nils-herrmann/clean_scirepeval huggingface dataset:
Influence of External Currents in Sensors Based on PCB Rogowski Coils

A current sensor based in the Rogowski coil is an innovative measuring system that gives advantages with respect to conventional measuring systems based in current transformers with magnetic core , [2].and . Their main advantages are: the linearity, the span and the bandwidth. Different kinds of manufacturing allow to obtain an important variety of Rogowski coils with different properties. One way of manufacturing is using the same method as for producing printed circuit boards, so by this way is possible to produce coils very similar and with a high precision. The authors are working in current measurement with Rogowski coils or Hall effect sensors and in particular in the realization of good and accurate coils [4] and . In this work, the influence of external currents to the coil in the measured current by the coil has been evaluated.
Lumped circuit model analysis of meander line antennas

The past decade has seen phenomenal advances in portable electronics technology like mobile phones, RFID tags and MP3 players. This has led to the development of System in Package (SiP) which combines all the necessary components into a single package. Miniaturization of RF circuit technology has resulted in the need for miniaturized antennas. Meander line antennas are widely used in applications where compactness and miniaturization are key objectives. Although this antenna has been widely used, yet no simple analytical model except those using complicated numerical techniques is available. In this paper, we present a simple analytical model to calculate the resonant frequency of the antenna employing a lumped equivalent circuit model. Circuit response of a typical meander line antenna using our model has been compared with simulated antenna response using Method of Moments based simulator IE3D with good agreement, thereby validating our approach.
Objective and perceived arousal during performance of tasks with elements of social threat: the influence of anxiety sensitivity.

Physiological arousal serves to maintain social anxiety disorder by skewing self-perception. Anxiety sensitivity is associated with the disorder and exaggerated perceptions of arousal, but has not been tested as explaining exaggerated perceived arousal in social contexts. The aim of this investigation was to address this issue.



A total of 42 individuals participated in three tasks associated with potential social threat (i.e., a speech, typing task, hyperventilation) and completed measures of trait social anxiety and anxiety sensitivity. State anxiety, perceived arousal, and objective arousal were assessed during each task.



Trait social anxiety and anxiety sensitivity were correlated with state anxiety and perceived arousal, but not objective arousal, during the tasks. Anxiety sensitivity mediated the relationships between trait social anxiety and perceived arousal and between trait social anxiety and state anxiety for the typing and hyperventilation tasks.



Although the sample likely included a number of individuals with social anxiety disorder, the sample was mostly comprised of individuals without a diagnosis. The current results can be extended to clinical presentations to some extent, but future research is needed to further explore the demonstrated relationships in samples of individuals with social anxiety disorder.



Anxiety sensitivity may play a crucial role in perceptions of arousal and state anxiety in the context of potential social threats, warranting attention from researchers and clinicians focussing on social anxiety disorder.
The role of the self in mindblindness in autism

Since its inception the 'mindblindness' theory of autism has greatly furthered our understanding of the core social-communication impairments in autism spectrum conditions (ASC). However, one of the more subtle issues within the theory that needs to be elaborated is the role of the 'self'. In this article, we expand on mindblindness in ASC by addressing topics related to the self and its central role in the social world and then review recent research in ASC that has yielded important insights by contrasting processes relating to both self and other. We suggest that new discoveries lie ahead in understanding how self and other are interrelated and/or distinct, and how understanding atypical self-referential and social-cognitive mechanisms may lead to novel ideas as to how to facilitate social-communicative abilities in ASC.
Online shopping behavior model: A literature review and proposed model

In this study, we conducted extensive reviews of online shopping literatures and proposed a hierarchy model of online shopping behavior. We collected 47 studies and classified them by variables used. Some critical points were found that research framework, methodology, and lack of cross-cultural comparison, etc So we developed a cross-cultural model of online shopping including shopping value, attitudes to online retailer's attributes and online purchasing based on the integrated V-A-B model.
Cognitive enhancement.

Cognitive enhancement refers to the improvement of cognitive ability in normal healthy individuals. In this article, we focus on the use of pharmaceutical agents and brain stimulation for cognitive enhancement, reviewing the most common methods of pharmacologic and electronic cognitive enhancement, and the mechanisms by which they are believed to work, the effectiveness of these methods and their prevalence. We note the many gaps in our knowledge of these matters, including open questions about the size, reliability and nature of the enhancing effects, and we conclude with recommendations for further research.  The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.
A simple stimulus generator for testing single-channel monopulse processor

The monopulse antenna tracking system is the preferred choice where higher pointing accuracy is required because of its inherent advantages. There are three possible configurations for realizing monopulse tracking system. One of the configurations is called single channel monopulse tracking system as it requires only one down converter chain. In this configuration, the sum and both (AZ/EL) error signals are combined to reduce the required number of down converters. A single channel monopulse processor is vital subsystem of a single channel monopulse tracking system which extracts the pointing error information from the IF signal. During the development, these processors need to be tested for its functionality in the laboratory which requires a stimulus generator. The stimulus generator generates an IF signal which mimics the real time signal and can be used for debugging and functional verification. This paper presents a simple approach for realizing a stimulus generator for single channel monopulse processor. A stimulus generator has been developed using this approach and has been used for laboratory testing of a single channel monopulse processor. The tested single channel monopulse processor has been successfully integrated with the earth station antenna tracking chain at NRSC, Hyderabad, India and used for tracking the LEO satellites.
Multi-Strategy Sentiment Analysis of Consumer Reviews Based on Semantic Fuzziness

Since Internet has become an excellent source of consumer reviews, the area of sentiment analysis (also called sentiment extraction, opinion mining, opinion extraction, and sentiment mining) has seen a large increase in academic interest over the last few years. Sentiment analysis mines opinions at word, sentence, and document levels, and gives sentiment polarities and strengths of articles. As known, the opinions of consumers are expressed in sentiment Chinese phrases. But due to the fuzziness of Chinese characters, traditional machine learning techniques can not represent the opinion of articles very well. In this paper, we propose a multi-strategy sentiment analysis method with semantic fuzziness to solve the problem. The results show that this hybrid sentiment analysis method can achieve a good level of effectiveness.
Social media-induced technostress: Its impact on the job performance of it professionals and the moderating role of job characteristics

Using social media during work hours for non-work-related reasons is becoming commonplace. Organizations are therefore challenged with identifying and overcoming the consequences of such use. Social media-induced technostress has been identified as an important unintended consequence of using social media at work, as it could negatively impact job performance. This study draws on Person-Environment Fit to investigate the relationship between social media-induced technostress and job performance in IT professionals, and the moderating effect of job characteristics on this relationship. The results indicate that social media-induced technostress is negatively related to job performance and the negative impact of social media-induced technostress is intensified when the job characteristics are low. This work extends the literature on job-stress, social media, technostress, and job characteristics.
Coarse to Fine: Diffusing Categories in Wikipedia

Automatic taxonomy construction aims to build a categorization system without human efforts. Traditional textual pattern based methods extract hyponymy relation in raw texts. However, these methods usually yield low precision and recall. In this paper, we propose a method to automatically find diffusing attributes to a category from Wikipedia infoboxes. We use the diffusing attribute to diffuse a coarsegrained category into several fine-grained subcategories and generate a finer-grained taxonomy. Experiments show our method can find proper diffusing attributes to categories across various domains.
Building quadrotors with Arduino for indoor environments

This paper discusses quadrotors in indoor environments with Arduino, an open source electronics platform, and MATLAB. In the world, there are a lot of commercial quadrotors that equip feedback controllers. But most of such quadrotors are not allowed to tune the parameter of the controller and to implement another types of controllers. Similarly, most of the quadrotors are not small enough to fly in a room where multiple quadrotors fly at the same time. This paper instructs how to build a palm-sized quadrotor that has an Arduino compatible circuit and a printed out frame. In a test flight, PD control by a MATLAB code is applied to the developed quadrotor.
Real time contextual collective anomaly detection over multiple data streams

Anomaly detection has always been a critical and challenging problem in many application areas such as industry, healthcare, environment and finance. This problem becomes more di cult in the Big Data era as the data scale increases dramatically and the type of anomalies gets more complicated. In time sensitive applications like real time monitoring, data are often fed in streams and anomalies are required to be identified online across multiple streams with a short time delay. The new data characteristics and analysis requirements make existing solutions no longer suitable. In this paper, we propose a framework to discover a new type of anomaly called contextual collective anomaly over a collection of data streams in real time. A primary advantage of this solution is that it can be seamlessly integrated with real time monitoring systems to timely and accurately identify the anomalies. Also, the proposed framework is designed in a way with a low computational intensity, and is able to handle large scale data streams. To demonstrate the e↵ectiveness and e ciency of our framework, we empirically validate it on two real world applications.
CPW to waveguide transition with tapered slotline probe

A new CPW to waveguide transition is developed based on the concept of tapered slot antenna and E-plane probe coupling. The transition consists of a tapered slotline probe and a slotline to CPW matching section. The current design has the advantages of broad bandwidth, compact size, low fabrication cost, and high reliability. The characteristics of a prototype transition are investigated by numerical simulation on Duroid substrate and WR-90 waveguide. The back-to-back combination is measured to verify the agreement with the simulated results and realization of this design.
Hypothalamic-pituitary-adrenal axis, neuroendocrine factors and stress.

The stress system coordinates the adaptive responses of the organism to stressors of any kind.(1). The main components of the stress system are the corticotropin-releasing hormone (CRH) and locus ceruleus-norepinephrine (LC/NE)-autonomic systems and their peripheral effectors, the pituitary-adrenal axis, and the limbs of the autonomic system. Activation of the stress system leads to behavioral and peripheral changes that improve the ability of the organism to adjust homeostasis and increase its chances for survival. The CRH and LC/NE systems stimulate arousal and attention, as well as the mesocorticolimbic dopaminergic system, which is involved in anticipatory and reward phenomena, and the hypothalamic beta-endorphin system, which suppresses pain sensation and, hence, increases analgesia. CRH inhibits appetite and activates thermogenesis via the catecholaminergic system. Also, reciprocal interactions exist between the amygdala and the hippocampus and the stress system, which stimulates these elements and is regulated by them. CRH plays an important role in inhibiting GnRH secretion during stress, while, via somatostatin, it also inhibits GH, TRH and TSH secretion, suppressing, thus, the reproductive, growth and thyroid functions. Interestingly, all three of these functions receive and depend on positive catecholaminergic input. The end-hormones of the hypothalamic-pituitary-adrenal (HPA) axis, glucocorticoids, on the other hand, have multiple roles. They simultaneously inhibit the CRH, LC/NE and beta-endorphin systems and stimulate the mesocorticolimbic dopaminergic system and the CRH peptidergic central nucleus of the amygdala. In addition, they directly inhibit pituitary gonadotropin, GH and TSH secretion, render the target tissues of sex steroids and growth factors resistant to these substances and suppress the 5' deiodinase, which converts the relatively inactive tetraiodothyronine (T(4)) to triiodothyronine (T(3)), contributing further to the suppression of reproductive, growth and thyroid functions. They also have direct as well as insulin-mediated effects on adipose tissue, ultimately promoting visceral adiposity, insulin resistance, dyslipidemia and hypertension (metabolic syndrome X) and direct effects on the bone, causing "low turnover" osteoporosis. Central CRH, via glucocorticoids and catecholamines, inhibits the inflammatory reaction, while directly secreted by peripheral nerves CRH stimulates local inflammation (immune CRH). CRH antagonists may be useful in human pathologic states, such as melancholic depression and chronic anxiety, associated with chronic hyperactivity of the stress system, along with predictable behavioral, neuroendocrine, metabolic and immune changes, based on the interrelations outlined above. Conversely, potentiators of CRH secretion/action may be useful to treat atypical depression, postpartum depression and the fibromyalgia/chronic fatigue syndromes, all characterized by low HPA axis and LC/NE activity, fatigue, depressive symptomatology, hyperalgesia and increased immune/inflammatory responses to stimuli.
Probabilistic vehicle trajectory prediction over occupancy grid map via recurrent neural network

In this paper, we propose an efficient vehicle trajectory prediction framework based on recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different from that of regular moving objects since it is affected by various latent factors including road structure, traffic rules, and driver's intention. Previous state of the art approaches use sophisticated vehicle behavior model describing these factors and derive the complex trajectory prediction algorithm, which requires a system designer to conduct intensive model optimization for practical use. Our approach is data-driven and simple to use in that it learns complex behavior of the vehicles from the massive amount of trajectory data through deep neural network model. The proposed trajectory prediction method employs the recurrent neural network called long short-term memory (LSTM) to analyze the temporal behavior and predict the future coordinate of the surrounding vehicles. The proposed scheme feeds the sequence of vehicles' coordinates obtained from sensor measurements to the LSTM and produces the probabilistic information on the future location of the vehicles over occupancy grid map. The experiments conducted using the data collected from highway driving show that the proposed method can produce reasonably good estimate of future trajectory.
Survey on Hadoop and Introduction to YARN Amogh

Big Data, the analysis of large quantities of data to gain new insight has become a ubiquitous phrase in recent years. Day by day the data is growing at a staggering rate. One of the efficient technologies that deal with the Big Data is Hadoop, which will be discussed in this paper. Hadoop, for processing large data volume jobs uses MapReduce programming model. Hadoop makes use of different schedulers for executing the jobs in parallel. The default scheduler is FIFO (First In First Out) Scheduler. Other schedulers with priority, pre-emption and non-pre-emption options have also been developed. As the time has passed the MapReduce has reached few of its limitations. So in order to overcome the limitations of MapReduce, the next generation of MapReduce has been developed called as YARN (Yet Another Resource Negotiator). So, this paper provides a survey on Hadoop, few scheduling methods it uses and a brief introduction to YARN. Hadoop, HDFS, MapReduce, Schedulers, YARN.
Full On-Chip CMOS Low-Dropout Voltage Regulator

This paper proposes a solution to the present bulky external capacitor low-dropout (LDO) voltage regulators with an external capacitorless LDO architecture. The large external capacitor used in typical LDOs is removed allowing for greater power system integration for system-on-chip (SoC) applications. A compensation scheme is presented that provides both a fast transient response and full range alternating current (AC) stability from 0- to 50-mA load current even if the output load is as high as 100 pF. The 2.8-V capacitorless LDO voltage regulator with a power supply of 3 V was fabricated in a commercial 0.35-mum CMOS technology, consuming only 65 muA of ground current with a dropout voltage of 200 mV. Experimental results demonstrate that the proposed capacitorless LDO architecture overcomes the typical load transient and ac stability issues encountered in previous architectures.
A cluster-based resampling method for pseudo-relevance feedback

Typical pseudo-relevance feedback methods assume the top-retrieved documents are relevant and use these pseudo-relevant documents to expand terms. The initial retrieval set can, however, contain a great deal of noise. In this paper, we present a cluster-based resampling method to select better pseudo-relevant documents based on the relevance model. The main idea is to use document clusters to find dominant documents for the initial retrieval set, and to repeatedly feed the documents to emphasize the core topics of a query. Experimental results on large-scale web TREC collections show significant improvements over the relevance model. For justification of the resampling approach, we examine relevance density of feedback documents. A higher relevance density will result in greater retrieval accuracy, ultimately approaching true relevance feedback. The resampling approach shows higher relevance density than the baseline relevance model on all collections, resulting in better retrieval accuracy in pseudo-relevance feedback. This result indicates that the proposed method is effective for pseudo-relevance feedback.
Multimodal feature extraction and fusion for semantic mining of soccer video: a survey

This paper presents a classified review of soccer video analysis works. The existing approaches in the aspects of highlight event detection, video summarization and retrieval based on video stream, ball and player tracking for provision of match statistics, technical and tactical analysis and application of different sources in soccer video analysis have been surveyed. In addition, some major existing commercial softwares developed for video analysis are introduced and compared. With regard to the existing challenge for automatic and realtime provision of video analysis, different computer vision approaches are discussed and compared. Audio, video and text feature extraction methods have been investigated and the future trends for improvement of the reviewed systems have been introduced in terms of response time optimization, increase of precision and eliminating the need of human intervention for video analysis.
Conceptual data structures for personal knowledge management

Designing a model and tools that are (a) capable of representing and handling personal knowledge in different degrees of structuredness and formalisation and (b) usable and extensible by end-users.  This paper presents the result of analysing literature and various data-models and formalism used to structure information on the desktop.  The unified data model (CDS) is capable of representing structures from various information tools, e. g. documents, file system, hypertext, tagging, and mind maps. The five knowledge axes of CDS are: identity, order, hierarchy, annotation and linking.  The CDS model is based on text. Extensions for multimedia annotations have not been investigated.  Future PKM tools should take the mentioned shortcoming of existing PKM tools into account. Implementing the CDS model can be a way to make PKM tools interoperable.  This paper presents research combining cognitive psychology, personal knowledge management and semantic web technologies. The CDS model shows a way to let end-users work on different levels of granularity and different levels of formality in one environment.  The most important contribution of management in the 20th century was to increase manual worker productivity fifty-fold. The most important contribution of management in the 21st century will be to increase knowledge worker productivity – hopefully by the same percentage. [...] The methods, however, are totally different from those that increased the productivity of manual workers. " Drucker (1999a, p. 79) What might these methods be? The field of knowledge management investigates since 1995 (Stankosky, 2005) how people and knowledge work together. North (2007) defines knowledge work as work based on knowledge with an immaterial result; value creation is based on processing, generating and communicating knowledge. Polanyi (1966) makes a distinction between explicit knowledge encoded in artefacts such as books or web pages, and tacit knowledge which resides in the individual. The SECI-model of Nonaka (1994) describes knowledge transfers between humans and artefacts. The field of knowledge management has focused on knowledge transfer between people, either via socialisation or via externalised artefacts. The high expectations of central enterprise knowledge repositories have often not been met (Braganza and Mollenkramer, 2002). The following wave of expert finders and corporate white pages focused mostly on connecting the right people and let them communicate. Today, knowledge workers are flooded with information (Alvarado et al., 2003). The field of Personal …