Reviewerly/exHarmony huggingface dataset:
Analysing of Hueckel Edge Detector Performance Using Satellite Image

In this research, an analysis for the standard Hueckel edge detection algorithm behaviour by using three dimensional representations for the edge goodness criterion is presents after applying it on a real high texture satellite image, where the edge goodness criterion is analysis statistically. The Hueckel edge detection algorithm showed a forward exponential relationship between the execution time with the used disk radius. Hueckel restrictions that mentioned in his papers are adopted in this research. A discussion for the resultant edge shape and malformation is presented, since this is the first practical study of applying Hueckel edge detection algorithm on a real high texture image containing ramp edges (satellite image).
Fragmentation in Distributed Database Design Based on Ant Colony Optimization Technique

Distributed database design solutions depend heavily on the exploitation of input data sources by using clustering techniques in data mining. A new approach of biomimetic computation systems such as ant colony optimization (ACO) for this solution is of interest to informatics experts. Using ACO techniques for this solution has the advantages such as faster algorithms thanks to the randomness of ant colony behavior. The use of random numbers based on heuristic information to pickup (drop) points will facilitate the flexible search on a large data space, so that it provides us with a better answer. In this article, the authors present ACO algorithms application solutions to clustering techniques for the problem of vertical fragmentation of distributed data.
Nan Jiang. 2018. <i>Second Language Processing: An Introduction</i>

Abstract This article reviews Second Language Processing: An Introduction EUR 46978-0-415-70804-3978-0-415-70803-6
Public Announcements for Epistemic Models and Hypertheories

Artemov has recently proposed a modernization of the semantics and proof theory of epistemic logic. We take up his approach and extend his framework with public announcements and the corresponding belief change operation. We establish a soundness and completeness result and show that our model update operation satisfies the AGM postulate of minimal change. Further, we also show that the standard approach cannot be directly employed to capture knowledge change by truthful announcements.
QANIZK for adversary-dependent languages and their applications

Quasi-Adaptive Non-Interactive Zero-Knowledge (QANIZK) proofs make possible efficient NIZK with short proofs by allowing the common reference string to depend on the language. The strongest notion of (computational) soundness for QANIZK is Unbounded Simulation-Soundness (USS). For USS, however, the language is completely beyond the adversary's control. In this paper, we introduce a stronger notion of USS for QANIZK, called USS for Adversary-Dependent Languages (USS-ADL), by allowing the adversary to adaptively develop the language. We present a generic construction of efficient USS-ADL-QANIZK for diverse vector spaces (DVS) over graded rings , of which linear subspaces over bilinear groups are specific instantiations. – Our generic construction provides the first USS-QANIZK for DVS over graded rings . This complements Abdalla et al.'s work (Eurocrypt'15) of QANIZK with one-time simulation-soundness. – As for applications, USS-ADL-QANIZK leads to modular constructions of digital signature and linearly homomorphic (structure-preserving) signature schemes with black-box security reductions . The instantiations cover the efficient USS-QANIZK for linear subspaces over bilinear groups proposed by Kiltz and Wee (Eurocrypt'15), a variant of the efficient structure-preserving signature proposed by Kiltz et al. (Crypto'15) and the efficient linearly homomorphic structure-preserving signature proposed by Kiltz and Wee (Eurocrypt'15). Our USS-ADL-QANIZK provides a new perspective on their constructions and security proofs in a unified way.
Multi-Electrode Electrical Profiling Results in the Northern Ladoga Area

DC electrical profiling with the use of Method of External Sliding Dipole (MESD) has been made along the profile Sevastyanovo-Hijtola-Sujstamo of 200 km length. The profile crosses the Ladoga anomaly of high conductivity. Interpretation of MESD results is performed in two stages. At the first stage, a one-dimensional inverse problem is solved using the Zohdy procedure (Zohdy 1989). The starting model is set in the form of a multilayered section with the number of layers equal to the number of deletions from the feeding line plus one (first) layer for the results of measurements inside the line. The depths to the base of the layers and their resistivity are taken equal to the corresponding values of the effective distances and to the apparent resistivity at corresponding distance. Further, an iterative selection of the theoretical model of the medium occurs before obtaining agreement with the experimental data within the error of observations. At the second stage, a quasi-2D section is constructed by symmetrically shifting the deep sounding centers with relation to the supply line AB to the southwest and northeast as the receiving dipoles MN move in opposite directions. The results of profiling, as well as the results of the study of samples from outcrops and boreholes, indicate the connection of anomalies with the presence of electron-conducting sulphide-carbonaceous rocks. Obviously, they explain the nature of the upper part of the regional Ladoga conductivity anomaly.
Emerging Social and Legal Issues of the Internet of Things

The advent of internet represents a revolution for the contemporary era, having brought about a striking series of changes in social, institutional, political, and economic life. This ongoing revolution has spread and absorbed within itself all the problems related to its own development. Objects become recognizable and acquire intelligence in that they are able to communicate data regarding themselves and also access other information aggregated by other devices. They are able to participate in a dialogue and interact among themselves within electronic communication networks without human intervention. All objects can acquire an active role thanks to connection with the web. The associated problems, which can no longer be ignored, draw attention above all to the lack of data control, which is to the vast extent of the data collected and more generally to the security of these data. This chapter has the aim of analyzing the ways in which European legislators, and consequently also Italian representatives, have intervened in order to stem the tide of emerging issues.
BoFGAN: Towards A New Structure of Backward-or-Forward Generative Adversarial Nets

Natural Language Generation (NLG), as an important part of Natural Language Processing (NLP), has begun to take full advantage of recent advances in language models. Based on recurrent neural networks (RNNs), NLG has made ground breaking improvement and is widely applied in many tasks. RNNs typically learn a joint probability of words, and the additional information is usually fed to RNNs hidden layer using implicit vector representations. Still, there exists some problem unsolved. Standard RNN is not applicable when we need to impose hard constraints on the language generation tasks: for example, standard RNNs cannot guarantee designated word(s) to appear in a target sentence to generate. In this paper, we propose a Backward-or-Forward Generative Adversarial Nets model (BoFGAN) to address this problem. Starting from a particular given word, a generative model at every time step generates a new preceding or subsequent word conditioned on the generated sequence so far until both sides reach an end. To train the generator, we first model it as a stochastic policy using Reinforcement Learning; then we employ a discriminator to evaluate the quality of a complete sequence as the end reward; and lastly, we apply Monte Carlo (MC) search to estimate the long-term return and update the generator via policy gradient. Experimental results demonstrate the effectiveness and rationality of our proposed BoFGAN model.
Domain Formalization for Metaphorical Reasoning

It is commonplace that cultural heritage is always discussed and analysed by using references to figures of speech. In particular, metaphors and allegories are very frequent in ancient and historical documents, painting and sculptures. It is also frequent to have some hints about the assets and their authors by comparing their contents with elements in the domain of the figures of speech to which the asset refer. In order to enable reasoning by figures of speech, we propose here a methodology able to link concepts in the domain of cultural assets with concepts in the domain of the figure of speech. We show here how reasoning in all these domains help in discovering some elements related to the cultural heritage that humans may neglect at first glance. Our approach can be useful in a variety of applications related to cultural heritage such as semantics annotations, linked data, crowd-sensing, etc.
The Resiliency of Multilevel Methods on Next-Generation Computing Platforms: Probabilistic Model and Its Analysis

The reduced reliability of next-generation exascale systems means that the resiliency properties of a numerical algorithm will become an important factor both in the choice of algorithm and in its analysis. The multigrid algorithm is the workhorse for the distributed solution of linear systems but little is known about its resiliency properties and convergence behavior in a fault-prone environment. In the current work, we propose a probabilistic model for the effect of faults involving random diagonal matrices. We summarize results of the theoretical analysis of the model for the rate of convergence of fault-prone multigrid methods which show that the standard multigrid method will not be resilient. Finally, we present a modification of the standard multigrid algorithm that will be resilient.
Marking Online Community Membership: The Pragmatics of Stance-taking

Data from academic seminars conducted through Skype textchat is analysed in this chapter, and the focus is on examples of how users mark community membership. Membership is marked explicitly by using pronominals and the metonymic use of the seminar group name. It is also marked implicitly by using reduced forms, which are stereotypical examples of a textchat speech style. I argue that these are markers of stance-taking, where community membership is recovered pragmatically as a weak implicature. Dis-alignment with the community is also seen, as individuals can also implicate their independence as setters of linguistic norms.
Frame-Based Optimal Design

Optimal experimental design (OED) addresses the problem of selecting an optimal subset of the training data for learning tasks. In this paper, we propose to efficiently compute OED by leveraging the geometry of data: We restrict computations to the set of instances lying on the border of the convex hull of all data points. This set is called the frame. We (i) provide the theoretical basis for our approach and (ii) show how to compute the frame in kernel-induced feature spaces. The latter allows us to sample optimal designs for non-linear hypothesis functions without knowing the explicit feature mapping. We present empirical results showing that the performance of frame-based OED is often on par or better than traditional OED approaches, but its solution can be computed up to twenty times faster.
Logic Without Language

Does a dog think? Does a prelingual child think? Creatures without language seem to be making some logical inferences which allow them to make decisions. We offer a utility and perception based account which allows us to deal with this phenomenon formally. We offer the suggestion that non-lingual creatures have a certain perception of the world and that they make the best decisions relative to that perception. Logic may be “used” to infer non-perceived facts from perceived facts.
A Closer Look at the Guo–Johansson–Stankovski Attack Against QC-MDPC Codes

In Asiacrypt 2016, Guo, Johansson, and Stankovski presented a reaction attack against QC-MDPC McEliece. In their attack, by observing the difference in failure rates for various sets $$\varPhi _d$$ of error vectors, the attacker obtains the distances between 1’s in the secret key and can thus recover the whole secret key. While the attack appears to be powerful, the paper only shows experiment results against the bit-flipping algorithm that uses precomputed thresholds, and the explanation of why the attack works does not seem to be convincing. In this paper, we give some empirical evidence to show that the Guo–Johansson–Stankovski attack, to some extent, works independently of the way that the thresholds in the bit-flipping algorithm are chosen. Also, by viewing the bit-flipping algorithm as a variant of “statistical decoding”, we point out why the explanation of the Guo–Johansson–Stankovski paper is not reasonable, identify some factors that can affect the failure rates, and show how the factors change for different $$\varPhi _d$$ .
Knowing When to Look for What and Where: Evaluating Generation of Spatial Descriptions with Adaptive Attention

We examine and evaluate adaptive attention [17] (which balances the focus on visual features and focus on textual features) in generating image captions in end-to-end neural networks, in particular how adaptive attention is informative for generating spatial relations. We show that the model generates spatial relations more on the basis of textual rather than visual features and therefore confirm the previous observations that the learned visual features are missing information about geometric relations between objects.
YVONNE: A Fast and Accurate Prediction Scoring Retrieval Framework Based on MF

The recommendation system has many successful applications on e-commerce and social media, including Amazon, Netflix, Yelp, etc. It is a personalized recommendation system. It recommends interesting product and information to the user based on the user’s interests, information, needs, etc. It is extremely important to use the known user information to get the missing information from other users. Most of previous works focus on the learning phase of the recommendation system. Only a few researches focus on the retrieval stage. In this paper, we propose a fast and accurate prediction scoring retrieval framework based on matrix factorization (MF). Our framework (Yvonne) can effectively predict the score of users’ missing items. Experiments with real data show that our framework significantly outperforms other methods on the efficiency and accuracy.
Further empirical data for torsion on bowed strings

Research on bowed string motion focuses on transverse waves rather than on torsional waves. These are believed to play only a minor role for stabilizing vibrations and no role for perception. Here, torsion is measured on both sides of the bow contact point for a variety of bridge-bow distances on a cello string. Every periodic string release is preceeded by a reverse torsional motion independent from bowing position or dynamics. Transverse and torsional motions are coupled and there are cases of stabilization, but also cases of perturbation or surrender. Structural and timing analyses of torsional waves suggest that the earlier concepts of differential slipping can be essentially confirmed while the concept of Schelleng ripples cannot be confirmed and the concept of subharmonics is under question.
Semantics and Soundness

In this chapter, we prove that the temporal type theory developed in Chaps. 4 and 5 is sound in the topos $$\mathcal {B}$$ . To do so, we begin in Sect. 6.1 by recalling the Kripke–Joyal semantics by which to interpret type-theoretic formulas in the topos $$\mathcal {B}$$ . Then in Sect. 6.3 we discuss the sheaf of real numbers and Time. We then proceed to our main goal: proving that our type signature—i.e., the one atomic predicate symbol and the ten axioms presented in Chap. 5—are sound in $$\mathcal {B}$$ . This is done in Sect. 6.5, which begins with a Table 6.2 summarizing the type signature.
A Semantic Method to Extract the User Interest Center

With the evolution of information systems and the large mass of heterogeneous data on the web, problems such as cognitive overload and disorientation (Conklin and Begeman in GIBIS a hypertext tool for team design deliberation, pp. 247–251, [1]) are starting to appear, and to overcome them several techniques have been invented to customize the information system, in order to improve search engine performance as well as recommendation engines. (Zeng et al. in Temporal User Profile Based Recommender System. Artificial Intelligence and Soft Computing. ICAISC 2018, [2], Su et al. in Music Recommendation Based on Information of User Profiles, Music Genres and User Ratings. Intelligent Information and Database Systems. ACIIDS 2018, [3]) have shown that the best techniques to provide relevant results to the specific needs of the user are based on the use of user profiles and more specifically its interests. Generally the selection of interesting documents to a user is done on the basis of his area of interest, inferred from the information about the user or his user profile. Thus the calculation of the interest center is one of the essential elements for a relevant research. In this article we will introduce a new method of extracting the user’s interests from his knowledge, based on the structure of an ontology to deduce the user’s interest’s center, taking into account the semantic links between the graph’s concepts.
Real-Time HDTV-to-8K TV Hardware Upconverter

8K is the pinnacle of the video systems and 8K broadcasting service will be started in December 2018. However, the availability of content for 8K TV is still insufficient, a situation similar to that of HDTV in the 1990s. Upconverting analogue content to HDTV content was important to supplement the insufficient HDTV content. This upconverted content was also important for news coverage as HDTV equipment was heavy and bulky. The current situation for 8K TV is similar wherein covering news with 8K TV equipment is very difficult as this equipment is much heavier and bulkier than that required for HDTV in the 1990s. The HDTV content available currently is sufficient, and the equipment has also evolved to facilitate news coverage; therefore, an HDTV-to-8K TV upconverter can be a solution to the problems described above. However, upconversion from interlaced HDTV to 8K TV results in an enlargement of the images by a factor of 32, thus making the upconverted images very blurry. Super resolution (SR) is a technology to solve the enlargement blur issue. One of the most common SR technologies is super resolution image reconstruction (SRR). However, SRR has limitations to use for the HDTV-to-8K TV upconverter. In this paper an HDTV-to-8K TV upconverter with nonlinear processing SR has been proposed in this study in order to fix this issue.
Classification of Software Defects Triggers: A Case Study of School Resource Management System

In this work, we identify trigger factors of software defects that are responsible for severe defects. We conducted a case study on a system by classifying 842 defects according to their trigger factors and then identified the level of severity they have on this system. Knowing these types of triggers helps software maintenance teams improving the management of software defects by reducing the cost of maintaining the system, consequently the cost of software projects.
Analysis and Verification on Mechanics Mechanism for Flat Digging of Grab

The research on digging resistances is the key to designing the grab, improving the grab’s structure and realizing the automatic flat digging of grab dredger. This article focuses on the mechanical analysis and experimental research of grab’s flat digging combining with theoretical calculation and experiments in dredging process. The theoretical digging resistances in both horizontal and vertical directions have been investigated in mathematical model. With the help of flat digging experiments, the forces on hoist rope and closing rope have been recorded. Then, work out the horizontal and vertical digging resistances based on moment balance. Since a good agreement is achieved between the theoretical calculations with the corresponding independent experimental results, the research has been verified and provides technical support for flat digging in dredging process.
PSP-CI: A Tool for Collecting Developer’s Data with Continuous Integration

Personal Software Process (PSP) is a method focused on the production of software from an individual perspective of quality. Its benefits in the improvement of the personal process are demonstrated by different researches. However, demanded documentation has stopped its implementations both in academy and industry, even though there are semi-automatic tools that try to solve the problem. This research work presents a tool based on Continuous Integration (CI), allowing to automate part of the PSP process. A preliminary experiment is carried out to validate the contribution in the software process, obtaining favorable results with almost no effort for the developer.
An Efficient Algorithm for Runtime Minimum Cost Data Storage and Regeneration for Business Process Management in Multiple Clouds

The proliferation of cloud computing provides flexible ways for users to utilize cloud resources to cope with data complex applications, such as Business Process Management (BPM) System. In the BPM system, users may have various usage manner of the system, such as upload, generate, process, transfer, store, share or access variety kinds of data, and these data may be complex and very large in size. Due to the pas-as-you-go pricing model of cloud computing, improper usage of cloud resources will incur high cost for users. Hence, for a typical BPM system usage, data could be regenerated, transferred and stored with multiple clouds, a data storage, transfer and regeneration strategy is needed to reduce the cost on resource usage. The current state-of-art algorithm can find a strategy that achieves minimum data storage, transfer and computation cost, however, this approach has very high computation complexity and is neither efficient nor practical to be applied at runtime. In this paper, by thoroughly investigating the trade-off problem of resources utilization, we propose a Provenance Candidates Elimination algorithm, which can efficiently find the minimum cost strategy for data storage, transfer and regeneration. Through comprehensive experimental evaluation, we demonstrate that our approach can calculate the minimum cost strategy in milliseconds, which outperforms the exiting algorithm by 2 to 4 magnitudes.
Contour detection in images with speckle by using the bi-geometric structure

The speckle produces severe degradations in digital images, which could be introduced by technological devices during the acquisition, capture or transmission of the images. This perturbation affects, for instance, medical and satellite images. Recently, some methods defined in the bi-geometric structure have presented significant improvements in the processing of image with speckle. In this work, we review some aspects of the bi-geometric structure including a discussion about some of the applications found in the literature focused in the detection of contours in grey scale images with speckle.