nils-herrmann/clean_scirepeval huggingface dataset:
An Accurate, Low-Voltage, CMOS Switching Power Supply With Adaptive On-Time Pulse-Frequency Modulation (PFM) Control

Integrated switching power supplies with multimode control are gaining popularity in state-of-the-art portable applications like cellular phones, personal digital assistants (PDAs), etc., because of their ability to adapt to various loading conditions and therefore achieve high efficiency over a wide load-current range, which is critical for extended battery life. Constant-frequency, pulsewidth modulated (PWM) switching converters, for instance, have poor light-load efficiencies because of higher switching losses while pulse-frequency modulation (PFM) control in discontinuous-conduction mode (DCM) is more efficient at light loads because the switching frequency and associated switching losses are scaled down with load current. This paper presents the design and integrated circuit prototype results of an 83% power efficient 0.5-V 50-mA CMOS PFM buck (step-down) dc-dc converter with a novel adaptive on-time scheme that generates a 27-mV output ripple voltage from a 1.4- to 4.2-V input supply (battery-compatible range). The output ripple voltage variation and steady-state accuracy of the proposed supply was 5 mV (22-27 mV) and 0.6% whereas its constant on-time counterpart was 45 mV (10-55 mV) and 3.6%, respectively. The proposed control scheme provides an accurate power supply while achieving 2%-10% higher power efficiency than conventional fixed on-time schemes with little circuit complexity added, which is critical during light-loading conditions, where quiescent current plays a pivotal role in determining efficiency and battery-life performance
Critical Success Factors of Total Quality Management and their impact on Performance of Iranian Automotive Industry

This paper shows a model to conduct an empirical study in Iranian automotive industry in order to improve their performance. There are many factors which are effective factors in improving performance of Iranian automobile industry namely, leadership, customer focus, training, supplier quality management, product design, process management, and team work. The quality improvement plays a fundamental role in determining the performance in Iranian manufacturing industries. In this research, a model has been developed that includes Quality culture, Critical success factors of Total Quality Management and quality improvement to study their influence on the performance of Iranian automotive industry. It is hoped that this paper can provide an academic source for both academicians and managers due to investigate the relationship between Quality culture, critical success factors of Total Quality Management, Quality improvement, and Performance in a systematic manner to increase successful rate of Total Quality Management implementation.
Ultra-Wideband Phase Shifters

A method with clear guidelines is presented to design compact planar phase shifters with ultra-wideband (UWB) characteristics. The proposed method exploits broadside coupling between top and bottom elliptical microstrip patches via an elliptical slot located in the mid layer, which forms the ground plane. A theoretical model is used to analyze performance of the proposed devices. The model shows that it is possible to design high-performance UWB phase shifters for the 25deg-48deg range using the proposed structure. The method is used to design 30deg and 45deg phase shifters that have compact size, i.e., 2.5 cm times 2 cm. The simulated and measured results show that the designed phase shifters achieve better than plusmn3deg differential phase stability, less than 1-dB insertion loss, and better than 10-dB return loss across the UWB, i.e., 3.1-10.6 GHz.
Stretchable liquid tactile sensor for robot-joints

In this paper, we propose a stretchable tactile sensor composed of a pair of silicone rubber channels filled with electro conductive liquid. When a force was applied to this channel, its length and cross-sectional area deforms. By measuring the resistance change of the electro conductive liquid in the channel, its deformation can be measured. The proposed tactile sensor is composed of two parallel channel filled with electro conductive liquid, therefore, by comparing the resistance changes of each channel to the deformation, only the contacting force can be measured independently. Since a liquid is used for the sensing material, the proposed liquid tactile sensor can be easily attached to movable portions as the joints of robots. In the paper, we measured the sensing characteristics of the liquid tactile sensor to the stretch, bend, and contact force. Finally, the efficiency of the sensor was demonstrated by measuring the contact force from 0 to 3.0N by attaching the 20% stretched liquid tactile sensor to curved surfaces with 0.05mm−1 in curvature.
An optimization framework for the development of efficient one-way car-sharing systems

Electric vehicle-sharing systems have been introduced to a number of cities as a means of increasing mobility, reducing congestion, and pollution. Electric vehicle-sharing systems can offer one or two-way services. One-way systems provide more flexibility to users since they can be dropped-off at any station. However, their modeling involves a number of complexities arising from the need to relocate vehicles accumulated at certain stations. The planning of one-way electric vehicle-sharing systems involves a host of strongly interacting decisions regarding the number, size and location of stations, as well as the fleet size. In this paper we develop and solve a multi-objective MILP model for planning one-way vehicle-sharing systems taking into account vehicle relocation and electric vehicle charging requirements. For real world problems the size of the problem becomes intractable due to the extremely large number of relocation variables. In order to cope with this problem we introduce an aggregate model using the concept of the virtual hub. This transformation allows the solution of the problem with a branch-and-bound approach. The proposed approach generates the efficient frontier and allows decision makers to examine the trade-off between operator’s and users’ benefits. The capabilities of the proposed approach are demonstrated on a large scale real world problem with available data from Nice, France. Extensive sensitivity analysis was performed by varying demand, station accessibility distance and subsidy levels. The results provide useful insights regarding the efficient planning of one-way electric vehicle-sharing systems and allow decision makers to quantify the trade-off between operator’s and users’ benefits.
Detecting integrity attacks on control systems using robust physical watermarking

Ensuring the security of control systems against integrity attacks is a major challenge. Due to the events of Stuxnet, replay attacks in particular have been considered by the research community. Replaying previous measurements of a system in steady state allows an adversary to generate statistically correct virtual outputs which can bypass traditional detectors. The adversary can then inject destabilizing inputs to cause damage to the plant. The method of injecting secret noisy control inputs, or physical watermarking, has recently been proposed to detect replay attacks. However, the proposed watermarking design methods assume that the adversary does not use his potential access to real time communication channels to create stealthy virtual outputs to send to the defender. In this paper, we formulate an attack model for an adversary who uses knowledge of the system as well as access to a subset of real time control inputs and sensor outputs to construct stealthy virtual outputs. A robust physical watermark and detector to counter such an adversary is proposed.
Digital image forgery detection using passive techniques: A survey

Today manipulation of digital images has become easy due to powerful computers, advanced photo-editing software packages and high resolution capturing devices. Verifying the integrity of images and detecting traces of tampering without requiring extra prior knowledge of the image content or any embedded watermarks is an important research field. An attempt is made to survey the recent developments in the field of digital image forgery detection and complete bibliography is presented on blind methods for forgery detection. Blind or passive methods do not need any explicit priori information about the image. First, various image forgery detection techniques are classified and then its generalized structure is developed. An overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed. The present status of image forgery detection technique is discussed along with a recommendation for future research. a 2013 Elsevier Ltd. All rights reserved.
Target-Dependent Twitter Sentiment Classification with Rich Automatic Features

Target-dependent sentiment analysis on Twitter has attracted increasing research attention. Most previous work relies on syntax, such as automatic parse trees, which are subject to noise for informal text such as tweets. In this paper, we show that competitive results can be achieved without the use of syntax, by extracting a rich set of automatic features. In particular, we split a tweet into a left context and a right context according to a given target, using distributed word representations and neural pooling functions to extract features. Both sentiment-driven and standard embeddings are used, and a rich set of neural pooling functions are explored. Sentiment lexicons are used as an additional source of information for feature extraction. In standard evaluation, the conceptually simple method gives a 4.8% absolute improvement over the state-of-the-art on three-way targeted sentiment classification, achieving the best reported results for this task.
The separability of working memory resources for spatial thinking and language processing: an individual differences approach.

The current study demonstrates the separability of spatial and verbal working memory resources among college students. In Experiment 1, we developed a spatial span task that taxes both the processing and storage components of spatial working memory. This measure correlates with spatial ability (spatial visualization) measures, but not with verbal ability measures. In contrast, the reading span test, a common test of verbal working memory, correlates with verbal ability measures, but not with spatial ability measures. Experiment 2, which uses an interference paradigm to cross the processing and storage demands of span tasks, replicates this dissociation and further demonstrates that both the processing and storage components of working memory tasks are important for predicting performance on spatial thinking and language processing tasks.
Social media affordances and governance in the workplace: An examination of organizational policies

This paper examines how organizations perceive affordances of social media and how they react to their employees’ use of social media through policies, a key means of organizational governance. Existing literature identified 4 affordances visibility, persistence, editability, and association (between people and between people and information) as action potentials of social media in organizations. Content analysis of a sample of organizational social media policies reveals that organizations especially reacted to the affordances of visibility and persistence much more than to the affordance of editability. It also discovers a third type of association (between employees and organization). It shows how organizations’ reactions to social media evolved from being solely concerned with risk management to also considering its value-generating potential.
Agents That Explain Their Own Actions

Computer generated battleeeld agents need to be able to explain the rationales for their actions. Such explanations make it easier to validate agent behavior, and can enhance the eeectiveness of the agents as training devices. This paper describes an explanation capability called Debrief that enables agents implemented in Soar to describe and justify their decisions. Debrief determines the motivation for decisions by recalling the context in which decisions were made, and determining what factors were critical to those decisions. In the process Debrief learns to recognize similar situations where the same decision would be made for the same reasons. Debrief currently being used by the TacAir-Soar tactical air agent to explain its actions , and is being evaluated for incorporation into other reactive planning agents.
Evaporative Cooling of Actuators for Humanoid Robots

Autonomous humanoid robots need high torque actuators to be able to walk and run. One problem in this context is the heat generated. In this paper we propose to use water evaporation to improve cooling of the motors. Simulations based on thermodynamic calculations as well as measurements on real actuators show that, under the assumption of the load of a soccer game, cooling can be considerably improved with relatively small amounts of water.
Including surge arresters in the lightning performance analysis of 132kV transmission line

Line arresters are considered as an effective way to improve the lightning performance of transmission lines, especially in parts of line that suffer from high soil resistivity and lightning ground flash density. This paper presents results of the application of line surge arresters on the 132KV double circuit transmission line in EMTP-RV and all the practical scenarios for installation of surge arresters. The study has shown that a significant level of improvement can be reached by installing arresters at all or only some of the line phases. It can increase the strength of the line to withstand lightning currents up to -292kA. the probability of having this lightning current, is practically zero.
Artificial neural networks for automatic ECG analysis

The analysis of the ECG can beneet from the wide availability of computing technology as far as features and performances as well. This paper presents some results achieved by carrying out the classiication tasks of a possible equipment integrating the most common features of the ECG analysis: arrhythmia, myocardial ischemia, chronic alterations. Several ANN architectures are implemented, tested, and compared with competing alternatives. Approach, structure, and learning algorithm of ANN were designed according to the features of each particular classiication task. The trade{oo between the time consuming training of ANNs and their performances is also explored. Data pre-and post-processing eeorts on the system performance were critically tested. These eeorts' crucial role on the reduction of the input space dimensions, on a more signiicant description of the input features, and on improving new or ambiguous event processing has been also documented. Finally, the algorithm assessment was done on data coming from all the currently available ECG databases.
Attitudes toward online shopping and the Internet

Since the explosion of the Web as a business medium, one of its primary uses has been for marketing. Soon, the Web will become a critical distribution channel for the majority of successful enterprises. The mass media, consumer marketers and advertising agencies seem to be in the midst of Internet discovery and exploitation. Before a company can envision what might sell online in the coming years, it must ®rst understand the attitudes and behaviour of its potential customers. Hence, this study examines attitudes toward various aspects of online shopping and provides a better understanding of the potential of electronic commerce for both researchers and practitioners.
Seeing Your Face Is Not Enough: An Inertial Sensor-Based Liveness Detection for Face Authentication

Leveraging built-in cameras on smartphones and tablets, face authentication provides an attractive alternative of legacy passwords due to its memory-less authentication process. However, it has an intrinsic vulnerability against the media-based facial forgery (MFF) where adversaries use photos/videos containing victims' faces to circumvent face authentication systems. In this paper, we propose FaceLive, a practical and robust liveness detection mechanism to strengthen the face authentication on mobile devices in fighting the MFF-based attacks. FaceLive detects the MFF-based attacks by measuring the consistency between device movement data from the inertial sensors and the head pose changes from the facial video captured by built-in camera. FaceLive is practical in the sense that it does not require any additional hardware but a generic front-facing camera, an accelerometer, and a gyroscope, which are pervasively available on today's mobile devices. FaceLive is robust to complex lighting conditions, which may introduce illuminations and lead to low accuracy in detecting important facial landmarks; it is also robust to a range of cumulative errors in detecting head pose changes during face authentication.
Language in context: emergent features of word, sentence, and narrative comprehension

Context exerts a powerful effect on cognitive performance and is clearly important for language processing, where lexical, sentential, and narrative contexts should differentially engage neural systems that support lexical, compositional, and discourse level semantics. Equally important, but thus far unexplored, is the role of context within narrative, as cognitive demands evolve and brain activity changes dynamically as subjects process different narrative segments. In this study, we used fMRI to examine the impact of context, comparing responses to a single, linguistically matched set of texts when these were differentially presented as random word lists, unconnected sentences and coherent narratives. We found emergent, context-dependent patterns of brain activity in each condition. Perisylvian language areas were always active, consistent with their supporting core linguistic computations. Sentence processing was associated with expanded activation of the frontal operculum and temporal poles. The same stimuli presented as narrative evoked robust responses in extrasylvian areas within both hemispheres, including precuneus, medial prefrontal, and dorsal temporo-parieto-occipital cortices. The right hemisphere was increasingly active as contextual complexity increased, maximal at the narrative level. Furthermore, brain activity was dynamically modulated as subjects processed different narrative segments: left hemisphere activity was more prominent at the onset, and right hemisphere more prominent at the resolution of a story, at which point, it may support a coherent representation of the narrative as a whole. These results underscore the importance of studying language in an ecologically valid context, suggesting a neural model for the processing of discourse.
Using Test Oracles Generated from Program Documentation

|This paper illustrates how software can be described precisely using LD-relations, how these descriptions can be presented in a readable manner using tabular notations, and one way such descriptions can be used to test programs. We describe an algorithm that can be used to generate a test oracle from program documentation, and present the results of using a tool based on it to help test part of a commercial network management application. The results demonstrate that these methods can be eeective at detecting errors and greatly increase the speed and accuracy of test evaluation when compared with manual evaluation. Such oracles can be used for unit testing, {in situ} testing, constructing self-checking software and ensuring consistency between code and documentation.
The Role of Technology Acceptance Model in Explaining Effect on E-Commerce Application System

Today e-commerce has become crucial element to transform some of the world countries into an information society. Business to consumer (B2C) in the developing countries is not yet a normalcy as compared to the developed countries. Consumer behaviour research has shown disappointing results regarding the overall use of the Web for online shopping, despite its considerable promise as a channel for commerce. As the use of the Internet continues to grow in all aspects of daily life, there is an increasing need to better understand what trends of internet usage and to study the barriers and problem of ecommerce adoption. Hence, the purpose of this research is to define how far Technology Acceptance Model (TAM) contributed in e-commerce adoption. Data for this study was collected by the means of a survey conducted in Malaysia in 2010. A total of 611 questionnaire forms were delivered to respondents. The location of respondents was within Penang state. By studying this sample, conclusions would be drawn to generalize the interests of the population.
Use of computer technology to help students with special needs.

Millions of students across the United States cannot benefit fully from a traditional educational program because they have a disability that impairs their ability to participate in a typical classroom environment. For these students, computer-based technologies can play an especially important role. Not only can computer technology facilitate a broader range of educational activities to meet a variety of needs for students with mild learning disorders, but adaptive technology now exists than can enable even those students with severe disabilities to become active learners in the classroom alongside their peers who do not have disabilities. This article provides an overview of the role computer technology can play in promoting the education of children with special needs within the regular classroom. For example, use of computer technology for word processing, communication, research, and multimedia projects can help the three million students with specific learning and emotional disorders keep up with their nondisabled peers. Computer technology has also enhanced the development of sophisticated devices that can assist the two million students with more severe disabilities in overcoming a wide range of limitations that hinder classroom participation--from speech and hearing impairments to blindness and severe physical disabilities. However, many teachers are not adequately trained on how to use technology effectively in their classrooms, and the cost of the technology is a serious consideration for all schools. Thus, although computer technology has the potential to act as an equalizer by freeing many students from their disabilities, the barriers of inadequate training and cost must first be overcome before more widespread use can become a reality.
Combining deep learning and hand-crafted features for skin lesion classification

Melanoma is one of the most lethal forms of skin cancer. It occurs on the skin surface and develops from cells known as melanocytes. The same cells are also responsible for benign lesions commonly known as moles, which are visually similar to melanoma in its early stage. If melanoma is treated correctly, it is very often curable. Currently, much research is concentrated on the automated recognition of melanomas. In this paper, we propose an automated melanoma recognition system, which is based on deep learning method combined with so called hand-crafted RSurf features and Local Binary Patterns. The experimental evaluation on a large publicly available dataset demonstrates high classification accuracy, sensitivity, and specificity of our proposed approach when it is compared with other classifiers on the same dataset.