nils-herrmann/clean_scirepeval huggingface dataset:
Smart Homes and Quality of Life for the Elderly: Perspective of Competing Models

The percentage of the elderly population has been on rise steadily over the past few years across the globe, which is a cause of serious concern among the research fraternity. A lot of research is going on that tries to harness the benefits of the various information and communication technologies to enable these elderly people to live independently and promote a sense of overall well-being. Although in the evolutionary phase, yet smart homes can help these elderly people in their daily life. However, for the success of such smart systems, the intention of the users towards using those systems must be understood. But, there is a serious lack of relevant exploratory research that tries to measure and explain the adoption of such smart homes by the elderly population from a multiple theory perspective: namely, the technology acceptance model, the theory of reasoned action and the theory of planned behavior. The main aim of this paper is to fill up this void of a lack of theoretical approach by testing the three models in the context of the adoption of smart homes by the elderly population. In order to do so, we conducted a survey with  $N = 239$  (after screening) and analyzed the results using the structural equation modeling and confirmatory factor analysis techniques. Results suggest that all the three models are valid although they do not take into account certain factors that are unique to this context. This paper paper provides the initial groundwork to explore the process of adopting smart home services by the elderly with potential future research areas.
Real Life Information Retrieval: A Study of User Queries on the Web

We analyzed transaction logs of a set of 51,473 queries posed by 18,113 users of Excite, a major Internet search service. We provide data on: (i) queries --- the number of search terms, and the use of logic and modifiers, (ii) sessions --- changes in queries during a session, number of pages viewed, and use of relevance feedback, and (iii) terms --- their rank/frequency distribution and the most highly used search terms. Common mistakes are also observed. Implications are discussed.
Stereo Processing by Semiglobal Matching and Mutual Information

This paper describes the semiglobal matching (SGM) stereo method. It uses a pixelwise, mutual information (Ml)-based matching cost for compensating radiometric differences of input images. Pixelwise matching is supported by a smoothness constraint that is usually expressed as a global cost function. SGM performs a fast approximation by pathwise optimizations from all directions. The discussion also addresses occlusion detection, subpixel refinement, and multibaseline matching. Additionally, postprocessing steps for removing outliers, recovering from specific problems of structured environments, and the interpolation of gaps are presented. Finally, strategies for processing almost arbitrarily large images and fusion of disparity images using orthographic projection are proposed. A comparison on standard stereo images shows that SGM is among the currently top-ranked algorithms and is best, if subpixel accuracy is considered. The complexity is linear to the number of pixels and disparity range, which results in a runtime of just 1-2 seconds on typical test images. An in depth evaluation of the Ml-based matching cost demonstrates a tolerance against a wide range of radiometric transformations. Finally, examples of reconstructions from huge aerial frame and pushbroom images demonstrate that the presented ideas are working well on practical problems.
Force Analysis of Connected Differential Mechanisms: Application to Grasping

In this paper, a methodology is proposed for the analysis of the force capabilities of connected differential mechanisms. These systems are the key elements used to extend the principle of underactuation in grasping from the fingers to the hand itself. The concept of underactuation in robotic grasping—with fewer actuators than degrees of freedom (DOF)—allows the hand to adjust itself to an irregularly shaped object without complex control strategies and sensors. Several technological solutions have been proposed in the past but no theoretical background has been provided to analyze their characteristics, especially with respect to the forces generated. The purpose of this paper is to provide such a theoretical foundation and to illustrate its usefulness with examples applied to grasping. First, several differential elements are presented and studied. Second, a mathematical method to obtain the output force capabilities of connected differential mechanisms is presented. Finally, the technique presented is applied to two types of underactuated robotic hands. robotic hand, grasping, underactuation, underactuated finger, differential mechanisms
Validation, verification, and testing techniques throughout the life cycle of a simulation study

Life cycle validation, verification, and testing (VV&T) is extremely important for the success of a simulation study. This paper surveys current software VV&T techniques and current simulation model VV&T techniques and describes how they can all be applied throughout the life cycle of a simulation study. The processes and credibility assessment stages of the life cycle are described and the applicability of the VV&T techniques for each stage is stated.
Impairment of voice and face recognition in patients with hemispheric damage

Voice and face recognition were tested in 21 left- and 9 right-hemisphere-damaged patients. Test materials were photographs and recordings of famous political and entertainment personalities. Pathological face recognition (prosopagnosia) and voice recognition (phonagnosia) were both significantly more prevalent in the right-hemisphere group. Only one instance of prosopagnosia and one of phonagnosia were observed in the left-hemisphere group, all of whom were aphasic. Of the right-hemisphere cases, there were four instances of each agnosia, with three patients showing a dual impairment. These findings are discussed in relation to differential modes of processing by the two cerebral hemispheres.
A shared " passengers & goods " city logistics system

Many strategic planning models have been developed to help decision making in city logistics. Such models do not take into account, or very few, the flow of passengers because the considered unit does not have the same nature (a person is active and a good is passive). However, it seems fundamental to gather the goods and the passengers in one model when their respective transports interact with each other. In this context, we suggest assessing a shared passengers & goods city logistics system where the spare capacity of public transport is used to distribute goods toward the city core. We model the problem as a vehicle routing problem with transfers and give a mathematical formulation. Then we propose an Adaptive Large Neighborhood Search (ALNS) to solve it. This approach is evaluated on data sets generated following a field study in the city of La Rochelle in France.
PREDICTING BREAST CANCER SURVIVABILITY USING DATA MINING TECHNIQUES

In this paper we present an analysis of the prediction of survivability rate of breast cancer patients using data mining techniques. The data used is the SEER Public-Use Data. The preprocessed data set consists of 151,886 records, which have all the available 16 fields from the SEER database. We have investigated three data mining techniques: the Naïve Bayes, the back-propagated neural network, and the C4.5 decision tree algorithms. Several experiments were conducted using these algorithms. The achieved prediction performances are comparable to existing techniques. However, we found out that C4.5 algorithm has a much better performance than the other two techniques.
A Weighted Frequent Itemset Mining Algorithm for Intelligent Decision in Smart Systems

Intelligent decision is the key technology of smart systems. Data mining technology has been playing an increasingly important role in decision-making activities. Frequent itemset mining (FIM), as an important step of association rule analysis, is becoming one of the most important research fields in data mining. Weighted FIM in uncertain databases should take both existential probability and importance of items into account in order to find frequent itemsets of great importance to users. However, the introduction of weight makes the weighted frequent itemsets not satisfy the downward closure property any longer. As a result, the search space of frequent itemsets cannot be narrowed according to downward closure property which leads to a poor time efficiency. In this paper, the weight judgment downward closure property for the weighted frequent itemsets and the existence property of weighted frequent subsets are introduced and proved first. Based on these two properties, the Weight judgment downward closure property-based FIM (WD-FIM) algorithm is proposed to narrow the searching space of the weighted frequent itemsets and improve the time efficiency. Moreover, the completeness and time efficiency of WD-FIM algorithm are analyzed theoretically. Finally, the performance of the proposed WD-FIM algorithm is verified on both synthetic and real-life data sets.
Gaussian Process Regression Networks

We introduce a new regression framework, Gaussian process regression networks (GPRN), which combines the structural properties of Bayesian neural networks with the nonparametric flexibility of Gaussian processes. GPRN accommodates input (predictor) dependent signal and noise correlations between multiple output (response) variables, input dependent length-scales and amplitudes, and heavy-tailed predictive distributions. We derive both elliptical slice sampling and variational Bayes inference procedures for GPRN. We apply GPRN as a multiple output regression and multivariate volatility model, demonstrating substantially improved performance over eight popular multiple output (multi-task) Gaussian process models and three multivariate volatility models on real datasets, including a 1000 dimensional gene expression dataset.
A statistical approach for real time robust background subtraction

This paper presents a novel algorithm for detecting moving objects from a static background scene that contains shading and shadows using color images. We develop a robust and e ciently computed background subtraction algorithm that is able to cope with local illumination changes, such as shadows and highlights, as well as global illumination changes. The algorithm is based on a proposed computational color model which separates the brightness from the chromaticity component. We have applied this method to real image sequences of both indoor and outdoor scenes. The results, which demonstrate the system's performance, and some speed up techniques we employed in our implementation are also shown.
Signal and Power Integrity Analysis on Integrated Fan-Out PoP (InFO_PoP) Technology for Next Generation Mobile Applications

A novel integrated fan-out package on package (InFO_PoP) technology for application processor (AP), memory, and PMIC system is developed for next generation high performance mobile applications. For AP and memory system, the InFO_PoP technology can provide better system performance and lower package profile, compared to current flip-chip package on package (FC_PoP) technology. For signal integrity, the eye height of eye diagram for the InFO_PoP is 24% larger than that for the FC_PoP at LPDDR4. For power integrity, the PDN impedance for the InFO_PoP is 84% lower than that for the FC_PoP at high frequency because of thinner dielectric layer between power/ground planes and shorter path from AP pad to PCB. For AP and PMIC system, an advanced power delivery network (PDN) is proposed to minimize the supply voltage variation and transient time using face-to-face interconnection between AP package and partitioned voltage regulators (PVRs) chip from PMIC package. The voltage variation of the InFO_PoP with PVRs system is 43% lower than that of the FC_PoP with PVRs system. Meanwhile, the InFO_PoP with PVRs system exhibits immediate transient response. The transient time of InFO_PoP with PVRs system is 54% less than that of the FC_PoP with PVRs system.
Control of VSC connected to the grid through LCL-filter to achieve balanced currents

Grid-connected voltage source converters (VSCs) are the heart of many applications with power quality concerns due to their reactive power controllability. However, the major drawback is their sensitivity to grid disturbances. Moreover, when VSCs are used in DG applications, voltage unbalance may be intolerant. The current protection may trip due to current unbalance or due to overcurrent. In this paper, a vector current controller for VSC connected to the grid through LCL-filter is developed with the main focus on producing symmetrical and balanced currents in case of unbalanced voltage dips. Implementing this controller helps the VSC system not to trip during voltage dips.
Analysis, design, and performance evaluation of asymmetrical half-bridge flyback converter for universal-line-voltage-range applications

The asymmetrical half-bridge (AHB) flyback converter is an attractive topology for operation at higher switching frequencies because it can operate with zero-voltage switching of the primary-side switches and zero-current switching of the secondary-side rectifier. In this paper, a detailed analysis and design procedure of the AHB flyback converter for the universal-line-voltage-range applications is presented. The performance of the AHB flyback converter is evaluated by loss analysis based on the simulation waveforms obtained in Simplis and experimentally verified on a laboratory prototype of a 65-W (19.5-V, 3.33-A) universal-line-voltage-range adapter.
Synthetic Social Media Data Generation

This paper presents a novel system, synthetic high-fidelity social media data generator (SHIELD), for generating the synthetic social media data. SHIELD jointly generates time-varying, directed and weighted interaction graph structures and topic-driven text features similar to the input social media data. A synthetic interaction graph is generated by a social network model to minimize the distance to real graph and is enhanced by adding various patterns, such as anomalies and information cascades, interaction types, and temporal dynamics. A synthetic text generator based on the  $n$ -gram Markov model is trained under each topic identified by topic modeling. Synthetic text and graph structures are combined through the assignment of synthetic social media entities. Extensive performance evaluation via a graph and text analysis is provided to demonstrate the statistical fidelity of large-scale synthetic data generated by SHIELD. A data evaluation exercise with human participants is executed to identify how difficult it is for a human to distinguish between tweets that were generated by SHIELD and tweets that were posted by real users. Experimental results followed by a statistical significance analysis showed that human participants cannot reliably distinguish between real and synthetic tweets.
Dynamic Programming for Detecting, Tracking, and Matching Deformable Contours

Abstruct-The problem of segmenting an image into separate regions and tracking them over time is one of the most significant problems in vision. Tenopoulos et al have proposed an approach to detect the contour regions of complex shapes, assuming a user selected initial contour not very far from the desired solution. We propose to further explore the information provided by the user’s selected points and applyan optimal method to detect contours which allows a segmentation of the image. The method is based on dynamic programming @P), and applies to a wide variety of shapes. It is exact and not iterative. We also consider a multiscale approach capable of speeding up the algorithm by a factor of 20, although at the expense of losing the guaranteed optimality characteristic. The problem of tracking and matching these contours is addressed. For tracking, the final contour obtained at one frame is sampled and used as initial points for the next frame. Then, the same DP process is applied. For matching, a novel strategy is proposed where the solution is a smooth displacement field in which unmatched regions are allowed while cross vectors are not. The algorithm is again based on DP and the optimal solution is guaranteed. We have demonstrated the algorithms on natural objects in a large spectrum of applications, including interactive segmentation and automatic tracking of the regions of interest in medical images.
Contextmapping : experiences from practice

In recent years, various methods and techniques have emerged for mapping the contexts of people's interaction with products. Designers and researchers use these techniques to gain deeper insight into the needs and dreams of prospective users of new products. As most of these techniques are still under development, there is a lack of practical knowledge about how such studies can be conducted. In this paper we share our insights, based on several projects from research and many years of industrial practice, of conducting user studies with generative techniques. The appendix contains a single case illustrating the application of these techniques in detail.
Explaining the Gibbs Sampler

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use.
Fine-grained change detection in structured text documents

Detecting and understanding changes between document revisions is an important task. The acquired knowledge can be used to classify the nature of a new document revision or to support a human editor in the review process. While purely textual change detection algorithms offer fine-grained results, they do not understand the syntactic meaning of a change. By representing structured text documents as XML documents we can apply tree-to-tree correction algorithms to identify the syntactic nature of a change.
 Many algorithms for change detection in XML documents have been propsed but most of them focus on the intricacies of generic XML data and emphasize speed over the quality of the result. Structured text requires a change detection algorithm to pay close attention to the content in text nodes, however, recent algorithms treat text nodes as black boxes.
 We present an algorithm that combines the advantages of the purely textual approach with the advantages of tree-to-tree change detection by redistributing text from non-overlapping common substrings to the nodes of the trees. This allows us to not only spot changes in the structure but also in the text itself, thus achieving higher quality and a fine-grained result in linear time on average. The algorithm is evaluated by applying it to the corpus of structured text documents that can be found in the English Wikipedia.
Grounding English Commands to Reward Functions

As intelligent robots become more prevalent, methods to make interaction with the robots more accessible are increasingly important. Communicating the tasks that a person wants the robot to carry out via natural language, and training the robot to ground the natural language through demonstration, are especially appealing approaches for interaction, since they do not require a technical background. However, existing approaches map natural language commands to robot command languages that directly express the sequence of actions the robot should execute. This sequence is often specific to a particular situation and does not generalize to new situations. To address this problem, we present a system that grounds natural language commands into reward functions using demonstrations of different natural language commands being carried out in the environment. Because language is grounded to reward functions, rather than explicit actions that the robot can perform, commands can be high-level, carried out in novel environments autonomously, and even transferred to other robots with different action spaces. We demonstrate that our learned model can be both generalized to novel environments and transferred to a robot with a different action space than the action space used during training.
Test Case Selection and Prioritization Using Multiple Criteria

Regression testing activities such as test case selection and test case prioritization are ordinarily based on the criteria which focused around code coverage, code modifications and test execution costs. The approach mainly based on the multiple criteria of code coverage which performs efficient selection of test case. The method mainly aims to maximize the coverage size by executing the test cases effectively. The selected test cases are then prioritized based on the priority which depends on the code coverage to achieve the desired results. Test case selection, Test case prioritization, Cod coverage, Jaccard distance, Greedy algorithm.
How users' Internet experience affects the adoption of mobile payment: a mediation model

Mobile payment becomes a convenient way to complete transactions due to the increasing popularity of mobile devices and the maturity of related technologies. Users’ experience of using computers and the Internet in financial activities largely affects their intention to use mobile payment. Combining the Technology Acceptance Model and Innovation Diffusion Theory, we examined the mediating effect of five factors, that is, perceived usefulness, perceived ease of use, compatibility, risk, and privacy concern, in the relationship between Internet experience and the adoption of mobile payment. Data from 922 mobile users supported the partial mediating effects of the five factors. ARTICLE HISTORY Received 6 March 2016 Revised 24 December 2016  February 2017
The Abandoned Side of the Internet: Hijacking Internet Resources When Domain Names Expire

The vulnerability of the Internet has been demonstrated by prominent IP prefix hijacking events. Major outages such as the China Telecom incident in 2010 stimulate speculations about malicious intentions behind such anomalies. Surprisingly, almost all discussions in the current literature assume that hijacking incidents are enabled by the lack of security mechanisms in the inter-domain routing protocol BGP. In this paper, we discuss an attacker model that accounts for the hijacking of network ownership information stored in Regional Internet Registry (RIR) databases. We show that such threats emerge from abandoned Internet resources (e.g., IP address blocks, AS numbers). When DNS names expire, attackers gain the opportunity to take resource ownership by re-registering domain names that are referenced by corresponding RIR database objects. We argue that this kind of attack is more attractive than conventional hijacking, since the attacker can act in full anonymity on behalf of a victim. Despite corresponding incidents have been observed in the past, current detection techniques are not qualified to deal with these attacks. We show that they are feasible with very little effort, and analyze the risk potential of abandoned Internet resources for the European service region: our findings reveal that currently 73 /24 IP prefixes and 7 ASes are vulnerable to be attacked. We discuss countermeasures and outline research directions towards preventive solutions.