nils-herrmann/clean_scirepeval huggingface dataset:
A Maturity Model for Assessing the Digital Readiness of Manufacturing Companies

“The most profound technologies are those that disappear... They weave themselves into the fabric of everyday life until they are indistinguishable from it” wrote computer scientist and visionary Mark Weiser nearly 25 years ago in his essay “The Computer for the 21st Century.” It turns out he was right: in the age of “Industry 4.0”, digital technologies are the core driver for the manufac‐ turing transformation. In fact, the introduction of such technologies allows companies to find solutions capable to turn increasing complexity into opportu‐ nities for ensuring sustainable competitiveness and profitable growth. Nonethe‐ less, the effective implementation in manufacturing still depends on the state of practice: it may slow down, or even worst, may prevent from implementation. Indeed, we assume that a minimum level of capabilities is required before imple‐ menting the digital technologies in a company. Based on this concern, our research question is “are manufacturing companies ready to go digital?”. This paper wants to illustrate a “tool” to answer this question by building a maturity assessment method to measure the digital readiness of manufacturing firms. Based on the inspiring principles of the CMMI (Capability Maturity Model Inte‐ gration) framework, we propose a model to set the ground for the investigation of company digital maturity. Different dimensions are used to assess 5 areas in which manufacturing key processes can be grouped: (1) design and engineering, (2) production management, (3) quality management, (4) maintenance manage‐ ment and (5) logistics management. Thus, the maturity model provides a norma‐ tive description of practices in each area and dimension, building a ranked order of practices (i.e. from low to high maturity). A scoring method for maturity assessment is subsequently defined, in order to identify the criticalities in imple‐ menting the digital transformation and to subsequently drive the improvement of the whole system. The method should be useful both to manufacturing companies and researchers interested in understanding the digital readiness level in the state of practice.
ELECTRONIC WORD OF MOUTH : FACTORS THAT INFLUENCE PURCHASE INTENTION Literature

With the rapid development of Internet and the emergence of Web 2.0 sites, user interaction has increased considerably, widening the scope of word-of mouth communication. People can now access information, exchange ideas and opinions, join various networks and socializing groups, regardless of their position on the globe. This new means of communication, electronic word of mouth (e-WOM), makes it possible for users to be inter-connected and participate in a continuous flow of information exchange. In literature, there have been identified multiple factors that can define electronic word of mouth and it has been noted that this phenomenon can influence the purchase intention of online consumers. However, due to the complexity of e-WOM, it’s very difficult to offer a single definition of this concept. Considering the ample area that electronic word of mouth may have an impact on, this article proposes a literature review of possible factors that influence the purchase intentions. Results will provide a baseline for developing a possible model for electronic word of mouth and its role in the purchase intention. Intercultural Communication and the Future of Education THE HUB Fusion between Social Sciences, Arts, Theology, Engineering and Management
A serious game model for cultural heritage

Serious games present a promising opportunity for learning, but the genre still lacks methodologies and tools for efficient and low-cost production, particularly for teacher and domain experts. This article gives an authoring framework that aims to provide structured support, from content design to final implementation. In particular, we have abstracted a conceptual model—the SandBox Serious Game - which relies on a generalization of task-based learning theory. The model invites players to perform cognitive tasks contextually while exploring information-rich virtual environments. We consider it particularly suited for cultural heritage entertainment applications. The model defines games that are set in realistic virtual worlds enriched with embedded educational tasks, which we have implemented as minigames. This approach simplifies the authoring work, which can easily be supported by visual authoring tools for ontology-based urban 3D modeling and implementation tasks, thus allowing an approach similar to the mind-maps concept. We propose a top-down methodology for content preparation, starting from a city-level analysis down to the single points of interest and associated tasks, which are instances of simple predefined minigame/quiz typologies. We provide examples and discuss criteria for selecting task typologies according to the authors' cognitive targets. Finally, we discuss the results of a user test, which took place in a lab, aimed at verifying the acquisition of cultural heritage knowledge in a pleasant and engaging way. Games appear particularly suited for supporting the study of images, especially of iconography. Compared to reading text, a game forces the player to focus more strongly on problems, which favors knowledge acquisition and retention. Learning complex concepts requires an investigative attitude, which can be spurred by well-designed games. Good design involves usability, graphic appeal, appropriate content, and the presence of connections which a player must discover in the content. Players should be asked to pay attention to and reason about their whole game activity - including the relationships between the game content, the brief introduction, and concluding texts. More comprehensive tests are needed to better investigate the educational effectiveness—however, the first results are promising, especially in terms of user motivation and creation of new opportunities for learning about CH.
Research Methodology

In this manuscript various components of research are listed and briefly discussed. The topics considered in this write-up cover a part of the research methodology paper of Master of Philosophy (M.Phil.) course and Doctor of Philosophy (Ph.D.) course. The manuscript is intended for students and research scholars of science subjects such as mathematics, physics, chemistry, statistics, biology and computer science. Various stages of research are discussed in detail. Special care has been taken to motivate the young researchers to take up challenging problems. Ten assignment works are given. For the benefit of young researchers a short interview with three eminent scientists is included at the end of the manuscript. Research is a logical and systematic search for new and useful information on a particular topic. It is an investigation of finding solutions to scientific and social problems through objective and systematic analysis. It is a search for knowledge, that is, a discovery of hidden truths. Here knowledge means information about matters. The information might be collected from different sources like experience, human beings, books, journals, nature, etc. A research can lead to new contributions to the existing knowledge. Only through research is it possible to make progress in a field. Research is done with the help of study, experiment, observation, analysis, comparison and reasoning. Research is in fact ubiquitous. For example, we know that cigarette smoking is injurious to health; heroine is addictive; cow dung is a useful source of biogas; malaria is due to the virus protozoan plasmod-ium; AIDS (Acquired Immuno Deficiency Syndrome) is due to the virus HIV (Human Immuno deficiency Virus). How did we know all these? We became aware of all these information only through research. More precisely, it seeks predictions of events and explanations, relationships and theories for them. The prime objectives of research are (1) to discover new facts (2) to verify and test important facts (3) to analyse an event or process or phenomenon to identify the cause and effect relationship (4) to develop new scientific tools, concepts and theories to solve and understand scientific and nonsci-entific problems (5) to find solutions to scientific, nonscientific and social problems and (6) to overcome or solve the problems occurring in our every day life. This is a fundamentally important question. No person would like to do research unless there are some motivating factors. Some of the motivations are the following: (1) to get a research …
Food image recognition using deep convolutional network with pre-training and fine-tuning

In this paper, we examined the effectiveness of deep convolutional neural network (DCNN) for food photo recognition task. Food recognition is a kind of fine-grained visual recognition which is relatively harder problem than conventional image recognition. To tackle this problem, we sought the best combination of DCNN-related techniques such as pre-training with the large-scale ImageNet data, fine-tuning and activation features extracted from the pre-trained DCNN. From the experiments, we concluded the fine-tuned DCNN which was pre-trained with 2000 categories in the ImageNet including 1000 food-related categories was the best method, which achieved 78.77% as the top-1 accuracy for UEC-FOOD100 and 67.57% for UEC-FOOD256, both of which were the best results so far. In addition, we applied the food classifier employing the best combination of the DCNN techniques to Twitter photo data. We have achieved the great improvements on food photo mining in terms of both the number of food photos and accuracy. In addition to its high classification accuracy, we found that DCNN was very suitable for large-scale image data, since it takes only 0.03 seconds to classify one food photo with GPU.
A rational account of pedagogical reasoning: Teaching by, and learning from, examples

Much of learning and reasoning occurs in pedagogical situations--situations in which a person who knows a concept chooses examples for the purpose of helping a learner acquire the concept. We introduce a model of teaching and learning in pedagogical settings that predicts which examples teachers should choose and what learners should infer given a teacher's examples. We present three experiments testing the model predictions for rule-based, prototype, and causally structured concepts. The model shows good quantitative and qualitative fits to the data across all three experiments, predicting novel qualitative phenomena in each case. We conclude by discussing implications for understanding concept learning and implications for theoretical claims about the role of pedagogy in human learning.
Enterprise Resource Planning: A Trio of Resources

Enterprise Resource Planning: A Trio of Resources Cindy P. Stevens a a Currently an assistant professor at Wentworth Institute of Technology, Boston, Massachusetts, for the Management of Technology (BMT) program. She holds an M.A. in Technical and Professional Communication from East Carolina University in Greenville, North Carolina, and a Ph.D. in Technology Management specializing in Digital Communications from Indiana State University. She can be reached at stevensc@wit.edu.
Nonlinear Analysis Methods for Reinforced Concrete Buildings with Shear walls

Proper modeling of the shear walls is very important for both linear and nonlinear analyses of building structures. In linear analyses of structures, Reinforced concrete (RC) shear walls are modeled utilizing different techniques either using shell elements or combination of frame elements. In the nonlinear analyses, the nonlinear material model of mid-pier frame is generally based on plastic hinge concept located on the plastic zones at the end of the structural elements or distributed along the member span length. The nonlinear behavior of the shell elements is generally modeled using multi layer shell element with layered material model. In this approach, the concrete and the reinforcement inside the structural elements are modeled respectively with different layers. In this study, different approaches for linear and nonlinear modeling of the shear walls in structural analyses of buildings are studied and applied to RC building with shear walls. The analyses results of different approaches are compared in terms of overall behavior of the structural systems.
Clouds of virtual machines in edge networks

This article addresses the potential impact of emerging technologies and solutions, such as software defined networking and network function virtualization, on carriers' network evolution. It is argued that standard hardware advances and these emerging paradigms can bring the most impactful disruption at the network's edge, enabling the deployment of clouds of nodes using standard hardware: it will be possible to virtualize network and service functions, which are provided today by expensive middleboxes, and move them to the edge, as close as possible to users. Specifically, this article identifies some of key technical challenges behind this vision, such as dynamic allocation, migration, and orchestration of ensembles of virtual machines across wide areas of interconnected edge networks. This evolution of the network will profoundly affect the value chain: it will create new roles and business opportunities, reshaping the entire ICT world.
BONE FRACTURE ANALYSIS USING THE EXTENDED FINITE ELEMENT METHOD ( XFEM ) WITH ABAQUS

The bones of elderly people with osteoporosis are susceptible to either traumatic fracture as a result of external impact, such as what happens during a fall, or even spontaneous fracture without trauma as a result of muscle contraction [1, 2]. Understanding the fracture behavior of bone tissue will help researchers find proper treatments to strengthen the bone in order to prevent such fractures, and design better implants to reduce the chance of secondary fracture after receiving the implant.
Perfectionism and workaholism in employees : The role of work motivation

Even though it has been over 20 years since Spence and Robbins (1992) first showed perfectionism and workaholism to be closely related, the relationship between perfectionism and workaholism is still under-researched. In particular, it has remained unclear why perfectionism is linked to workaholism. Using data from 131 employees, this study—examining self-oriented and socially prescribed perfectionism—investigated whether intrinsic–extrinsic work motivation could explain the positive relationship between perfectionism and workaholism. Whereas socially prescribed perfectionism was unrelated to workaholism, self-oriented perfectionism showed a positive correlation with workaholism. Furthermore autonomous (integrated and identified regulation) and controlled (introjected and external regulation) work motivation showed positive correlations. However, when all predictors were entered in a regression analysis, only self-oriented perfectionism, identified regulation, and introjected regulation positively predicted workaholism. In addition, a mediation analysis showed that identified and introjected regulation fully mediated the effect of self-oriented perfectionism on workaholism. The findings suggest that high levels of work motivation explain why many self-oriented perfectionists are workaholic.
Fog computing security: a review of current applications and security solutions

Fog computing is a new paradigm that extends the Cloud platform model by providing computing resources on the edges of a network. It can be described as a cloud-like platform having similar data, computation, storage and application services, but is fundamentally different in that it is decentralized. In addition, Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. These features make the Fog platform highly suitable for time and location-sensitive applications. For example, Internet of Things (IoT) devices are required to quickly process a large amount of data. This wide range of functionality driven applications intensifies many security issues regarding data, virtualization, segregation, network, malware and monitoring. This paper surveys existing literature on Fog computing applications to identify common security gaps. Similar technologies like Edge computing, Cloudlets and Micro-data centres have also been included to provide a holistic review process. The majority of Fog applications are motivated by the desire for functionality and end-user requirements, while the security aspects are often ignored or considered as an afterthought. This paper also determines the impact of those security issues and possible solutions, providing future security-relevant directions to those responsible for designing, developing, and maintaining Fog systems.
Types of study in medical research: part 3 of a series on evaluation of scientific publications.

The choice of study type is an important aspect of the design of medical studies. The study design and consequent study type are major determinants of a study's scientific quality and clinical value.



This article describes the structured classification of studies into two types, primary and secondary, as well as a further subclassification of studies of primary type. This is done on the basis of a selective literature search concerning study types in medical research, in addition to the authors' own experience.



Three main areas of medical research can be distinguished by study type: basic (experimental), clinical, and epidemiological research. Furthermore, clinical and epidemiological studies can be further subclassified as either interventional or noninterventional.



The study type that can best answer the particular research question at hand must be determined not only on a purely scientific basis, but also in view of the available financial resources, staffing, and practical feasibility (organization, medical prerequisites, number of patients, etc.).
Segmenting and Tagging Text with Neural Networks

Shao, Y. 2018. Segmenting and Tagging Text with Neural Networks. Studia Linguistica Upsaliensia 21. 76  Acta Universitatis Upsaliensis. ISBN 978-91-513-0340-6. Segmentation and tagging of text are important preprocessing steps for higher-level natural language processing tasks. In this thesis, we apply a sequence labelling framework based on neural networks to various segmentation and tagging tasks, including sentence segmentation, word segmentation, morpheme segmentation, joint word segmentation and part-of-speech tagging, and named entity transliteration. We apply a general neural CRF model to different tasks by designing specific tag sets. In addition, we explore effective ways of representing input characters, such as utilising concatenated n-grams and sub-character features, and use ensemble decoding to mitigate the effects of random parameter initialisation. The segmentation and tagging models are evaluated in a truly multilingual setup with more than 70 datasets. The experimental results indicate that the proposed neural CRF model is effective for segmentation and tagging in general as state-of-the-art accuracies are achieved on datasets in different languages, genres, and annotation schemes for various tasks. For word segmentation, we propose several typological factors to statistically characterise the difficulties posed by different languages and writing systems. Based on this analysis, we apply language-specific settings to the segmentation system for higher accuracy. Our system achieves substantially better results on languages that are more difficult to segment when compared to previous work. Moreover, we investigate conventionally adopted evaluation metrics for segmentation tasks. We propose that precision should be excluded and using recall alone is more adequate for sentence segmentation and word segmentation. The segmentation and tagging tools implemented along with this thesis are publicly available as experimental frameworks for future development as well as preprocessing tools for higher-level NLP tasks.
A contextual change account of the directed forgetting effect.

The authors propose that the costs and benefits of directed forgetting in the list method result from an internal context change that occurs between the presentations of 2 lists in response to a "forget" instruction. In Experiment 1 of this study, costs and benefits akin to those found in directed forgetting were obtained in the absence of a forget instruction by a direct manipulation of cognitive context change. Experiment 2 of this study replicated those findings using a different cognitive context manipulation and investigated the effects of context reinstatement at the time of recall. Context reinstatement reduced the memorial costs and benefits of context change in the condition where context had been manipulated and in the standard forget condition. The results are consistent with a context change account of directed forgetting.
PCB multi-track coils for domestic induction heating applications

In this paper, an analysis of the resistance of multi-track coils in printed circuit board (PCB) implementations, where the conductors have rectangular cross-section, for spiral planar coils is carried out. For this purpose, different analytical losses models for the mentioned conductors have been reviewed. From this review, we conclude that for the range of frequencies, the coil dimensions and the planar configuration typically used in domestic induction heating, the application in which we focus, these analysis are unsatisfactory. Therefore, in this work the resistance of multi-track winding has been calculated by means of finite element analysis (FEA) tool. These simulations provide us some design guidelines that allow us to optimize the design of multi-track coils for domestic induction heating. Furthermore, several prototypes are used to verify the simulated results, both single-turn coils and multi-turn coils.
Matching Network Elimination in Broadband Rectennas for High-Efficiency Wireless Power Transfer and Energy Harvesting

Impedance matching networks for nonlinear devices such as amplifiers and rectifiers are normally very challenging to design, particularly for broadband and multiband devices. A novel design concept for a broadband high-efficiency rectenna without using matching networks is presented in this paper for the first time. An off-center-fed dipole antenna with relatively high input impedance over a wide frequency band is proposed. The antenna impedance can be tuned to the desired value and directly provides a complex conjugate match to the impedance of a rectifier. The received RF power by the antenna can be delivered to the rectifier efficiently without using impedance matching networks; thus, the proposed rectenna is of a simple structure, low cost, and compact size. In addition, the rectenna can work well under different operating conditions and using different types of rectifying diodes. A rectenna has been designed and made based on this concept. The measured results show that the rectenna is of high power conversion efficiency (more than 60%) in two wide bands, which are 0.9–1.1 and 1.8–2.5 GHz, for mobile, Wi-Fi, and ISM bands. Moreover, by using different diodes, the rectenna can maintain its wide bandwidth and high efficiency over a wide range of input power levels (from 0 to 23 dBm) and load values (from 200 to 2000 Ω). It is, therefore, suitable for high-efficiency wireless power transfer or energy harvesting applications. The proposed rectenna is general and simple in structure without the need for a matching network hence is of great significance for many applications.