nils-herrmann/clean_scirepeval huggingface dataset:
Design of Ultrawideband Planar Monopole Antennas of Circular and Elliptical Shape

An efficient approach is described for designing ultrawideband (UWB) antennas in the form of planar monopoles of elliptical and circular shape. To avoid the time consuming trial-and-error approach presented in other works, simple design formulas for this type of radiators are described and their validity is tested via electromagnetic analysis and measurements. Full electromagnetic wave investigations are performed assuming three types of substrates with wide range of dielectric constant and thickness. The presented results show that the proposed method can be applied directly to design planar antennas that cover the ultrawide frequency band from 3.1 GHz to more than 10.6 GHz. Four types of monopole antennas were manufactured using RT6010LM substrate and their operation was tested in terms of return loss, radiation pattern characteristics, gain, and time domain response. The developed antennas feature UWB behavior with near omnidirectional characteristics and good radiation efficiency. The time domain transmission tests between two identical elements show that the manufactured circular monopoles offer better performance in terms of distortionless pulse transmission than their elliptically shaped counter parts. These antennas are also assessed in terms of fidelity factor. The manufactured antennas show a high fidelity factor which is more than 90% for the face-to-face orientation.
Multiplicative Binding , Representation Operators & Analogy

Analogical inference depends on systematic substitution of the components of compositional structures. Simple systematic substitution has been achieved in a number of connectionist systems that support binding (the abilit y to create connectionist representations of the combination of component representations). These systems have used various implementations of two generic composition operators: bind() and bundle(). This paper introduces a novel implementation of the bind() operator that is simple, can be eff iciently implemented, and highlights the relationship between retrieval queries and analogical mapping.
Incorporating Entity Correlation Knowledge into Topic Modeling

Latent Dirichlet Allocation (LDA) is a popular topic modeling technique for exploring hidden topics in text corpora. Standard LDA model suffers the problem that the topic assignment of each word is independent and lacks the mechanism to utilize the rich prior background knowledge to learn semantically coherent topics. To address this problem, in this paper, we propose a model called Entity Correlation Latent Dirichlet Allocation (EC-LDA) by incorporating constraints derived from entity correlations as the prior knowledge into LDA topic model. Different from other knowledge-based topic models which extract the knowledge information directly from the train dataset itself or even from the human judgements, for our work, we take advantage of the prior knowledge from the external knowledge base (Freebase 1, in our experiment). Hence, our approach is more suitable to widely kinds of text corpora in different scenarios. We fit our proposed model using Gibbs sampling. Experiment results demonstrate the effectiveness of our model compared with standard LDA.
3D convolutional neural networks by modal fusion

We propose multi-view and volumetric convolutional neural networks (ConvNets) for 3D shape recognition, which combines surface normal and height fields to capture local geometry and physical size of an object. This strategy helps distinguishing between objects with similar geometries but different sizes. This is especially useful for enhancing volumetric ConvNets and classifying 3D scans with insufficient surface details. Experimental results on CAD and real-world scan datasets showed that our technique outperforms previous approaches.
COMPARISON OF EXISTING TECHNOLOGY ACCEPTANCE THEORIES AND MODELS TO SUGGEST A WELL IMPROVED THEORY / MODEL

This paper presents a part of an on-going research study which aims to develop a model on technology acceptance appropriate to the Sri Lankan context. Current paper reviews the theoretical literature to propose an improved theory/model from a comparison of existing technology acceptance theories/models. In this technological era, awareness of technology is important in today’s fast changing networked society. Since technology is of little value unless it is used, how people accept and use technology may have salient theoretical and practical implications. Therefore, researchers concurred on the fact that quality elucidations occur because of robust theories/models on technology acceptance. Despite of the negative aspects identified in the theoretical paradigms of these theories/models, one significant paradigm out of fourteen theories/models could be drawn from the conceptual review on theory/model comparison presented here. Among the fourteen theories reviewed, UTAUT seems to be an improved theory that could provide a useful tool to assess the likelihood of success for technology acceptance studies.
Emotional intelligence and emotional creativity.

Three studies examined the relationship between emotional intelligence (EI) and emotional creativity (EC) and whether each construct was predictive of creative behavior. It was hypothesized that the relationship between EI and EC corresponds to the relationship between cognitive intelligence and creative ability. Therefore, EI and EC were expected to be two distinct sets of abilities. Intercorrelations and confirmatory factor analyses supported the hypothesis. Furthermore, it was hypothesized that EC, but not EI, would correlate with behavioral creativity. Self-report measures of EC significantly correlated with laboratory and self-reported creativity measures in both studies, while ability measures of EC only correlated with self-reported artistic activity. EI was uncorrelated with creative behavior.
An unusual case of asymptomatic spontaneous umbilical endometriosis treated with skin-sparing excision

Spontaneous umbilical endometriosis is a rare extrapelvic manifestation of endometriosis. Very few such cases have been previously reported, almost always associated with a variety of symptoms, usually during menstruation. We present a case of asymptomatic umbilical endometriosis treated with skin-sparing excision. Differential diagnoses relevant to the clinician, as well as treatment options, are also presented. Surgeons should always consider umbilical endometriosis in their diagnostic approach when confronted with atypical umbilical nodules, regardless of whether they are symptomatic or not.
On Maximal Spherical Codes I

We investigate the possibilities for attaining two Levenshtein upper bounds for spherical codes. We find the distance distributions of all codes meeting these bounds. Then we show that the fourth Levenshtein bound can be attained in some very special cases only. We prove that no codes with an irrational maximal scalar product meet the third Levenshtein bound. So in dimensions 3 ≤ n ≤ 100 exactly seven codes are known to attain this bound and ten cases remain undecided. Moreover, the first two codes (in dimensions 5 and 6) are unique up to isometry. Nonexistence of maximal codes in all dimensions n with cardinalities between 2n+1 and 2n+ [7 √ n ] is shown as well. We prove nonexistence of several infinite families of maximal codes whose maximal scalar product is rational. The distance distributions of the only known nontrivial infinite family of maximal codes (due to Levenshtein) are given.
Keyword Search in Spatial Databases: Towards Searching by Document

This work addresses a novel spatial keyword query called the m-closest keywords (mCK) query. Given a database of spatial objects, each tuple is associated with some descriptive information represented in the form of keywords. The mCK query aims to find the spatially closest tuples which match m user-specified keywords. Given a set of keywords from a document, mCK query can be very useful in geotagging the document by comparing the keywords to other geotagged documents in a database. To answer mCK queries efficiently, we introduce a new index called the bR*-tree, which is an extension of the R*-tree. Based on bR*-tree, we exploit a priori-based search strategies to effectively reduce the search space. We also propose two monotone constraints, namely the distance mutex and keyword mutex, as our a priori properties to facilitate effective pruning. Our performance study demonstrates that our search strategy is indeed efficient in reducing query response time and demonstrates remarkable scalability in terms of the number of query keywords which is essential for our main application of searching by document.
Cybercrime and cyber-security issues associated with China: some economic and institutional considerations

China is linked to cybercrimes of diverse types, scales, motivations and objectives. The Chinese cyberspace thus provides an interesting setting for the study of cybercrimes. In this paper, we first develop typology, classification and characterization of cybercrimes associated with China, which would help us understand modus operandi, structures, profiles and personal characteristics of cybercrime organizations and potential perpetrators, the signature aspects and goals of cybercrimes, the nature and backgrounds of the criminal groups involved, characteristics of potential targets for criminal activities, the nature and extent of the damage inflicted on the victims and the implications to and responses elicited from various actors. We then examine this issue from developmental and international political economy angles. Specifically, we delineate salient features of China’s politics, culture, human capital and technological issues from the standpoint of cyber-security and analyze emerging international relations and international trade issues associated with this phenomenon. Our analysis indicates that China’s global ambition, the shift in the base of regime legitimacy from MarxLeninism to economic growth, the strong state and weak civil society explain the distinctive pattern of the country’s cyber-attack and cybersecurity landscapes.
Evaluation of the Wireless M-Bus standard for future smart water grids

The most recent Wireless Sensor Networks technologies can provide viable solutions to perform automatic monitoring of the water grid, and smart metering of water consumptions. However, sensor nodes located along water pipes cannot access power grid facilities, to get the necessary energy imposed by their working conditions. In this sense, it is of basic importance to design the network architecture in such a way as to require the minimum possible power. This paper investigates the suitability of the Wireless Metering Bus protocol for possible adoption in future smart water grids, by evaluating its transmission performance, through simulations and experimental tests executed by means of prototype sensor nodes.
Cognitive measurements of graph aesthetics

Ware, Data Visualization Research Lab, Center for Coastal and Ocean Mapping, University of New Hampshire, 24 Colovos Road, Durham, NH 03824, U.S.A. Tel: 603 862 1138; Fax: 603 862 0839; E-mail: colinw@cisunix.unh.edu  A large class of diagrams can be informally characterized as node–link diagrams. Typically nodes represent entities, and links represent relationships between them. The discipline of graph drawing is concerned with methods for drawing abstract versions of such diagrams. At the foundation of the discipline are a set of graph aesthetics (rules for graph layout) that, it is assumed, will produce graphs that can be clearly understood. Examples of aesthetics include minimizing edge crossings and minimizing the sum of the lengths of the edges. However, with a few notable exceptions, these aesthetics are taken as axiomatic, and have not been empirically tested. We argue that human pattern perception can tell us much that is relevant to the study of graph aesthetics including providing a more detailed understanding of aesthetics and suggesting new ones. In particular, we find the importance of good continuity (ie keeping multi-edge paths as straight as possible) has been neglected. We introduce a methodology for evaluating the cognitive cost of graph aesthetics and we apply it to the task of finding the shortest paths in spring layout graphs. The results suggest that after the length of the path the two most important factors are continuity and edge crossings, and we provide cognitive cost estimates for these parameters. Another important factor is the number of branches emanating from nodes on the path. Information Visualization (2002) 00, 00 – 00. doi:10.1057/palgrave.ivs.9500013
‘Internet Addiction’: A Critical Review

It has been alleged by some academics that excessive Internet use can be pathological and addictive. This paper reviews what is known from the empirical literature on ‘Internet addiction’ and its derivatives (e.g., Internet Addiction Disorder, Pathological Internet Use, etc.) and assesses to what extent it exists. Empirical research into ‘Internet addiction’ can roughly be divided into five areas: (1) survey studies that compare excessive Internet users with non-excessive users, (2) survey studies that have examined vulnerable groups of excessive Internet use, most notably students, (3) studies that examine the psychometric properties of excessive Internet use, (4) case studies of excessive Internet users and treatment case studies, and (5) correlational studies examining the relationship of excessive Internet use with other behaviours (e.g., psychiatric problems, depression, self-esteem, etc.). Each of these areas is reviewed. It is concluded that if ‘Internet addiction’ does indeed exist, it affects a relatively small percentage of the online population. However, exactly what it is on the Internet that they are addicted to still remains unclear.
Navigating Digital Innovation - The Complementary Effect of Organizational and Knowledge Recombination

This paper reports findings from an exploratory series of case studies undertaken to better understand the impacts of digitization on organizational and knowledge recombination. While ‘digitalized firms’ are expected to frequently update their knowledge (e.g., big data analyses, ‘smarter’ products) and organizational structures (e.g., agile team structures, open innovation approaches), we know little about the interrelations between recombining knowledge and organizational capabilities. Therefore, we collected data from 19 interviewees in 8 different firms from four industries. Our study integrates theoretical notions from the literature on organizational and knowledge recombination theory and categorizes the emerging shifts arising from digitization. Our results suggest that the identified changes in the digital age manifest as increased proximity to the customer (by fully digitizing the customer interface and digital co-creation) and celerity to the markets (cross-organizational teams, and collaborations with start-ups and competitors) affecting the whole organization.
Factors Influencing Quality of Mobile Apps: Role of Mobile App Development Life Cycle

In this paper, The mobile application field has been receiving astronomical attention from the past few years due to the growing number of mobile app downloads and withal due to the revenues being engendered .With the surge in the number of apps, the number of lamentable apps/failing apps has withal been growing.Interesting mobile app statistics are included in this paper which might avail the developers understand the concerns and merits of mobile apps.The authors have made an effort to integrate all the crucial factors that cause apps to fail which include negligence by the developers, technical issues, inadequate marketing efforts, and high prospects of the users/consumers.The paper provides suggestions to eschew failure of apps. As per the various surveys, the number of lamentable/failing apps is growing enormously, primarily because mobile app developers are not adopting a standard development life cycle for the development of apps. In this paper, we have developed a mobile application with the aid of traditional software development life cycle phases (Requirements, Design, Develop, Test, and, Maintenance) and we have used UML, M-UML, and mobile application development technologies.
An exploration of crowdsourcing citation screening for systematic reviews

Systematic reviews are increasingly used to inform health care decisions, but are expensive to produce. We explore the use of crowdsourcing (distributing tasks to untrained workers via the web) to reduce the cost of screening citations. We used Amazon Mechanical Turk as our platform and 4 previously conducted systematic reviews as examples. For each citation, workers answered 4 or 5 questions that were equivalent to the eligibility criteria. We aggregated responses from multiple workers into an overall decision to include or exclude the citation using 1 of 9 algorithms and compared the performance of these algorithms to the corresponding decisions of trained experts. The most inclusive algorithm (designating a citation as relevant if any worker did) identified 95% to 99% of the citations that were ultimately included in the reviews while excluding 68% to 82% of irrelevant citations. Other algorithms increased the fraction of irrelevant articles excluded at some cost to the inclusion of relevant studies. Crowdworkers completed screening in 4 to 17 days, costing $460 to $2220, a cost reduction of up to 88% compared to trained experts. Crowdsourcing may represent a useful approach to reducing the cost of identifying literature for systematic reviews.
A Survey on Image Classification Approaches and Techniques

Object Classification is an important task within the field of computer vision. Image classification refers to the labelling of images into one of a number of predefined categories. Classification includes image sensors, image pre-processing, object detection, object segmentation, feature extraction and object classification.Many classification techniques have been developed for image classification. In this survey various classification techniques are considered; Artificial Neural Network(ANN), Decision Tree(DT), Support Vector Machine(SVM) and Fuzzy Classification
Performance analysis of supervised machine learning algorithms for text classification

The demand of text classification is growing significantly in web searching, data mining, web ranking, recommendation systems and so many other fields of information and technology. This paper illustrates the text classification process on different dataset using some standard supervised machine learning techniques. Text documents can be classified through various kinds of classifiers. Labeled text documents are used to classify the text in supervised classifications. This paper applied these classifiers on different kinds of labeled documents and measures the accuracy of the classifiers. An Artificial Neural Network (ANN) model using Back Propagation Network (BPN) is used with several other models to create an independent platform for labeled and supervised text classification process. An existing benchmark approach is used to analysis the performance of classification using labeled documents. Experimental analysis on real data reveals which model works well in terms of classification accuracy.
A precision relaxation oscillator with a self-clocked offset-cancellation scheme for implantable biomedical SoCs

Recently, there has been an increasing demand for SoCs in the biomedical field . In implantable applications, SoCs are designed under very stringent power and area constraints. The analog and mixed-signal circuits as well as digital circuits in those SoCs require a clock source, because clock-based signal-processing techniques, such as sampling and chopper stabilization, are often used. The primary clock source for such SoCs needs to provide good accuracy and long-term stability of the oscillation frequency ƒOSC to minimize variations and drifts of the system characteristics. A fairly pure clock signal is required to avoid signal distortion when sampling or chopping techniques are applied. Considering such a source is typically a free-running oscillator, and biomedical signals of typical interest reside at low frequencies, the close-in phase noise is important.
A Fast Parallel Algorithm for Thinning Digital Patterns

A fast parallel thinning algorithm is proposed in this paper. It consists of two subiterations: one aimed at deleting the south-east boundary points and the north-west corner points while the other one is aimed at deleting the north-west boundary points and the south-east corner points. End points and pixel connectivity are preserved. Each pattern is thinned down to a "skeleton" of unitary thickness. Experimental results show that this method is very effective.
1 TRANSFORMATIONAL LEADERSHIP AND JOB BEHAVIORS : THE MEDIATING ROLE OF CORE JOB CHARACTERISTICS

While the effects of transformational leadership on task performance and organizational citizenship behavior (OCB) are well-documented, the mechanisms that explain those effects remain unclear. We proposed that transformational l eadership is associated with the way followers view their jobs, in terms of Hackman and Ol ham’s (1976) core job characteristics. Our results support a structural equation model whe re the direct effects of transformational leadership on task performance and OCB are suppleme nt d by indirect effects through the mechanisms of job characteristics, intrinsic motiva tion, and goal commitment. Supplementary analyses revealed that the transformational leaders hip elationships were significantly stronger for followers with high leader-member exchange (LMX ) perceptions.
Where to Go Next: A Spatio-temporal LSTM model for Next POI Recommendation

Next Point-of-Interest (POI) recommendation is of great value for both location-based service providers and users. Recently Recurrent Neural Networks (RNNs) have been proved to be effective on sequential recommendation tasks. However, existing RNN solutions rarely consider the spatio-temporal intervals between neighbor checkins, which are essential for modeling user check-in behaviors in next POI recommendation. In this paper, we propose a new variant of LSTM, named STLSTM, which implements time gates and distance gates into LSTM to capture the spatio-temporal relation between successive check-ins. Specifically, one time gate and one distance gate are designed to control short-term interest update, and another time gate and distance gate are designed to control long-term interest update. Furthermore, to reduce the number of parameters and improve efficiency, we further integrate coupled input and forget gates with our proposed model. Finally, we evaluate the proposed model using four real-world datasets from various location-based social networks. Our experimental results show that our model significantly outperforms the state-of-the-art approaches for next POI recommendation.