is feasible to create an Android malware detection system with satisfactory results.
A Compact Frequency-Reconfigurable Metamaterial-Inspired Antenna

Adding frequency reconfigurability to a compact metamaterial-inspired antenna is investigated. The antenna is a printed monopole with an incorporated slot and is fed by a coplanar waveguide (CPW) line. This antenna was originally inspired from the concept of negative-refractive-index metamaterial transmission lines and exhibits a dual-band behavior. By using a varactor diode, the lower band (narrowband) of the antenna, which is due to radiation from the incorporated slot, can be tuned over a broad frequency range, while the higher band (broadband) remains effectively constant. A detailed equivalent circuit model is developed that predicts the frequency-tuning behavior for the lower band of the antenna. The circuit model shows the involvement of both CPW even and odd modes in the operation of the antenna. Experimental results show that, for a varactor diode capacitance approximately ranging from 0.1-0.7 pF, a tuning range of 1.6-2.23 GHz is achieved. The size of the antenna at the maximum frequency is 0.056 λ0 × 0.047 λ0 and the antenna is placed over a 0.237 λ0 × 0.111 λ0 CPW ground plane (λ0 being the wavelength in vacuum).
Security in wireless sensor networks

Recent advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks that consist of many low-power, low-cost, and small-size sensor nodes. Sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. Security is critical for many sensor network applications, such as military target tracking and security monitoring. To provide security and privacy to small sensor nodes is challenging, due to the limited capabilities of sensor nodes in terms of computation, communication, memory/storage, and energy supply. In this article we survey the state of the art in research on sensor network security.
GPU-based parallel collision detection for fast motion planning

We present parallel algorithms to accelerate collision queries for sample-based motion planning. Our approach is designed for current many-core GPUs and exploits data-parallelism and multithreaded capabilities. In order to take advantage of high numbers of cores, we present a clustering scheme and collision-packet traversal to perform efficient collision queries on multiple configurations simultaneously. Furthermore, we present a hierarchical traversal scheme that performs workload balancing for high parallel efficiency. We have implemented our algorithms on commodity NVIDIA GPUs using CUDA and can perform 500, 000 collision queries per second on our benchmarks, which is 10X faster than prior GPU-based techniques. Moreover, we can compute collisionfree paths for rigid and articulated models in less than 100 milliseconds for many benchmarks, almost 50-100X faster than current CPU-based PRM planners.
A variable stiffness joint using leaf springs for robot manipulators

Safety of a manipulator designed to be used at home requires different approach than industrial robots, where safety is achieved mainly by decreasing the interaction with humans. Robots for applications at home, however, require frequent interaction with humans. Introducing compliant component gives the answer to the safety issue at the cost of performance degradation. In order to reduce the performance degradation, manipulators equipped with variable stiffness have been studied by many researchers. This paper presents a variable stiffness joint(VSJ) designed for a robot manipulator. The stiffness is generated by leaf springs and two actuators are used to control the position and stiffness of the joint. Changing the effective length of the spring results in change in stiffness. The position of the joint is controlled via rotating two actuators at the same speed in the same direction. The stiffness is controlled when the two actuators rotate in the different speed. Experiments are conducted to show that the position and stiffness are controlled independent with each other and having less stiffness at the joint helps in making unexpected collision with object safer.
Threshold compression for 3G scalable monitoring

We study the problem of scalable monitoring of operational 3G wireless networks. Threshold-based performance monitoring in large 3G networks is very challenging for two main factors: large network scale and dynamics in both time and spatial domains. A fine-grained threshold setting (e.g., perlocation hourly) incurs prohibitively high management complexity, while a single static threshold fails to capture the network dynamics, thus resulting in unacceptably poor alarm quality (up to 70% false/miss alarm rates). In this paper, we propose a scalable monitoring solution, called threshold-compression that can characterize the location- and time-specific threshold trend of each individual network element (NE) with minimal threshold setting. The main insight is to identify groups of NEs with similar threshold behaviors across location and time dimensions, forming spatial-temporal clusters to reduce the number of thresholds while maintaining acceptable alarm accuracy in a large-scale 3G network. Our evaluations based on the operational experience on a commercial 3G network have demonstrated the effectiveness of the proposed solution. We are able to reduce the threshold setting up to 90% with less than 10% false/miss alarms.
An Annotated Dataset for Extracting Definitions and Hypernyms from the Web

This paper presents and analyzes an annotated corpus of definitions, created to train an algorithm for the automatic extraction of definitions and hypernyms from Web documents. As an additional resource, we also include a corpus of non-definitions with syntactic patterns similar to those of definition sentences, e.g.: “An android is a robot” vs. “Snowcap is unmistakable”. Domain and style independence is obtained thanks to the annotation of a sample of the Wikipedia corpus and to a novel pattern generalization algorithm based on wordclass lattices (WCL). A lattice is a directed acyclic graph (DAG), a subclass of nondeterministic finite state automata (NFA). The lattice structure has the purpose of preserving the salient differences among distinct sequences, while eliminating redundant information. The WCL algorithm will be integrated into an improved version of the GlossExtractor Web application (Velardi et al., 2008). This paper is mostly concerned with a description of the corpus, the annotation strategy, and a linguistic analysis of the data. A summary of the WCL algorithm is also provided for the sake of completeness.