nils-herrmann/clean_scirepeval huggingface dataset:
Reorganized DCT based image representation for reduced reference stereoscopic image quality assessment
Venue: Neurocomputing

In this paper, a novel reduced reference (RR) stereoscopic image quality assessment (SIQA) is proposed by characterizing the statistical properties of the stereoscopic image in the reorganized discrete cosine transform (RDCT) domain. Firstly, the difference image between the left and right view images is computed. Afterwards, the left and right view images, as well as the difference image, are decomposed by block based discrete cosine transform (DCT) The DCT coefficients are further reorganized into a three level coefficient tree, resulting in ten RDCT subbands. For each RDCT subband, the statistical property of the coefficient distribution is modeled by the generalized Gaussian density (GGD) function. And the mutual information (MI) and energy distribution ratio (EDR) are employed to depict the statistical properties across different RDCT subbands. Moreover, EDR can further model the mutual masking property of the human visual system (HVS) By considering the GGD modeling behavior within each RDCT subband and MI together EDR characterizing behavior across RDCT subbands, the statistical properties of the stereoscopic image are fully exploited, including the left view, right view, and the difference image. Experimental results demonstrated that the statistical properties of the difference image can well represent the perceptual quality of the stereoscopic image, which outperforms the representative RR quality metrics for stereoscopic image and even some full reference (FR) quality metrics. By considering the left view, right view, and difference image together, the performances of the proposed RR SIQA can be further improved, which presenting a more closely relationship between the quality metric output and human visual perception.
GERMANICUS ON TOUR: HISTORY, DIPLOMACY AND THE PROMOTION OF A DYNASTY
Venue: The Classical Quarterly

Towards the end of Book 2 of Tacitus' Annals, Germanicus, great nephew of Augustus, grandson of Mark Antony, and nephew, adopted son and heir of the emperor Tiberius, falls ill and dies at Antioch (2.69 72) His travels in the eastern Mediterranean in a.d. 18 thus reach a sad conclusion. They had begun when, after being recalled from the wars of conquest in Germany described in detail in the opening books of the Annals (1.50 1, 1.55 71; 2.5.2 26) he was sent from Rome by Tiberius to preside over the installation of a new king of Armenia (2.43.1; cf. 2.3 5.1)
Word Sense Disambiguation Approaches for Indian Languages A Survey

In natural languages, there are many words that have different meaning in different context. Word sense disambiguation is a method for identification of correct word sense in a specific context. Indian languages are morphologically rich in nature and hence show more inflections as compare to foreign languages. Therefore it is difficult to develop word sense disambiguation system for Indian languages. In this paper various efforts done by various researchers to develop word sense disambiguation systems for Indian languages have been discussed.
Survey on Word Sense Disambiguation: An Initiative towards an Indo Aryan Language

Resolution of lexical ambiguity, commonly known as Word Sense Disambiguation (WSD) task is to distinguish the correct sense among the set of senses for an ambiguous term depending on the particular context automatically. It plays the vital role as it acts as an intermediate phase to many Natural Language Processing (NLP) applications like Machine Translation, Information Retrieval, Speech Processing, Hypertext navigation, Parts of Speech tagging. Existing literature reveals that there are various approaches for lexical ambiguity resolution Knowledge based, Corpus based. In recent years, many WSD systems is being developed in Indian languages like Hindi, Malayalam, Manipuri, Nepali, Kannada but no such automated system has yet emerged for the Indo Aryan language Assamese. Our future work aims to develop a model for the WSD problem which is fast, optimal and efficient in terms of accuracy and scalability. This paper presents a survey report made in this research topic discussing the WSD problem, various approaches along with their algorithms. Moreover it also list out the various NLP applications which would be efficient when disambiguation system is merged. Evaluation measures used to determine the WSD performance are also discussed here.
Word Sense Disambiguation Techniques for Indian and other Asian Languages: A Survey

Natural Languages used by people for establishing proper communication consist of many words having multiple meanings known as polysemous but implies a single sense depending on the context. Word sense disambiguation is a method of determining the appropriate sense of a polysemous word in the context. WSD is almost finished for English. It is a challenging task for Indian languages since these are morphologically rich in nature and development of various resources like machine readable dictionaries, WordNet etc. are in progress. We have discussed the unsupervised Graph based WSD for English. Then, we have discussed the various efforts accomplished by several researchers to develop WSD systems for Indian languages like Hindi, Kannada, Malayalam, and Assamese. Finally, we have discussed about WSD for other Asian languages like Nepali, Arabic and Myanmar.
Survey of the word sense disambiguation and challenges for the Slovak language
Venue: 2016 IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI)

The main goal of this paper is to explain important terms of the word sense disambiguation (WSD) in the Slovak language. A comprehensive survey of current approaches and evaluation methodologies is provided. Special attention is given to necessary language resources and tools. The paper deals with problems specific to Slovak language: missing language resources, rich morphology, free word order and their solutions. Research directions of Slovak WSD system utilizing available language resources and unsupervised approaches are explained in the conclusion.
A JOURNEY FROM BIG DATA TOWARDS PRESCRIPTIVE ANALYTICS

This survey paper addresses the concept of big data and various types of analytics that can be undergone by the researchers using big data. Since the data size is big and mixture of different data type, the time to store, retrieve and process the big data is a challenging issue, so an outline to improve the performance of big data processing is also given in this paper. Finally, to make use of big data analytics in a positive and beneficial manner, this paper explores the importance of predictive and prescriptive analytics for any type of applications which is very useful for the people to come to a conclusion at various stage, when they are in need to take best decision.
On the role of context in business process management

We emphasize the importance of going beyond a one size fits all approach to BPM.We suggest a comprehensive consideration of contextual factors in BPM.We propose a framework to identify BPM contexts along four dimensions. Business Process Management (BPM) has proven successful to help organizations improve and innovate, and its application has grown in scope and context. One essential problem related to this development is that the BPM body of knowledge does not account for a broader variety of business contexts. On the contrary, most approaches, methods, or models in BPM suggest one way forward, and we recognize that BPM projects following a one size fits all approach are prone to fail, since they do not sufficiently consider situational requirements. In this viewpoint article, we argue that BPM needs to be contextual in order for projects to be most efficient and effective. We observe a lack of research on how to identify and characterize business contexts relevant for tailoring the right BPM approach. Therefore, we examine contextual factors that influence BPM and propose a framework to identify the context in which BPM is applied. We define context in BPM as situational factors related to goal process organization and environment dimensions. Our viewpoint article not only creates awareness for contextual BPM, it also intends to stimulate research on the role of context in BPM and to help practitioners better understand the specific business context in which BPM initiatives are applied.
Determinants of the intention to use NFC technology as a payment system: an acceptance model approach
Venue: Inf. Syst. E Bus. Manag.

The worldwide growth of mobile technology has enabled many companies to take advantage of its application as complementary sales tools. The main objective of this research is user acceptance analysis of near field communication mobile payment systems. Classic variables from the technology acceptance model, as well as variables from other recent studies, were used as models for this research (compatibility, security, personal innovation and individual mobility) To meet these objectives a questionnaire, filled out by 191 respondents, formed the basis of a structural equation modeling designed by PLS 3.0 software. The results show that attitude, subjective norms and innovation and are determinants of the future intention to use this technology. Finally, the main implications for corporate management and business development strategies which reinforce this type of business in light of new technical developments are discussed.
A Survey on Pattern Discovery of Web Usage Mining

In the recent years with the development of Internet technology the growth of World Wide Web exceeded all expectations. A lot of information is available in different formats and retrieving content has become a very difficult task. One possible approach to solving problem is Web Usage Mining (WUM) Web mining is the application of data mining on web data and web usage mining is an important component of web mining. The goal of web usage mining is to understand the behavior of website users through the process of data mining of web data and Web usage mining is to understand the behavior of website users through the process of data mining of web Access data. knowledge obtained from web usage mining can be used to enhance web design, introduce personalization service and facilitate more effective browsing the important an application of web mining extracting the hidden knowledge in the log files of a web server recognizing various interests of web users, discovering customer behaviour while at the site are normally referred as the application of web usage mining. In this paper, we provide an updated focused survey on different pattern discovery techniques of web usage mining.
Clickstream Prediction Using Sequential Stream Mining Techniques with Markov Chains
Venue: IDEAS

As one of data mining tasks, sequential pattern mining provides valuable information about frequent patterns of users over time. For instance, frequent sequential patterns can be applicable to analyze user clickstreams for determination of web navigation patterns, genome sequences, and customer purchasing patterns. In many real life situations, data to be mined are continuously changing. Moreover, these data are streaming at a high velocity, which leads to impracticality of storing all these data in memory. Hence, to handle these situations, we propose three stream mining algorithms to first find frequent sequential patterns. The algorithms then form statistical models, which are stored as Markov chains or transition matrices capturing frequent sequential patterns mined so far, to predict future user clickstream (e.g. the web page the user will visit next) Experimental results show the efficiency and prediction accuracy of our proposed Markov chain based sequential stream mining algorithms in clickstream prediction.
Virtual reality social training for adolescents with high functioning autism
Venue: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Virtual reality training has potential to be an effective mode of therapy for players with autism spectrum disorders, but existing systems are not suited to the complex interactions required for this application; evaluation and treatment of autism is still a challenging task for human experts. In this paper we present an adaptive training system that learns to map player performance deficits to the most effective instructional response. This system uses a neural network to monitor player performance and a learning fuzzy inference system to map performance deficits to instructional techniques. The functionalities of the system are then evaluated.
Cross domain Text Classification with Multiple Domains and Disparate Label Sets
Venue: ACL

Advances in transfer learning have let go the limitations of traditional supervised machine learning algorithms for being dependent on annotated training data for training new models for every new domain. However, several applications encounter scenarios where models need to transfer/adapt across domains when the label sets vary both in terms of count of labels as well as their connotations. This paper presents first of its kind transfer learning algorithm for cross domain classification with multiple source domains and disparate label sets. It starts with identifying transferable knowledge from across multiple domains that can be useful for learning the target domain task. This knowledge in the form of selective labeled instances from different domains is congregated to form an auxiliary training set which is used for learning the target domain task. Experimental results validate the efficacy of the proposed algorithm against strong baselines on a real world social media and the 20 Newsgroups datasets.
Fifty Years of Consumer Issues in The Journal of Consumer Affairs

This article is the Guest Editor's introduction to the virtual issue to celebrate the 50th anniversary of Journal of Consumer Affairs (JCA) published on the journal website in the summer of 2016. The virtual issue highlights the research published during JCA's first 50 years and includes 20 articles that reported on consumer issues which are still relevant today. The evolution of research topics over the 50 years shows that consumer issues have evolved from handling and resolving complaints to information search, decision making, consumer fraud, debt profiles, a hierarchy of saving needs, welfare reform, diffusion of innovations, identity theft, financial literacy, and health care reform. The 2010 creation of the Consumer Financial Protection Bureau can be seen as a capstone for the consumer movement. What will the next 50 years bring? We can assume that JCA will continue to be a leader in providing research on consumers and their issues.
Two Discourse Driven Language Models for Semantics
Venue: ACL

Natural language understanding often requires deep semantic knowledge. Expanding on previous proposals, we suggest that some important aspects of semantic knowledge can be modeled as a language model if done at an appropriate level of abstraction. We develop two distinct models that capture semantic frame chains and discourse information while abstracting over the specific mentions of predicates and entities. For each model, we investigate four implementations: a "standard" N gram language model and three discriminatively trained "neural" language models that generate embeddings for semantic frames. The quality of the semantic language models (SemLM) is evaluated both intrinsically, using perplexity and a narrative cloze test and extrinsically we show that our SemLM helps improve performance on semantic natural language processing tasks such as co reference resolution and discourse parsing.
Energetic dinitromethyl group functionalized azofurazan and its azofurazanates

Incorporating explosophore groups such as nitro, dinitromethyl, and azo into furazan results in potential candidates for energetic materials applications. In this study, 3,3' azofurazan was functionalized with fluorodinitromethyl (2) and dinitromethyl (3) moieties by fluorination and acidification of potassium 4,4' bis(dinitromethyl) 3,3' azofurazanate (1) respectively. In addition, 3 was converted to its ammonium (4) hydrazinium (5) and hydroxylammonium (7) salts. All the compounds were fully characterized by multinuclear NMR and IR spectra, and elemental analysis. Compounds 2 and 3 are further supported by X ray crystallographic analysis. Electronic structures were also studied. In addition, physicochemical properties, such as thermal stability, density, and sensitivity were measured, and energetic properties (e.g. detonation velocities and detonation pressures) were calculated using EXPLO5 code.
Explicit Definitions and Implicit Assumptions about Post Socialist Cities in Academic Writings

In the past five years, several critical commentaries have been published about the state of the art in research and theory on post socialist cities. Besides overviewing and generalizing the findings of previous studies, authors have identified several weak points in this field. This paper attempts to echo this body of work through reflecting on one simple, yet crucial question that has emerged in some of the contributions. This question is what the post socialist city actually stands for in urban research. The paper discusses the variety of meanings that this concept has acquired in academic literature and in scholars' attempts to explain the characteristic development of cities in former socialist countries since the 1990s.
Shrinking Cities in Post Socialist Europe: What Can We Learn From Their Analysis for Theory Building Today?

In the final decades of the twentieth century, the post industrial regions of western Europe and the US were hot spots of urban shrinkage, and this also affected large areas in post socialist countries. Despite ongoing calls for a better integration of diverse global urban experiences into theorization, post socialist cities and their trajectories, as well as their experiences with rapid urban change, have been largely disregarded in general theory development. At the same time, we face a somewhat inconsistent situation in the theoretical discourse on urban development. There are requests for "new geographies of theory" or to regard all cities as "ordinary" in order to include different types of narratives and experience into overall comparisons and/or theory building. Set against this background, this paper aims to deal with the case of shrinking post socialist cities, that is, cities that are "excluded" from hegemonic discourses for two reasons: they are post socialist and they are shrinking. In contrast to this situation, we understand shrinking post socialist cities as valuable examples for strengthening the debate on current and future forms of, and determining factors for, general urbanization. At the focus of our paper, therefore, are the questions about what we can learn from the analysis of shrinking post socialist cities for the general discourse, as well as for theory building for cities, and how we can overcome the observed reluctance to integrate the post socialist experience into general theory development. The paper draws on an EU 7 FP research project finished in 2012 that comparatively analysed urban shrinkage across several regions of Europe, with a particular focus on post socialist countries.
Institutional transition: Internal migration, the propiska, and post socialist urban change in Bishkek, Kyrgyzstan

Since the collapse of the Soviet Union in the early 1990s, there has been remarkable enthusiasm for theorising how transitional processes have unfolded in post socialist cities. In seeking to extend literature that uses the post socialist condition as a tool for theory building, we draw attention to the ongoing processes of institutional change in post socialist cities. In doing so, we reject a 'top down' perspective and examine how these institutional transitions are shaped through processes of 'domestication' negotiation and contestation between different interest groups in the city. We develop our argument, by drawing attention to the local political debates surrounding the propiska in Bishkek, Kyrgyzstan. The propiska developed throughout the Soviet Union to control internal migration and is still used today in a less restrictive form. By discussing our case study, we hope to foster attention towards the ongoing contested processes of institutional transition in post socialist cities.
Popular responses to city text changes: street naming and the politics of practicality in a post socialist martyr city

The cultural politics of attributing names and the popular responses to the naming process of the urban landscape are core issues in 'critical toponymies' In many Romanian cities there are place names that articulate a collective memory agenda with respect to the 1989 Revolution, and Timisoara stands at the forefront of streets bearing martyr names. However, there have been recent calls for more attention to the popular responses to place naming practices. This paper explores these calls by addressing the issue of users of urban street place names. It also highlights the need to introduce the theory of 'the politics of practicality' in place and street name studies. We seek to explain if Timisoarians are (un)happy with the new 'martyr city text' and how social justice and the contextualisation of the conflict as a case of the practical and the ideological are interrelated. By analysing the concerns of local service workers and by surveying local people's opinion on the use of the martyrs' names, we look to determine to what extent they accept or reject the new names and their use. In particular, pride and recognition versus everyday difficulties in martyr name uses produce major tensions at a local level. Therefore social justice (restitution) issues created local conflict over the uses of new names, and the politics of practicality in the martyrs' case shaped how political and symbolic changes are received by the people. This paper is developing and challenging previous work on place and street naming in geography by considering, beyond the understanding that conflicts over naming are symbolic or ideological, that ordinary citizens use, connect with, and depend upon street names in practical terms: they internalise and react differently to the costs of rewriting the city text.
FE forming analysis with nonlinear friction coefficient model considering contact pressure, sliding velocity and sliding length

A nonlinear friction coefficient model which considers contact pressure, sliding velocity and sliding length was developed to improve the accuracy of predictions of the formability of steel sheets. The effects of contact pressure and sliding velocity under mixed lubrication were estimated based on a friction test in which a long steel sheet was drawn between two dies. The effect of the sliding length under the condition of lack of lubricants was estimated in another friction test, in which a long tool bar was placed between steel sheets and drawn continuously at the same position on the sheets. The results of cup drawing experiments and a finite element (FE) forming analysis using the developed friction model demonstrated that the model improves the accuracy of predictions of the formability of steel sheets. Finally, the effect of press motion control with a servo press on formability improvement was estimated by using the nonlinear model.