nils-herrmann/clean_scirepeval huggingface dataset:
Strategic sensemaking and organizational performance: linkages among scanning, interpretation, action, and outcomes.

This study investigated the strategic "sensemaking" processes of scanning, interpretation, and action and how those activities are linked to organizational performance. Using path analyses on data from 156 hospitals, we tested the direct and indirect effects among these sensemaking processes and performance outcomes and developed a model of their relationships. In a more general sense, the research represents an attempt to provide insight not only into relationships between cognition and action, but also into the links between those fundamental processes and organizational performance outcomes.
Generalized Boosted Models : A guide to the gbm package

Boosting takes on various forms with different programs using different loss functions, different base models, and different optimization schemes. The gbm package takes the approach described in  and . Some of the terminology differs, mostly due to an effort to cast boosting terms into more standard statistical terminology (e.g. deviance). In addition, the gbm package implements boosting for models commonly used in statistics but not commonly associated with boosting. The Cox proportional hazard model, for example, is an incredibly useful model and the boosting framework applies quite readily with only slight modification [7]. Also some algorithms implemented in the gbm package differ from the standard implementation. The AdaBoost algorithm  has a particular loss function and a particular optimization algorithm associated with it. The gbm implementation of AdaBoost adopts AdaBoost’s exponential loss function (its bound on misclassification rate) but uses Friedman’s gradient descent algorithm rather than the original one proposed. So the main purposes of this document is to spell out in detail what the gbm package implements.
What is embodiment? A psychometric approach

What is it like to have a body? The present study takes a psychometric approach to this question. We collected structured introspective reports of the rubber hand illusion, to systematically investigate the structure of bodily self-consciousness. Participants observed a rubber hand that was stroked either synchronously or asynchronously with their own hand and then made proprioceptive judgments of the location of their own hand and used Likert scales to rate their agreement or disagreement with 27 statements relating to their subjective experience of the illusion. Principal components analysis of this data revealed four major components of the experience across conditions, which we interpret as: embodiment of rubber hand, loss of own hand, movement, and affect. In the asynchronous condition, an additional fifth component, deafference, was found. Secondary analysis of the embodiment of runner hand component revealed three subcomponents in both conditions: ownership, location, and agency. The ownership and location components were independent significant predictors of proprioceptive biases induced by the illusion. These results suggest that psychometric tools may provide a rich method for studying the structure of conscious experience, and point the way towards an empirically rigorous phenomenology.
Autonomous Vehicle Navigation and MappingSystem

— Autonomous vehicle navigation gains increasing importance in various growing application areas. In this paper we described a system it navigates the vehicle autonomously to its destination. This system provides a communication between vehicle and internet using GPRS modem. This system interfaced with OSRM open source map through internet. So we can decide the robot path from internet. In non-urban Domains such as deserts the problem of successful GPS-based navigation appears to be almost solved, navigation in urban domains particularly in the close vicinity of buildings is still a challenging problem. In such situations GPS accuracy significantly drops down due to unavailability of GPS signal. This project also improves the efficiency in navigation. This system not only relay on GPS. To improve the efficiency it uses location information from inertial sensors also. This system uses rotatable laser range finder for obstacle sensing. This is also designed in such a way that It can be monitored from anywhere through internet.  An autonomous vehicle, also known as a driverless vehicle, self-driving vehicle is an vehicle capable of fulfilling the human transportation capabilities of a traditional vehicle. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input. Autonomous vehicles sense their surroundings with such techniques as radar, lidar, GPS, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Some autonomous vehicles update their maps based on sensory input, allowing the vehicles to keep track of their position even when conditions change or when they enter uncharted environments. For any mobile robot, the ability to
A modified K-means clustering algorithm for use in isolated work recognition

Studies of isolated word recognition systems have shown that a set of carefully chosen templates can be used to bring the performance of speaker-independent systems up to that of systems trained to the individual speaker. The earliest work in this area used a sophisticated set of pattern recognition algorithms in a human-interactive mode to create the set of templates (multiple patterns) for each word in the vocabulary. Not only was this procedure time consuming but was impossible to reproduce exactly because it was highly dependent on decisions made by the experimenter. Subsequent work led to an automatic clustering procedure which, given only a set of clustering parameters , clustered patterns with the same performance as the previously developed supervised algorithms. The one drawback of the automatic procedure was that the specification of the input parameter set was found to be somewhat dependent on the vocabulary type and size of population to be clustered. Since a naive user of such a statistical clustering algorithm could not be expected, in general, to know how to choose the word clustering parameters, even this automatic clustering algorithm was not appropriate for a completely general word recognition system. It is the purpose of this paper to present a clustering algorithm based on a standard K-means approach which requires no user parameter specification. Experimental data show that this new algorithm performs as well or better than the previously used clustering techniques when tested as part of a speaker-independent isolated word recognition system. P I. INTRODUCTION ATTERN recognition techniques have been widely used in all aspects of speech recognition. However, the area which has depended most on pattern recognition techniques is that of pattern clustering to derive a set of speaker-independent templates for isolated word recognition. The problem here is straightforward. We are given a set of N word patterns, where each pattern is a single utterance of one particular word in the vocabulary, spoken (in general) by N different talkers, and our task is to cluster the N patterns into A4 clusters such that within each
Adaptive teams of autonomous aerial and ground robots for situational awareness

In this paper, we report on the integration challenges of the various component technologies developed towards the establishment of a framework for deploying an adaptive system of heterogeneous robots for urban surveillance. In our integrated experiment and demonstration, aerial robots generate maps that are used to design navigation controllers and plan missions for the team. A team of ground robots constructs a radio signal strength map that is used as an aid for planning missions. Multiple robots establish a mobile, ad-hoc communication network that is aware of the radio signal strength between nodes and can adapt to changing conditions to maintain connectivity. Finally, the team of aerial and ground robots is able to monitor a small village, and search for and localize human targets by the color of the uniform, while ensuring that the information from the team is available to a remotely located human operator. The key component technologies and contributions include (a) mission specification and planning software; (b) exploration and mapping of radio signal strengths in an urban environment; (c) programming abstractions and composition of controllers for multi-robot deployment; (d) cooperative control strategies for search, identification, and localization of targets; and (e) three-dimensional mapping in an urban setting.
Automatic Vehicle Parallel Parking Design Using Fifth Degree Polynomial Path Planning

Automatic vehicle parallel parking design and its related concerns about safety improvement remain some of the heated problems for automatic land vehicular control. This paper presents the calculation process of a parallel parking car's path planning and the algorithm development for its motion design based on a fifth-degree polynomial curve. In addition to the proposed algorithm for automatic vehicle parking, the minimum horizontal distance allowed for parking between a car and a parking spot is also investigated. The preliminary results show that the fifth degree polynomial path planning and the algorithm are well applied to the automatic parallel parking problem.
Development of a 60 GHz Substrate Integrated Waveguide planar diplexer

A 60 GHz frequency band planar diplexer based on Substrate Integrated Waveguide (SIW) technology is presented in this research. The 5th order millimeter wave SIW filter is investigated first, and then the 60 GHz SIW diplexer is designed and been simulated. SIW-microstrip transitions are also included in the final design. The relative bandwidths of up and down channels are 1.67% and 1.6% at 59.8 GHz and 62.2 GHz respectively. Simulation shows good channel isolation, small return losses and moderate insertion losses in pass bands. The diplexer can be easily integrated in millimeter wave integrated circuits.
Automatic recovery of the atmospheric light in hazy images

Most image dehazing algorithms require, for their operation, the atmospheric light vector, A, which describes the ambient light in the scene. Existing methods either rely on user input or follow error-prone assumptions such as the gray-world assumption. In this paper we present a new automatic method for recovering the atmospheric light vector in hazy scenes given a single input image. The method first recovers the vector's orientation, Â = A/∥A∥, by exploiting the abundance of small image patches in which the scene transmission and surface albedo are approximately constant. We derive a reduced formation model that describes the distribution of the pixels inside such patches as lines in RGB space and show how these lines are used for robustly extracting Â. We show that the magnitude of the atmospheric light vector,∥A∥, cannot be recovered using patches of constant transmission. We also show that errors in its estimation results in dehazed images that suffer from brightness biases that depend on the transmission level. This dependency implies that the biases are highly-correlated with the scene and are therefore hard to detect via local image analysis. We address this challenging problem by exploiting a global regularity which we observe in hazy images where the intensity level of the brightest pixels is approximately independent of their transmission value. To exploit this property we derive an analytic expression for the dependence that a wrong magnitude introduces and recover ∥A∥ by minimizing this particular type of dependence. We validate the assumptions of our method through a number of experiments as well as evaluate the expected accuracy at which our procedure estimates A as function of the transmission in the scene. Results show a more successful recovery of the atmospheric light vector compared to existing procedures.
What is resilience? A review and concept analysis

The complexities of defining what appears to be the relatively simple concept of resilience are widely recognized. This paper analyses the concept of resilience from a range of disciplinary perspectives and clarifies a definition in order to inform research, policy and practice. The work takes a life course approach to resilience, examining evidence derived from research across the lifespan. It incorporates the methods of systematic review, concept analysis and consultation through face-to-face meetings. The synthesis of methodological approaches enables a clear identification of the antecedents, defining attributes and consequences of resilience, validated with stakeholder partners. Through this process, resilience is defined as the process of effectively negotiating, adapting to, or managing significant sources of stress or trauma. Assets and resources within the individual, their life and environment facilitate this capacity for adaptation and ‘bouncing back’ in the face of adversity. Across the life course, the experience of resilience will vary. A large proportion of resilience research is routed within the discipline of developmental psychology, and has mainly been developed with children and adolescents. A major contribution to resilience research could be made through more multi-disciplinary studies that examine the dynamics of resilience across the lifespan, its role in healthy ageing and in managing loss, such as changes in cognitive functioning.
Automated processing of shoeprint images based on the Fourier transform for use in forensic science

The development of a system for automatically sorting a database of shoeprint images based on the outsole pattern in response to a reference shoeprint image is presented. The database images are sorted so that those from the same pattern group as the reference shoeprint are likely to be at the start of the list. A database of 476 complete shoeprint images belonging to 140 pattern groups was established with each group containing two or more examples. A panel of human observers performed the grouping of the images into pattern categories. Tests of the system using the database showed that the first-ranked database image belongs to the same pattern category as the reference image 65 percent of the time and that a correct match appears within the first 5 percent of the sorted images 87 percent of the time. The system has translational and rotational invariance so that the spatial positioning of the reference shoeprint images does not have to correspond with the spatial positioning of the shoeprint images of the database. The performance of the system for matching partial-prints was also determined.
Supervised Learning Based on Temporal Coding in Spiking Neural Networks

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input–output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.
The Influence of Avatars on Online Consumer Shopping Behavior

An impediment to Web-based retail sales is the impersonal nature of Web-based shopping. A solution to this problem is to use an avatar to deliver product information. An avatar is a graphic representation that can be animated by means of computer technology. Study 1 shows that using an avatar sales agent leads to more satisfaction with the retailer, a more positive attitude toward the product, and a greater purchase intention. Study 2 shows that an attractive avatar is a more effective sales agent at moderate levels of product involvement, but an expert avatar is a more effective sales agent at high levels of product involvement.
A miniature 2.1-GHz low loss microstrip filter with independent electric and magnetic coupling

A miniature planar two-pole microstrip filter with independent electric and magnetic coupling has been developed at 2.1 GHz. The independent coupling allows separate control of two transmission zeroes and result in a sharp filter skirt. The two-pole filter occupies an area of 6.6/spl times/4.6 mm/sup 2/ (30 mm/sup 2/) on an /spl epsi//sub r/=10.2 substrate, and shows a 5% bandwidth (100 MHz) and an insertion loss of 1.4 dB. The filter unloaded Q is 150 at 2.1 GHz which is much better than compatible filters done in LTCC technology.
The grand challenge of computer Go: Monte Carlo tree search and extensions

The ancient oriental game of Go has long been considered a grand challenge for artificial intelligence. For decades, computer Go has defied the classical methods in game tree search that worked so successfully for chess and checkers. However, recent play in computer Go has been transformed by a new paradigm for tree search based on Monte-Carlo methods. Programs based on Monte-Carlo tree search now play at human-master levels and are beginning to challenge top professional players. In this paper, we describe the leading algorithms for Monte-Carlo tree search and explain how they have advanced the state of the art in computer Go.
A Blockchain-Based Supply Chain Quality Management Framework

Recent quality scandals reveal the importance of quality management from a supply chain perspective. Although there has been many related studies focusing on supply chain quality management, the technologies used still have difficulties in resolving problems arising from the lack of trust in supply chains. The root reason lies in three challenges brought to the traditional centralized trust mechanism: self-interests of supply chain members, information asymmetry in production processes, costs and limitations of quality inspections. Blockchain is a promising technology to address these problems. In this paper, we discuss how to improve the supply chain quality management by adopting the blockchain technology, and propose a framework for blockchain-based supply chain quality management.
Cutting the electric bill for internet-scale systems

Energy expenses are becoming an increasingly important fraction of data center operating costs. At the same time, the energy expense per unit of computation can vary significantly between two different locations. In this paper, we characterize the variation due to fluctuating electricity prices and argue that existing distributed systems should be able to exploit this variation for significant economic gains. Electricity prices exhibit both temporal and geographic variation, due to regional demand differences, transmission inefficiencies, and generation diversity. Starting with historical electricity prices, for twenty nine locations in the US, and network traffic data collected on Akamai's CDN, we use simulation to quantify the possible economic gains for a realistic workload. Our results imply that existing systems may be able to save millions of dollars a year in electricity costs, by being cognizant of locational computation cost differences.
A 60 GHz Phase Shifter Integrated With LNA and PA in 65 nm CMOS for Phased Array Systems

This paper presents the design of a 60 GHz phase shifter integrated with a low-noise amplifier (LNA) and power amplifier (PA) in a 65 nm CMOS technology for phased array systems. The 4-bit digitally controlled RF phase shifter is based on programmable weighted combinations of I/Q paths using digitally controlled variable gain amplifiers (VGAs). With the combination of an LNA, a phase shifter and part of a combiner, each receiver path achieves 7.2 dB noise figure, a 360° phase shift range in steps of approximately 22.5°, an average insertion gain of 12 dB at 61 GHz, a 3 dB-bandwidth of 5.5 GHz and dissipates 78 mW. Consisting of a phase shifter and a PA, one transmitter path achieves a maximum output power of higher than +8.3 dBm, a 360° phase shift range in 22.5° steps, an average insertion gain of 7.7 dB at 62 GHz, a 3 dB-bandwidth of 6.5 GHz and dissipates 168 mW.
WSN- and IOT-Based Smart Homes and Their Extension to Smart Buildings

Our research approach is to design and develop reliable, efficient, flexible, economical, real-time and realistic wellness sensor networks for smart home systems. The heterogeneous sensor and actuator nodes based on wireless networking technologies are deployed into the home environment. These nodes generate real-time data related to the object usage and movement inside the home, to forecast the wellness of an individual. Here, wellness stands for how efficiently someone stays fit in the home environment and performs his or her daily routine in order to live a long and healthy life. We initiate the research with the development of the smart home approach and implement it in different home conditions (different houses) to monitor the activity of an inhabitant for wellness detection. Additionally, our research extends the smart home system to smart buildings and models the design issues related to the smart building environment; these design issues are linked with system performance and reliability. This research paper also discusses and illustrates the possible mitigation to handle the ISM band interference and attenuation losses without compromising optimum system performance.
A Metric Conceptual Space Algebra

The modeling of concepts from a cognitive perspective is important for designing spatial information systems that interoperate with human users. Concept representations that are built using geometric and topological conceptual space structures are well suited for semantic similarity and concept combination operations. In addition, concepts that are more closely grounded in the physical world, such as many spatial concepts, have a natural fit with the geometric structure of conceptual spaces. Despite these apparent advantages, conceptual spaces are underutilized because existing formalizations of conceptual space theory have focused on individual aspects of the theory rather than the creation of a comprehensive algebra. In this paper we present a metric conceptual space algebra that is designed to facilitate the creation of conceptual space knowledge bases and inferencing systems. Conceptual regions are represented as convex polytopes and context is built in as a fundamental element. We demonstrate the applicability of the algebra to spatial information systems with a proof-of-concept application.