nils-herrmann/clean_scirepeval huggingface dataset:
A MINI UNMANNED AERIAL VEHICLE ( UAV ) : SYSTEM OVERVIEW AND IMAGE ACQUISITION

In the last years UAV (Unmanned Aerial Vehicle)-systems became relevant for applications in precision farming and in infrastructure maintenance, like road maintenance and dam surveillance. This paper gives an overview about UAV (Unmanned Aerial Vehicle) systems and their application for photogrammetric recording and documentation of cultural heritage. First the historical development of UAV systems and the definition of UAV-helicopters will be given. The advantages of a photogrammetric system on-board a model helicopter will be briefly discussed and compared to standard aerial and terrestrial photogrammetry. UAVs are mostly low cost systems and flexible and therefore a suitable alternative solution compared to other mobile mapping systems. A mini UAV-system was used for photogrammetric image data acquisition near Palpa in Peru. A settlement from the 13 century AD, which was presumably used as a mine, was flown with a model helicopter. Based on the image data, an accurate 3D-model will be generated in the future. With an orthophoto and a DEM derived from aerial images in a scale of 1:7 000, a flight planning was build up. The determined flying positions were implemented in the flight control system. Thus, the helicopter is able to fly to predefined pathpoints automatically. Tests in Switzerland and the flights in Pinchango Alto showed that using the built-in GPS/INSand stabilization units of the flight control system, predefined positions could be reached exactly to acquire the images. The predicted strip crossings and flying height were kept accurately in the autonomous flying mode.
A survey of hard real-time scheduling for multiprocessor systems

This survey covers hard real-time scheduling algorithms and schedulability analysis techniques for homogeneous multiprocessor systems. It reviews the key results in this field from its origins in the late 1960s to the latest research published in late 2009. The survey outlines fundamental results about multiprocessor real-time scheduling that hold independent of the scheduling algorithms employed. It provides a taxonomy of the different scheduling methods, and considers the various performance metrics that can be used for comparison purposes. A detailed review is provided covering partitioned, global, and hybrid scheduling algorithms, approaches to resource sharing, and the latest results from empirical investigations. The survey identifies open issues, key research challenges, and likely productive research directions.
An effect analysis of industry 4.0 to higher education

From history to the present day, especially in the field of technology is provided a wide range of developments. The most important of these developments has achieved the realization of the industrial revolution, has led to play a leading role in the production is done by human beings. The effects on production of industry 4.0 emerging with this mind is very important. The qualified employees should be trained to make the necessary preparations for the company in this period, it is experiencing the fourth industrial revolution. Therefore, the impacts on higher education of industry 4.0 are examined in this paper. The importance in education of industry 4.0 has revealed with statistical data presented in this study.
Perceptual Organization in User-Generated Graph Layouts

Many graph layout algorithms optimize visual characteristics to achieve useful representations. Implicitly, their goal is to create visual representations that are more intuitive to human observers. In this paper, we asked users to explicitly manipulate nodes in a network diagram to create layouts that they felt best captured the relationships in the data. This allowed us to measure organizational behavior directly, allowing us to evaluate the perceptual importance of particular visual features, such as edge crossings and edge-lengths uniformity. We also manipulated the interior structure of the node relationships by designing data sets that contained clusters, that is, sets of nodes that are strongly interconnected. By varying the degree to which these clusters were ldquomaskedrdquo by extraneous edges we were able to measure observerspsila sensitivity to the existence of clusters and how they revealed them in the network diagram. Based on these measurements we found that observers are able to recover cluster structure, that the distance between clusters is inversely related to the strength of the clustering, and that users exhibit the tendency to use edges to visually delineate perceptual groups. These results demonstrate the role of perceptual organization in representing graph data and provide concrete recommendations for graph layout algorithms.
Electroporation of Cells and Tissues

Electrical pulses that cause the transmembrane voltage of fluid lipid bilayer membranes to reach at least 0 2 V, usually 0.5–1 V, are hypothesized to create primary membrane “pores” with a minimum radius of ∼1 nm. Transport of small ions such as Na and Cl through a dynamic pore population discharges the membrane even while an external pulse tends to increase , leading to dramatic electrical behavior. Molecular transport through primary pores and pores enlarged by secondary processes provides the basis for transporting molecules into and out of biological cells. Cell electroporationin vitro is used mainly for transfection by DNA introduction, but many other interventions are possible, including microbial killing. Ex vivo electroporation provides manipulation of cells that are reintroduced into the body to provide therapy. In vivo electroporation of tissues enhances molecular transport through tissues and into their constituative cells. Tissue electroporation, by longer, large pulses, is involved in electrocution injury. Tissue electroporation by shorter, smaller pulses is under investigation for biomedical engineering applications of medical therapy aimed at cancer treatment, gene therapy, and transdermal drug delivery. The latter involves a complex barrier containing both high electrical resistance, multilamellar lipid bilayer membranes and a tough, electrically invisible protein matrix.
Pairwise Relation Classification with Mirror Instances and a Combined Convolutional Neural Network

Relation classification is the task of classifying the semantic relations between entity pairs in text. Observing that existing work has not fully explored using different representations for relation instances, especially in order to better handle the asymmetry of relation types, in this paper, we propose a neural network based method for relation classification that combines the raw sequence and the shortest dependency path representations of relation instances and uses mirror instances to perform pairwise relation classification. We evaluate our proposed models on two widely used datasets: SemEval-2010 Task 8 and ACE-2005. The empirical results show that our combined model together with mirror instances achieves the state-of-the-art results on both datasets.
Why do you play World of Warcraft? An in-depth exploration of self-reported motivations to play online and in-game behaviours in the virtual world of Azeroth

Massively multiplayer online role-playing games (MMORPGs) are video games in which players create an avatar that evolves and interacts with other avatars in a persistent virtual world. Motivations to play MMORPGs are heterogeneous (e.g. achievement, socialisation, immersion in virtual worlds). This study investigates in detail the relationships between self-reported motives and actual in-game behaviours. We recruited a sample of 690 World of Warcraft players (the most popular MMORPG) who agreed to have their avatar monitored for 8 months. Participants completed an initial online survey about their motives to play. Their actual in-game behaviours were measured through the game’s official database (the Armory website). Results showed specific associations between motives and in-game behaviours. Moreover, longitudinal analyses revealed that teamworkand competition-oriented motives are the most accurate predictors of fast progression in the game. In addition, although specific associations exist between problematic use and certain motives (e.g. advancement, escapism), longitudinal analyses showed that high involvement in the game is not necessarily associated with a negative impact upon daily living.
A ug 2 01 7 Reinforced Video Captioning with Entailment Rewards

Sequence-to-sequence models have shown promising improvements on the temporal task of video captioning, but they optimize word-level cross-entropy loss during training. First, using policy gradient and mixed-loss methods for reinforcement learning, we directly optimize sentence-level task-based metrics (as rewards), achieving significant improvements over the baseline, based on both automatic metrics and human evaluation on multiple datasets. Next, we propose a novel entailment-enhanced reward (CIDEnt) that corrects phrase-matching based metrics (such as CIDEr) to only allow for logically-implied partial matches and avoid contradictions, achieving further significant improvements over the CIDEr-reward model. Overall, our CIDEnt-reward model achieves the new state-of-the-art on the MSR-VTT dataset.
Kinematics and design of a portable and wearable exoskeleton for hand rehabilitation

We present the kinematic design and actuation mechanics of a wearable exoskeleton for hand rehabilitation of post-stroke. Our design method is focused on achieving maximum safety, comfort and reliability in the interaction, and allowing different users to wear the device with no manual regulations. In particular, we propose a kinematic and actuation solution for the index finger flexion/extension, which leaves full movement freedom on the abduction-adduction plane. This paper presents a detailed kineto-static analysis of the system and a first prototype of the device.
A personalized collaborative Digital Library environment: a model and an application

The Web, and consequently the information contained in it, is growing rapidly. Every day a huge amount of newly created information is electronically published in Digital Libraries, whose aim is to satisfy the users’ information needs. In this paper, we envisage a Digital Library not only as an information resource where users may submit queries to satisfy their daily information need, but also as a collaborative working and meeting space of people sharing common interests. Indeed, we will present a personalized collaborative Digital Library environment, where users may organize the information space according to their own subjective view, may build communities, may become aware of each other, exchange information and knowledge with other users, and may get recommendations based on preference patterns of users.
Self-Confidence and Baseball Performance : A Causal Examination of Self-Efficacy Theory

Using path analytic-techniques, the causal relationships in Bandura's model of self-efficacy were examined in a field setting. Male intercollegiate and interscholastic baseball players (N = 53) completed self-report measures over a nine-game period during the baseball season. Perceptions of self-efficacy, competitive state anxiety, effort expenditure, and objective hitting performance were measured. Moderate support for Bandura's model was found in that higher performances predicted stronger percepts of efficacy in six games, and lower levels of somatic and cognitive anxiety were associated with stronger self-efficacy beliefs in seven games. In turn, stronger self-efficacy predicted greater effort in six games and higher hitting performance in five games. Results are discussed in relation to the ecological validity of previous causal examinations of self-efficacy theory, as well as the utility of selfefficacy theory as a framework for investigating the self-confidenceperformance relationship.
Device analyzer: largescale mobile data collection

We collected usage information from 12,500 Android devices in the wild over the course of nearly 2 years. Our dataset contains 53 billion data points from 894 models of devices running 687 versions of Android. Processing the collected data presents a number of challenges ranging from scalability to consistency and privacy considerations. We present our system architecture for collection and analysis of this highly-distributed dataset, discuss how our system can reliably collect time-series data in the presence of unreliable timing information, and discuss issues and lessons learned that we believe apply to many other big data collection projects.
Running With an Elastic Lower Limb Exoskeleton.

Although there have been many lower limb robotic exoskeletons that have been tested for human walking, few devices have been tested for assisting running. It is possible that a pseudo-passive elastic exoskeleton could benefit human running without the addition of electrical motors due to the spring-like behavior of the human leg. We developed an elastic lower limb exoskeleton that added stiffness in parallel with the entire lower limb. Six healthy, young subjects ran on a treadmill at 2.3 m/s with and without the exoskeleton. Although the exoskeleton was designed to provide ~50% of normal leg stiffness during running, it only provided 24% of leg stiffness during testing. The difference in added leg stiffness was primarily due to soft tissue compression and harness compliance decreasing exoskeleton displacement during stance. As a result, the exoskeleton only supported about 7% of the peak vertical ground reaction force. There was a significant increase in metabolic cost when running with the exoskeleton compared with running without the exoskeleton (ANOVA, P < .01). We conclude that 2 major roadblocks to designing successful lower limb robotic exoskeletons for human running are human-machine interface compliance and the extra lower limb inertia from the exoskeleton.
A survey on device-to-device (D2D) communication: Architecture and security issues

The number of devices is expected to radically increase in near future, with an estimate of above 50 billion connected devices by 2020. The subscribers demand improved data rates, with reduced latency and increased system capacity. To endure the rising demands, cellular networks need to undergo suitable changes. For fulfillment of the rising needs of users and efficient utilization of the available scarce resources, device-to-device (D2D) communication is being looked upon as an important emerging technology for present and future cellular networks. It allows peer-to-peer communication between users, with improved spectral efficiency, energy efficiency and system throughput. In this paper, a detailed survey on device-to-device (D2D) communications has been offered, along with the challenges which exist for D2D (like resource allocation, security, interference management etc.) to become a successful paradigm of wireless networks. In order to fulfill the subscriber needs, architecture has been proposed which assures overcoming the various implementation challenges of D2D communication. The paper largely focuses on security in D2D communication and the possible attacks to which the direct links are susceptible to. For ensuring a secure D2D communication, solution has been proposed, based upon Internet Protocol Security (IP Sec).
A Low-Voltage 5-GHz Quadrature Up-Conversion Mixer for Wireless Transmitter

In this paper, a low-voltage CMOS quadrature up-conversion mixer for 5-GHz wireless communication applications is designed. The simulation results demonstrate the mixer can reach a high conversion gain (CG), a low noise figure (NT), and a high linearity (IIP3). A miniature lumped- element microwave broadband rat-race hybrid and RLC shift network are used for the LO and the IF port design, respectively. The mixer exhibits a 3 dB improvement in noise and conversion gain, and the image rejection is -35 dBc. The mixer achieves noise figure of 12.8 dB, a conversion gain of 15 dB, an output third intercept point at 0 dBm, while dissipating 15 mW for operating voltage at 1 V. The mixer is designed with TSMC 0.18 um process.
Can the Elephants Handle the NoSQL Onslaught?

In this new era of “big data”, traditional DBMSs are under attack from two sides. At one end of the spectrum, the use of document store NoSQL systems (e.g. MongoDB) threatens to move modern Web 2.0 applications away from traditional RDBMSs. At the other end of the spectrum, big data DSS analytics that used to be the domain of parallel RDBMSs is now under attack by another class of NoSQL data analytics systems, such as Hive on Hadoop. So, are the traditional RDBMSs, aka “big elephants”, doomed as they are challenged from both ends of this “big data” spectrum? In this paper, we compare one representative NoSQL system from each end of this spectrum with SQL Server, and analyze the performance and scalability aspects of each of these approaches (NoSQL vs. SQL) on two workloads (decision support analysis and interactive data-serving) that represent the two ends of the application spectrum. We present insights from this evaluation and speculate on potential trends for the future.
Discovering Business Rules in Knowledge-Intensive Processes Through Decision Mining: An Experimental Study

Decision mining allows discovering rules that constraint the paths that the instances of a business process may follow during its execution. In Knowl‐ edge-intensive Processes (KiP), the discovery of such rules is a great challenge because they lack structure. In this context, this experimental study applies a decision mining technique in an event log of a real company that provides ICT infrastructure services. The log comprises structured data (ticket events) and nonstructured data (messages exchanged among team members). The goal was to discover tacit decisions that could be potentially declared as business rules for the company. In addition to mining the decision points, we validated the discov‐ ered rule with the company w.r.t. their meaning.
Model predictive hovering-translation control of an unmanned Tri-TiltRotor

The experimental translational hovering control of a Tri-TiltRotor Unmanned Aerial Vehicle is the subject of this paper. This novel UAV is developed to possess the capability to perform autonomous conversion between the Vertical Take-Off and Landing, and the Fixed-Wing flight modes. Via this design's implemented features however, the capability for additional control authority on the UAV's longitudinal translational motion arises: The rotor-tilting servos are utilized in performing thrust vectoring of the main rotors, thus exploiting their fast response characteristics in directly providing translation-controlling forces. The system's hovering translation is handled by a Model Predictive Control scheme, following the aforementioned actuation principles. While performing experimental studies of the overall controlled system's efficiency, the advantageous effects of this novel control authority are clearly noted. Additionally, in this article the considerations and requirements for operational autonomy-related on-board-only state estimation are addressed.
Monadic Parsing in Haskell

This paper is a tutorial on defining recursive descent parsers in Haskell. In the spirit of one-stop shopping , the paper combines material from three areas into a single source. The three areas are functional parsers (Burge, 1975; Wadler, 1985; Hutton, 1992; Fokker, 1995), the use of monads to structure functional programs (Wadler, 1990, ), and the use of special syntax for monadic programs in Haskell (Jones, 1995; Peterson et al., 1996). More specifically, the paper shows how to define monadic parsers using do notation in Haskell. Of course, recursive descent parsers defined by hand lack the efficiency of bottomup parsers generated by machine (Aho et al., 1986; Mogensen, 1993; Gill and Marlow, 1995). However, for many research applications, a simple recursive descent parser is perfectly sufficient. Moreover, while parser generators typically offer a fixed set of combinators for describing grammars, the method described here is completely extensible: parsers are first-class values, and we have the full power of Haskell available to define new combinators for special applications. The method is also an excellent illustration of the elegance of functional programming. The paper is targeted at the level of a good undergraduate student who is familiar with Haskell, and has completed a grammars and parsing course. Some knowledge of functional parsers would be useful, but no experience with monads is assumed. A Haskell library derived from the paper is available on the web from:
Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization.

Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts.
DynamicFusion: Reconstruction and tracking of non-rigid scenes in real-time

We present the first dense SLAM system capable of reconstructing non-rigidly deforming scenes in real-time, by fusing together RGBD scans captured from commodity sensors. Our DynamicFusion approach reconstructs scene geometry whilst simultaneously estimating a dense volumetric 6D motion field that warps the estimated geometry into a live frame. Like KinectFusion, our system produces increasingly denoised, detailed, and complete reconstructions as more measurements are fused, and displays the updated model in real time. Because we do not require a template or other prior scene model, the approach is applicable to a wide range of moving objects and scenes.