nils-herrmann/clean_scirepeval huggingface dataset:
Modal Analysis of Dielectric-Filled Rectangular Waveguide With Transverse Slots

The dispersion relations and modes for a dielectric-filled rectangular waveguide with transverse slots are investigated. The differences between the air-filled and the dielectric-filled rectangular waveguides with transverse slots are analyzed. The dielectric-filled rectangular waveguide with transverse slots supports a leaky waveguide mode, a surface-wave mode and a proper waveguide mode. The complex propagation wavenumber is calculated by enforcing an aperture magnetic field integral equation using either a space-domain approach or a spectral-domain approach. The physical significance of the solutions is explained. The theoretical results agree very well with the results from HFSS simulation.
An integrated service-device-technology roadmap for smart city development

Article history: Received 13 March 2012 Received in revised form 28 September 2012 Accepted 29 September 2012 Available online 13 November 2012 Firms and other organizations use Technology Roadmapping (TRM) extensively as a framework for supporting research and development of future technologies and products that could sustain a competitive advantage.While the importance of technology strategy has receivedmore attention in recent years, few research studies have examined how roadmapping processes are used to explore the potential convergence of products and services that may be developed in the future. The aim of this paper is to introduce an integrated roadmapping process for services, devices and technologies capable of implementing a smart city development R&D project in Korea. The paper applies a QFD (Quality Function Deployment) method to establish interconnections between services and devices, and between devices and technologies. The method is illustrated by a detailed case study, which shows how different types of roadmap can be coordinated with each other to produce a clear representation of the technological changes and uncertainties associated with the strategic planning of complex innovations.
EveTAR: A New Test Collection for Event Detection in Arabic Tweets

Research on event detection in Twitter is often obstructed by the lack of publicly-available evaluation mechanisms such as test collections; this problem is more severe when considering the scarcity of them in languages other than English. In this paper, we present EveTAR, the first publicly-available test collection for event detection in Arabic tweets. The collection includes a crawl of 590M Arabic tweets posted in a month period and covers 66 significant events (in 8 different categories) for which more than 134k relevance judgments were gathered using crowdsourcing with high average inter-annotator agreement (Kappa value of 0.6). We demonstrate the usability of the collection by evaluating 3 state-of-the-art event detection algorithms. The collection is also designed to support other retrieval tasks, as we show in our experiments with ad-hoc search systems.
IoT based monitoring and control system for home automation

The project proposes an efficient implementation for IoT (Internet of Things) used for monitoring and controlling the home appliances via World Wide Web. Home automation system uses the portable devices as a user interface. They can communicate with home automation network through an Internet gateway, by means of low power communication protocols like Zigbee, Wi-Fi etc. This project aims at controlling home appliances via Smartphone using Wi-Fi as communication protocol and raspberry pi as server system. The user here will move directly with the system through a web-based interface over the web, whereas home appliances like lights, fan and door lock are remotely controlled through easy website. An extra feature that enhances the facet of protection from fireplace accidents is its capability of sleuthing the smoke in order that within the event of any fireplace, associates an alerting message and an image is sent to Smartphone. The server will be interfaced with relay hardware circuits that control the appliances running at home. The communication with server allows the user to select the appropriate device. The communication with server permits the user to pick out the acceptable device. The server communicates with the corresponding relays. If the web affiliation is down or the server isn't up, the embedded system board still will manage and operate the appliances domestically. By this we provide a climbable and price effective Home Automation system.
Research on customer segmentation model by clustering

In the paper, we use credit card consumption data as our model-building samples and present a modeling framework for building segment-level predictive models that utilize pattern-based clustering approach and signature discovery techniques. We devise monetary matrix and fluctuate-rate matrix to study various modes. Through clustering on both matrixes, we uncover different customer characteristics. Utilizing these characteristics, we can build two-dimension Consumption-Based customer segmentation model.
BOP: Benchmark for 6D Object Pose Estimation

We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. The benchmark comprises of: i) eight datasets in a unified format that cover different practical scenarios, including two new datasets focusing on varying lighting conditions, ii) an evaluation methodology with a pose-error function that deals with pose ambiguities, iii) a comprehensive evaluation of 15 diverse recent methods that captures the status quo of the field, and iv) an online evaluation system that is open for continuous submission of new results. The evaluation shows that methods based on point-pair features currently perform best, outperforming template matching methods, learning-based methods and methods based on 3D local features. The project website is available at bop.felk.cvut.cz.
Understanding customer knowledge sharing in web-based discussion boards: An exploratory study

The proliferation and advance of web-based technologies create expanded opportunities for retailers to gain a better understanding of their customers. However, the success of these web-based discussion boards depends solely on whether customers are willing to share their knowledge and experience with other customers in these discussion boards. Thus, this study aims at identifying the factors that drive knowledge sharing among customers in web-based discussion boards.  An exploratory study with 104 respondents was conducted to identify and categorize the key factors of customer knowledge sharing in web-based discussion boards.  The results indicate that the enjoyment of helping others is the most frequently cited reason for customer knowledge sharing in web-based discussion boards. On the other hand, the lack of knowledge self-efficacy is the mostly cited reason explaining why customers do not want to share knowledge with others.  The exploratory analysis suggests that the underlying reasons that motivate and inhibit customers to share are very different. There is a need to integrate multiple theoretical perspectives from across the social and technical domains if this phenomenon is to be better understood.  Building upon the findings of this study, some generic guidelines for retailers and web designers for promoting customer sharing in web-based discussion boards are outlined.  This research is one of the first studies to use the socio-technical perspective to investigate customer knowledge sharing phenomena in web-based discussion boards.
Automated Alarm System for Diaper Wet Using GSM

Wearing a wet diaper for prolonged periods, cause diaper rash. This paper presents an automated alarm system for Diaper wet. The design system using an advanced RF transceiver and GSM system to sound an alarm on the detection of moisture in the diaper to alert the intended person to change the diaper. A wet diaper detector comprises an elongated pair of spaced fine conductors which form the wet sensor. The sensor is positioned between the layers of a diaper in a region subject to wetness. The detector and RF transmitter are adapted to be easily coupled to the protruding end of the elongated sensor. When the diaper is wet the resistance between the spaced conductors falls below a pre-established value. Consequently, the detector and RF transmitter sends a signal to the RF receiver and the GSM to produce the require alarm. When the diaper is changed, the detector unit is decoupled from the pressing studs for reuse and the conductor is discarded along with the soiled diaper. Our experimental tests show that the designed system perfectly produces the intended alarm and can be adjusted for different level of wet if needed.
The Product Market and the Market for “ Ideas ” : Commercialization Strategies for Technology Entrepreneurs

This paper presents a synthetic framework identifying the central drivers of start-up commercialization strategy and the implications of these drivers for industrial dynamics. We link strategy to the commercialization environment – the microeconomic and strategic conditions facing a firm that is translating an " idea " into a value proposition for customers. The framework addresses why technology entrepreneurs in some environments undermine established firms, while others cooperate with incumbents and reinforce existing market power. Our analysis suggests that competitive interaction between start-up innovators and established firms depends on the presence or absence of a " market for ideas. " By focusing on the operating requirements, efficiency, and institutions associated with markets for ideas, this framework holds several implications for the management of high-technology entrepreneurial firms. (Stern). We would like to thank the firms who participate in the MIT Commercialization Strategies survey for their time and effort. The past two decades have witnessed a dramatic increase in investment in technology entrepreneurship – the founding of small, start-up firms developing inventions and technology with significant potential commercial application. Because of their youth and small size, start-up innovators usually have little experience in the markets for which their innovations are most appropriate, and they have at most two or three technologies at the stage of potential market introduction. For these firms, a key management challenge is how to translate promising
A 1-kW Contactless Energy Transfer System Based on a Rotary Transformer for Sealing Rollers

This paper introduces an innovative contactless energy transfer system for power supplying rotatable parts of automatic machineries as a robust alternative to sliding contacts. The design procedure of the key system devices, such as the dc/ac converter and the rotary transformer with its windings, is discussed. Different configurations in terms of switching network, number of turns, wire, and compensation are discussed with respect to their impact on the system efficiency and power factor. A thermal model to account for the core temperature is also introduced. Two setups, operating at 50 kHz and able to transfer up to 1.3 kW in a contactless fashion, are realized and tested to supply sealing roller resistors of automatic machineries. The system prototypes are then experimentally tested to validate the analytical models and the finite element simulations of the entire wireless power transfer link. Trade-offs emerge from the setups, in particular concerning efficiency, power factor, and electro-magnetic compatibility. As a consequence, we discuss the choice of the optimal configuration depending on the final application.
Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands

Recently Dutch government, as well as many other governments around the world, has digitized a major portion of its public services. With this development electronic services finally arrive at the transaction level. The risks of electronic services on the transactional level are more profound than at the informational level. The public needs to trust the integrity and ‘information management capacities’ of the government or other involved organizations, as well as trust the infrastructure and those managing the infrastructure. In this process, the individual citizen will have to decide to adopt the new electronic government services by weighing its benefits and risks. In this paper, we present a study which aims to identify the role of risk perception and trust in the intention to adopt government e-services. In January 2003, a sample of 238 persons completed a questionnaire. The questionnaire tapped people’s intention to adopt e-government electronic services. Based on previous research and theories on technology acceptance, the questionnaire measured perceived usefulness of e-services, risk perception, worry, perceived behavioural control, subjective norm, trust and experience with e-services. Structural equation modelling was used to further analyze the data (Amos) and to design a theoretical model predicting the individual’s intention to adopt e-services. This analysis showed that the perceived usefulness of electronic services in general is the main determinant of the intention to use e-government services. Risk perception, personal experience, perceived behavioural control and subjective norm were found to significantly predict the perceived usefulness of electronic services in general, while trust in e-government was the main determinant of the perceived usefulness of e-government services.  E-mail addresses: Margot.Kuttschreuter@utwente.nl (M. Kuttschreuter), J.M.Gutteling@utwente.nl (J.M. Gutteling). M. Horst et al. / Computers in Human Behavior 23 (2007) 1838–1852 1839
Simultaneous Perception and Path Generation Using Fully Convolutional Neural Networks

In this work, a novel learning-based approach has been developed to generate driving paths by integrating LIDAR point clouds, GPS-IMU information, and Google driving directions. The system is based on a fully convolutional neural network that jointly learns to carry out perception and path generation from real-world driving sequences and that is trained using automatically generated training examples. Several combinations of input data were tested in order to assess the performance gain provided by specific information modalities. The fully convolutional neural network trained using all the available sensors together with driving directions achieved the best MaxF score of 88.13% when considering a region of interest of 60×60 meters. By considering a smaller region of interest, the agreement between predicted paths and ground-truth increased to 92.60%. The positive results obtained in this work indicate that the proposed system may help fill the gap between low-level scene parsing and behavior-reflex approaches by generating outputs that are close to vehicle control and at the same time human-interpretable.
Connected component labeling on a 2D grid using CUDA

Connected component labeling is an important but computationally expensive operation required in many fields of research. The goal in the present work is to label connected components on a 2D binary map. Two different iterative algorithms for doing this task are presented. The first algorithm (Row–Col Unify) is based upon the directional propagation labeling, whereas the second algorithm uses the Label Equivalence technique. The Row–Col Unify algorithm uses a local array of references and the reduction technique intrinsically. The usage of shared memory extensively makes the code efficient. The Label Equivalence algorithm is an extended version of the one presented by Hawick et al. (2010) . At the end the comparison depending on the performances of both of the algorithms is presented.
Spectral and Energy-Efficient Wireless Powered IoT Networks: NOMA or TDMA?

Wireless powered communication networks (WPCNs), where multiple energy-limited devices first harvest energy in the downlink and then transmit information in the uplink, have been envisioned as a promising solution for the future Internet-of-Things (IoT). Meanwhile, nonorthogonal multiple access (NOMA) has been proposed to improve the system spectral efficiency (SE) of the fifth-generation (5G) networks by allowing concurrent transmissions of multiple users in the same spectrum. As such, NOMA has been recently considered for the uplink of WPCNs based IoT networks with a massive number of devices. However, simultaneous transmissions in NOMA may also incur more transmit energy consumption as well as circuit energy consumption in practice which is critical for energy constrained IoT devices. As a result, compared to orthogonal multiple access schemes such as time-division multiple access (TDMA), whether the SE can be improved and/or the total energy consumption can be reduced with NOMA in such a scenario still remains unknown. To answer this question, we first derive the optimal time allocations for maximizing the SE of a TDMA-based WPCN (T-WPCN) and a NOMA-based WPCN (N-WPCN), respectively. Subsequently, we analyze the total energy consumption as well as the maximum SE achieved by these two networks. Surprisingly, it is found that N-WPCN not only consumes more energy, but also is less spectral efficient than T-WPCN. Simulation results verify our theoretical findings and unveil the fundamental performance bottleneck, i.e., “worst user bottleneck problem”, in multiuser NOMA systems.
Insights from Machine-Learned Diet Success Prediction

To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider "quantified self" movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000 long-term active MyFitnessPal users to study the characteristics of a (un-)successful diet. Concretely, we train a machine learning model to predict repeatedly being over or under self-set daily calories goals and then look at which features contribute to the model's prediction. Our findings include both expected results, such as the token "mcdonalds" or the category "dessert" being indicative for being over the calories goal, but also less obvious ones such as the difference between pork and poultry concerning dieting success, or the use of the "quick added calories" functionality being indicative of over-shooting calorie-wise. This study also hints at the feasibility of using such data for more in-depth data mining, e.g., looking at the interaction between consumed foods such as mixing protein- and carbohydrate-rich foods. To the best of our knowledge, this is the first systematic study of public food diaries.
A Low Complexity SCMA Decoder Based on List Sphere Decoding

Non-orthogonal multiple access is one of the key techniques developed for the future 5G communication systems among which, the recent proposed sparse code multiple access (SCMA) has attracted a lots of researchers' interests. By exploring the shaping gain of the multi-dimensional complex codewords, SCMA is shown to have a better performance compared with some other non-orthogonal schemes such as low density signature (LDS). However, although the sparsity of the codewords makes the near optimal message passing algorithm (MPA) possible, the decoding complexity is still very high. In this paper, we propose a low complexity decoding algorithm based on list sphere decoding. Complexity analysis and simulation results show that the proposed algorithm can reduce the computational complexity substantially while achieve the near maximum likelihood (ML) performance.
Primate anterior cingulate cortex: Where motor control, drive and cognition interface

Controversy surrounds the function of the anterior cingulate cortex. Recent discussions about its role in behavioural control have centred on three main issues: its involvement in motor control, its proposed role in cognition and its relationship with the arousal/drive state of the organism. I argue that the overlap of these three domains is key to distinguishing the anterior cingulate cortex from other frontal regions, placing it in a unique position to translate intentions to actions.
Information security management objectives and practices: a parsimonious framework

As part of their continuing efforts to establish effective information security management (ISM) practices, information security researchers and practitioners have proposed and developed many different information security standards and guidelines. Building on these previous efforts, the purpose of this study is to put forth a framework for ISM.  This framework is derived from the development of an a priori set of objectives and practices as suggested by literature, standards, and reports found in academia and practice; the refinement of these objectives and practices based on survey data obtained from 354 certified information security professionals; and the examination of interrelationships between the objectives and practices.  The empirical analysis suggests: four factors (information integrity, confidentiality, accountability, and availability) serve as critical information security objectives; most of the security areas and items covered under ISO 17799 are valid with one new area – “external” or “inter-organizational information security”; and for moderately information-sensitive organizations, “confidentiality” has the highest correlation with ISM practices; for highly information-sensitive organizations, “confidentiality”, “accountability”, and “integrity” are the major ISM objectives. The most important contributor to information security objectives is “access control”.  This study contributes to the domain of information security research by developing a parsimonious set of security objectives and practices grounded in the findings of previous works in academia and practical literature.  These findings provide insights for business managers and information security professionals attempting to implement ISM programs within their respective organizational settings.  This paper fulfills a need in the information security community for a parsimonious set of objectives and practices based on the many guidelines and standards available in both academia and practice.
An experimental high performance radar system for highly automated driving

The performance of automotive radar systems is expected to significantly increase in the near future. With enhanced resolution capabilities more accurate and denser point clouds of traffic participants and roadside infrastructure can be acquired and so the amount of gathered information is growing drastically. One main driver for this development is the global trend towards self-driving cars, which all rely on precise and fine-grained sensor information. New radar signal processing concepts have to be developed in order to provide this additional information. This paper presents a prototype high resolution radar sensor which helps to facilitate algorithm development and verification. The system is operational under real-time conditions and achieves excellent performance in terms of range, velocity and angular resolution. Complex traffic scenarios can be acquired out of a moving test vehicle, which is very close to the target application. First measurement runs on public roads are extremely promising and show an outstanding single-snapshot performance. Complex objects can be precisely located and recognized by their contour shape. In order to increase the possible recording time, the raw data rate is reduced by several orders of magnitude in real-time by means of constant false alarm rate (CFAR) processing. The number of target cells can still exceed more than 10 000 points in a single measurement cycle for typical road scenarios.