Reviewerly/exHarmony huggingface dataset:
Study on clues for gold prospecting in the Maizijing-Shulonggou area, Ningxia Hui autonomous region, China, using ALI, ASTER and WorldView-2 imagery

Several gold occurrences have been discovered in the Maizijing-Shulonggou area, Ningxia Hui autonomous region, China. The clues for gold prospecting in this area may relate to fractures and hydrothermal alterations, but it is very difficult to conduct a field investigation on the clues because of the alpine valleys. To explore the clues for gold prospecting, this study extracted geological information related to fracture zones and hydrothermal alterations using ALI, ASTER, and WorldView-2 data, and subsequently, explored potential relationships between extracted geological characteristics and gold mineralization. The WorldView-2 image in the study area was used for fracture interpretation. The azimuth and density of linear fractures were investigated, and the results showed that linear fractures with NE direction were most common, the gold occurrences except Au2 were all located in NE fracture zones, and all gold occurrences located in high fracture density areas (level 1–3 areas) where NE and NW fractures were the most common observations. This suggests that the high fracture density and NE and NW fractures are important indicators of potential gold mineralization. Hydrothermal alteration minerals in exposed bedrocks were mapped using ALI and ASTER imagery. Based on the spectral analysis, ASTER image in the study area were used to map quartz, illite and chlorite, while ALI image were used to map limonite. The spatial distribution of alteration minerals revealed regional specific alteration mineral in gold mineralization. In the northern Maizijing region, the composition of alteration mineral in the surrounding of Au1 was overwhelmed by quartz, while the alteration minerals in the surrounding of Au2-4 were dominated by limonite in the southern Shulonggou region, which showed different indicator minerals for gold prospecting in the two regions. As a result, the key areas for prospecting are the NE and NW fracture zones with quartz veins in the Maizijing region and the NE and NW fracture zones with limonitization in the Shulonggou region. In the Shulonggou region, pyrite in buried quartz-pyritization belt and illitization-pyritization belt is likely to be the precursor of limonite. Heavy mineral assemblages were analyzed for native gold content, and the results suggested high native gold content in the illitization-pyritization belt, followed by quartz-pyritization belt, which was consistent with the strong association of limonite and gold mineralization, thus the two belts shall be prioritized for gold prospecting in the Shulonggou region.
System for Face Recognition under Different Facial Expressions Using a New Associative Hybrid Model Amαβ-KNN for People with Visual Impairment or Prosopagnosia

Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system that integrates Artificial Intelligence which learns the face of the people with whom the user interacts daily. During the study we propose a new hybrid model of Alpha-Beta Associative memories (Amαβ) with Correlation Matrix (CM) and K-Nearest Neighbors (KNN), where the Amαβ-CMKNN was trained with characteristic biometric vectors generated from images of faces from people who present different facial expressions such as happiness, surprise, anger and sadness. To test the performance of the hybrid model, two experiments that differ in the selection of parameters that characterize the face are conducted. The performance of the proposed model was tested in the databases CK+, CAS-PEAL-R1 and Face-MECS (own), which test the Amαβ-CMKNN with faces of subjects of both sexes, different races, facial expressions, poses and environmental conditions. The hybrid model was able to remember 100% of all the faces learned during their training, while in the test in which faces are presented that have variations with respect to those learned the results range from 95.05% in controlled environments and 86.48% in real environments using the proposed integrated system.
A comparison of object-triple mapping libraries

Domain-independent information systems like ontology editors provide only limited usability for non-experts when domain-specific linked data need to be created. On the contrary, domain-specific applications require adequate architecture for data authoring and validation, typically using the object- oriented paradigm. So far, several software libraries mapping the RDF model (representing linked data) to the object model have been introduced in the literature. In this paper, we develop a novel framework for comparison of object-triple mapping solutions in terms of features and performance. For feature comparison, we designed a set of qualitative criteria reflecting object-oriented application developer’s needs. For the performance comparison, we introduce a benchmark based on a real-world information system that we implemented using one of the compared object-triple mapping (OTM) solutions – JOPA. We present a detailed evaluation of a selected set of OTM libraries, showing how they differ in terms of features. We further narrow down the set of selected OTM libraries to contain only RDF4J-compatible ones and use the benchmark to measure their time and memory efficiency.
Development and evaluation of knowledge treasure for emergency situation awareness

In this work, we have developed a knowledge treasure for situation awareness. Background knowledge and information for emergency situations are required to support the decision makers. Our main motive is to provide real-time decision support to make recovery from incidents with the help of available resources. A knowledge treasure consists of a knowledge base of concepts (i.e. a domain ontology), database of instances and required procedures and rules for different use cases. Web ontology language (OWL) is used to construct the ontology in protégé 5.2 editor. In this paper, we followed the proper methodology to develop and evaluate the ontology for emergency situation management. A review of several approaches has been done to evaluate the ontology. Two major evaluation approaches have been applied on the ontology to evaluate it quantitatively and qualitatively and compared the results with other existing ontology.
Principles of Managing the Process of Innovative Ideas Genesis

Innovative development has universally valid social value and it is very important today. Its corresponding theoretical base is developing, but there is no clear understanding how innovations are generated and what their genesis is. The description of the life cycle of the creation, development and implementation of innovation usually begins with the words: “Innovation is given”, but who gives it, where and how the innovative idea is born, is not currently the subject of researches and discussion. Therefore, it seems important, first of all, to understand where and how innovations are born, in order to design appropriate information technology for representing the meaning of problem situation in the processes of collective decision-making, and then find ways of managing this process. This article shows that the source of the innovation idea is the problem situation in which the actors turned out to be. It is proposed to use the theory of intersubjective management to solve problem situations and find ways out of them. The development of technological platform for implementing the provisions of the intersubjective management theory is based on the formal ontologies construction. Ontological engineering makes it possible to build a communicative semantic model that integrates all views of actors on the problem situation, which is necessary for the creating of their collective model of the innovation idea at the stage of the innovation origin, preceding its implementation.
Interaction design of community-driven environmental projects (CDEPs): A case study from the Anacostia Watershed

Water is becoming an increasingly precious resource across the world, but citizens can help ensure good-quality water by helping to manage their local watersheds. Local, place-based advocacy projects that are strongly grounded within their geographical area have the potential to inspire environmental change as citizens come together to collectively address environmental challenges in their own neighborhoods. However, less attention has been given to these small, intensely place-based local projects. Our research focuses on the interaction design of technology to support small, local, place-based "community-driven environmental projects" (CDEPs) for water management in the Anacostia River Watershed. Analysis of case study data collected over a 3-y period to identify the needs of CDEP members provides the basis for the interaction design of technology known as NatureNet to support CDEPs. From this research, six design insights for supporting CDEPs are suggested: (i) a shared common endeavor connected to the identity of the members, (ii) ways for newcomers and experienced participants to share a common space and function together effectively, (iii) support for different sources of knowledge, (iv) different modes of participation and ways for participants to express themselves, (v) different ways to express status through diverse opportunities, and (vi) support for porous and changing leadership roles. Taken together, the findings from our study suggest a preference for technology-lite, highly flexible software that supports the diverse needs of CDEP members.
Research on denoising processing of computer video electromagnetic leakage reduction image based on fuzzy degree

On the basis of analyzing, receiving, and parsing the computer video electromagnetic leakage emission signal, an image of the screen display content can be obtained. Due to the interference noise existing in the receiving process, the received image information may be drifted, the recognition may be poor, and the definition might be low. In order to improve the recognizability of the restored image, firstly, based on image noise analysis, cumulative averaging and noise smoothing, this paper proposes an image processing method based on ambiguity for electromagnetic leakage emission reduction image. Secondly, according to image denoising implementation steps, combined with computer video reproduction example, the image processing method was verified by comprehensive experiments. Lastly, the image evaluation and signal-to-noise ratio analysis of the experimental results were carried out. The results show that the image processing method based on the ambiguity of electromagnetic leakage emission reduction image has some improvement in subjective and objective evaluation with obvious promotion.
Urban hacking: the versatile forms of cultural resilience in Hong Kong

The current understanding of urban resilience focuses on economic, environmental, and social responses. While the significance of art in enhancing social resistance has been acknowledged, the full potential of (un)authorised artistic and creative practices in initiating and strengthening the strategies of urban resilience is not yet recognised. Based on extensive fieldwork in 2012–2017, this paper delineates how urban hacking challenges the sociopolitical and spatio-aesthetic dynamics of the urban public space in Hong Kong as a form of cultural resilience that can contribute to a more holistic understanding of urban resilience. The diversity of urban hacking is indicated in an analysis of selected case studies of urban knitting and digital hacking that question the prevailing perceptions emphasising hacking as a method of illegal and arbitrary destruction. I posit that varied forms of urban hacking have a growing power to raise awareness of sociopolitical issues, enhance solidarity, and renegotiate space for new strategies and subjectivities aiming for more versatile co-authorship of the city.
Influence of Visual Salience on Webpage Product Searches

Visual salience can increase search efficiency in complex displays but does that influence persist when completing a specific search? In two experiments, participants were asked to search webpages for the prices of specific products. Those products were located near an area of high visual salience or low visual salience. In Experiment 1, participants were read the name of the product before searching; in Experiment 2, participants were shown an image of the exact product before searching. In both cases, participants completed their search more quickly in the high-salience condition. This was true even when there was no ambiguity about the visual characteristics of the product. Our findings suggest that salience guides users through complex displays under realistic, goal-driven task conditions. Designers can use this knowledge to create interfaces that are easier to search by aligning salience and task-critical elements.
Cross Domain Person Re-Identification With Large Scale Attribute Annotated Datasets

We propose a novel deep convolutional neural network framework called deep augmented attribute network (DAAN) to learn augmented attribute features for cross-domain person re-identification (person Re-ID) task.We observed that in some cases, different persons could have similar attributes (e.g., wearing similar clothes).It motivates us to distinguish such pedestrians by further learning complementary image features.We thus construct a deep neural network with three branches: 1) the attribute branch predicts the attributes of the input image; 2) the augmentation branch generates complementary features that are fused with the output of the attribute branch to form the augmented attribute features; and 3) the reconstruction branch to refine augmented attribute features on the target dataset.In order to learn precise and detailed attributes for pedestrian, we manually labeled two large datasets (CUHK03 and Market-1501) with 25 predefined mid-level semantic attributes.We evaluate the DAAN on a series of cross-domain person Re-ID tasks, where DAAN demonstrates superior performance (around 6%) to the prior state-of-the-art crossdomain algorithms.
On the use of character n-grams as the only intrinsic evidence of plagiarism

When a shift in writing style is noticed in a document, doubts arise about its originality. Based on this clue to plagiarism, the intrinsic approach to plagiarism detection identifies the stolen passages by analysing the writing style of the suspicious document without comparing it to textual resources that may serve as sources for the plagiarist. Character n-grams are recognised as a successful approach to modelling text for writing style analysis. Although prior studies have investigated the best practice of using character n-grams in authorship attribution and other problems, there is still a need for such investigations in the context of intrinsic plagiarism detection. Moreover, it has been assumed in previous works that the ways of using character n-grams in authorship attribution remain the same for intrinsic plagiarism detection. In this paper, we study the effect of character n-grams frequency and length on the performance of intrinsic plagiarism detection. Our experiments utilise two state-of-the-art methods and five large document collections of PAN labs written in English and Arabic. We demonstrate empirically that the low- and the high-frequency n-grams are not equally relevant for intrinsic plagiarism detection, but their performance depends on the way they are exploited.
Generic Adaptive Scheduling for Efficient Context Inconsistency Detection

Many applications use contexts to understand their environments and make adaptation. However, contexts are often inaccurate or even conflicting with each other (a.k.a. context inconsistency). To prevent applications from behaving abnormally or even failing, one promising approach is to deploy constraint checking to detect context inconsistencies. A variety of constraint checking techniques have been proposed, based on different incremental or parallel mechanisms for the efficiency. They are commonly deployed with the strategy that schedules constraint checking immediately upon context changes. This assures no missed inconsistency, but also limits the detection efficiency. One may break the limit by grouping context changes for checking together, but this can cause severe inconsistency missing problem (up to 79.2 percent). In this article, we propose a novel strategy GEAS to isolate latent interferences among context changes and schedule constraint checking with adaptive group sizes. This makes GEAS not only improve the detection efficiency, but also assure no missed inconsistency with theoretical guarantee. We experimentally evaluated GEAS with large-volume real-world context data. The results show that GEAS achieved significant efficiency gains for context inconsistency detection by 38.8-566.7 percent (or 1.4x-6.7x). When enhanced with an extended change-cancellation optimization, the gains were up to 2,755.9 percent (or 28.6x).
Diverse Decoding for Abstractive Document Summarization

Recently, neural sequence-to-sequence models have made impressive progress in abstractive document summarization. Unfortunately, as neural abstractive summarization research is in a primitive stage, the performance of these models is still far from ideal. In this paper, we propose a novel method called Neural Abstractive Summarization with Diverse Decoding (NASDD). This method augments the standard attentional sequence-to-sequence model in two aspects. First, we introduce a diversity-promoting beam search approach in the decoding process, which alleviates the serious diversity issue caused by standard beam search and hence increases the possibility of generating summary sequences that are more informative. Second, we creatively utilize the attention mechanism combined with the key information of the input document as an estimation of the salient information coverage, which aids in finding the optimal summary sequence. We carry out the experimental evaluation with state-of-the-art methods on the CNN/Daily Mail summarization dataset, and the results demonstrate the superiority of our proposed method.
The Learning Problems Behind the Seams in Seamless Learning

Learning increasingly takes places across different contexts in space (e.g., formal and informal settings) and time (e.g., lifelong learning). Seamless learning draws attention towards the potential, but also to the problems that may occur when learning across contexts. While major seams have been identified and many case studies conducted, the theoretical foundation of seamless learning does not seem as yet to have been sufficiently established. This chapter aims to consider the further conceptual development of seamless learning. Based on learning theories, we utilise the ten dimensions of mobile seamless learning in order to highlight the problems that can often lay behind the seams. The analyses build upon (re-)scoping seamless learning into seam-aware learning. Based on this, we have developed a set of learning strategies that aims to help learners to integrate their experiences made within different contexts. Then, we propose a small number of didactic design principles that foster the aforementioned learning strategies. As an outcome, this chapter aims to focus our understanding of the problem and to define the necessary learning competences. We also provide insight into these initial seam-aware design principles. Consequently, this chapter is addressed both to theorists as well as practitioners in the area of seamless learning.
Investigation and optimization of sampling characteristics of light field camera for flame temperature measurement

It is essential to investigate the light field camera parameters for the accurate flame temperature measurement because the sampling characteristics of the flame radiation can be varied with the light field camera parameters. In this study, novel indices of the light field camera were proposed to investigate the directional and spatial sampling characteristics of the flame radiation. Effects of light field camera parameters such as focal length and magnification of the main lens, focal length and magnification of the microlens were investigated. It has been observed that the sampling characteristics of the flame are varied with the different parameters of the light field camera. The optimized parameters of the light field camera were then proposed for the flame radiation sampling. The larger sampling angle (23 times larger) is achieved by the optimized parameters compared to the commercial light field camera parameters. A non-negative least square (NNLS) algorithm was used to reconstruct the flame temperature. The reconstruction accuracy was also evaluated by the optimized parameters. The results suggested that the optimized parameters can provide higher reconstruction accuracy for axisymmetric and non-symmetric flame conditions in comparison to the commercial light field camera.
Complaints about technology as a resource for identity-work

Abstract This article examines how people complain about technology. Using discourse analysis, we inspect sixteen hours of video-recorded focus-group interviews and focused one-on-one discussions where technology was topicalized. We investigate these conversations paying attention to (i) features of language and its situated delivery, including emphasis, word choice, metaphor, and categorizations; and (ii) how these accomplish social actions. We show how interactants use narratives of complaint-like activities about hypothetical categories of people and confessions of their own complainable participation to accomplish a ‘bemoaning’ speech act that manages competing affiliations, demands, and disagreements to construct reasonable moral identities in the situated interaction. By engaging in specific micro-level discursive practices in interaction, participants produce and reproduce what new technologies ‘mean’ to them and for contemporary society. This shows how important it is to examine opinions as situated actions rather than as simple facts about what people believe. (Complaints, accounts, stance, technology, discourse analysis, identity)*
The Bitcoin game: Ethno-resonance as method

The global financial crisis and the contemporaneous emergence of the digital currency Bitcoin invite us to think about money and how it often functions almost imperceptibly in society. In this article, we show that Bitcoin is a ‘new object of concern’ that also compels us to reimagine ethnography in a digital age. We present a method, which we term ethno-resonance, that is both a reaction to the conditions presented by the Bitcoin phenomenon and a way of maintaining critical distance from its cyberlibertarian politics. We explicate six aspects of the method, framed around answers to what, why, how, who, when and where questions. Applied to cryptocurrencies, the method leads us to depict Bitcoin as a game, and we analyse the game’s dynamics through mapping the interplay between four foundational myths that animate, complicate and sustain the game. More broadly, this contributes to our understanding of the nature of money and alternative currencies.