Reviewerly/exHarmony huggingface dataset:
Transitivity and Equivalence in Decidable Fragments of First-Order Logic: A Survey

In this talk, I survey recent work on extensions of various well-known decidable fragments of first-order logic, in which certain distinguished predicates are required to denote transitive relations or equivalence relations. I explain the origins of this work in modal logic, and outline the current state-of-the-art.
Basics on Mapping Solar Radiation Gridded Data

There is a lot of gridded information on meteorological variables elsewhere. Numerical weather prediction models and satellite-derived models deliver time series and aggregates of main meteorological variables with global coverage that can be finally used to create maps offering information on the spatial variability of those magnitudes. This chapter intends to give a very simple overview of mapping solar radiation data or any other gridded variable using QGIS open-source Geographic Information System.
Improved Parameter Estimation Method for Bilateral Filter with Distribution Distance

Makishi et al. (2017) proposed a method that estimates the parameters for a bilateral filter, based on the distribution distance of images. This study proposes an improved version of the Makishi et al. (2017) method, which includes three new contributions. Firstly, our improved method was verified with two image sizes and two noise distributions. Secondly, five distribution distance functions were examined for the local search of parameter sets, where SKLD was found to be slightly superior to HD in terms of image quality and execution time. Finally, the parallelization of local search was examined for faster parameter estimation with recent multi-core processors. With a 2.8GHz Xeon processor of 10 cores, the parameter estimation times were reduced to 36ms (256x256 pixel) and 1.03 s (1024x1024 pixel).
Test control of students' knowledge in the process of mastering the interdisciplinary course «Ergodesign» by means of LMS Moodle

The possibilities of an interdisciplinary automated training system in the modular object-oriented environment of distance learning MOODLE are highlighted. The structure of the training course «Ergodesign» is presented and the possibilities of electronic learning management systems for the implementation of test control of students' knowledge are considered. Prospects for the development of modern distance learning technologies are outlined.
Encode-then-Encrypt: A Novel Framework for Reliable and Secure Communication

Achieving a reliable and secure communication is the major challenge in the context of data communication and storage. In this paper, Encode-then-Encrypt framework is defined using linear error correcting codes and elliptic curves to address these challenges as a single solution rather than addressing them separately. The working of the proposed framework is explained in detail by taking Reed-Solomon codes (with a set of encoding and decoding algorithms) and elliptic curves of characteristic 2 (with a set of encryption and decryption algorithms). We have outlined the advantages of using such elliptic curves and error correcting codes over any other cryptosystem defined in the existing literature. The proposed framework can be implemented as a part of any real-time communication system to ensure reliability and security.
A New Method Based-Gentle Adaboost and Wavelet Transform for Breast Cancer Classification

In this paper we have realized a comparative study of mammograms classification accuracy based on a new Gentle Adaboost algorithm for different wavelet transforms and different features. Our proposition deals with the combination of a new Gentle Adaboost based algorithm with three wavelets transforms. In this new algorithm, the main classifier is realized by weighted weak classifiers. These weak classifiers are constructed from the sub-bands of discrete wavelet transform, stationary wavelet transform and double density wavelet transform. Used features are extracted from transformed mammograms. We have investigated the effect of these wavelet transforms combined with the extracted features on the classification accuracy. Receiver Operating Curves (ROC) tool is employed to evaluate the performance of the propositions. Mammograms of MIAS Database are used as samples to classify. True positive rate is plotted versus false positive rate for different types of features and for Gentle Adaboost iterations. Results showed that the best area under curve (AUC), is reached for Zernike moments combined with double density wavelet transform and it is equal to 1 for both t = 10 and t = 50.
Information environment the Internet as a means of improving the efficiency of the educational process

the concept of “cloud technologies” is considered in this article, which over the past decade has provided Internet users with great opportunities, both integrated physical resources, and various program services. The types of "cloud infrastructure" and the possibility of their use in the educational process are investigated. software services available for online learning are enumerated.
The effective application of intelligent technology in electrical engineering and its automation

With the advancement of social and technology, the technical level of the electrical industry has been continuously improved, and many intelligent achievements have been relatively mature applications, effectively improving the productivity of the electrical industry and providing more stable and safer services for social development. To this end, the article introduces the application background and advantages of intelligent technology, analyzes the application value of intelligent technology in electrical engineering automation, so that the electrical industry can reasonably apply intelligent technology and give full play to its functions and values.
High Level Synthesis and Implementation of Cryptographic Algorithm in AHIR Platform

This paper proposes a High Level Synthesis (HLS) design methodology that translates complex algorithms modeled in high level language to hardware description. The existing HLS strategies fails to provide adequate abstraction to the underlying hardware details and thus limits software programmers from designing complex and advanced cipher algorithms. In this paper the method of generating synthesizable Register Transfer Level (RTL) design from algorithm is accomplished through an open framework called AHIR, an acronym for a hardware intermediate representation. The integrated design flow intends to generate layout from algorithm with minimal human intervention and thus offers software programmers with ample opportunities to design application specific digital hardware. The paper discusses several highlights of the design flow including savings in verification, rapid prototyping and shorter time to market together with various performance overheads. The cipher algorithms implemented in this paper includes the widely accepted Advanced Encryption Standard (AES) along with other established lightweight algorithms namely PRESENT, Light Encryption Device (LED) which are effective for resource constrained applications. A comparative performance analysis was carried out between the high level design approach and the traditional RTL style based on their FPGA and ASIC implementation.
A Tool for Knowledge-Oriented Physics-Based Motion Planning and Simulation

The recent advancements in robotic systems set new challenges for robotic simulation software, particularly for planning. It requires the realistic behavior of the robots and the objects in the simulation environment by incorporating their dynamics. Furthermore, it requires the capability of reasoning about the action effects. To cope with these challenges, this study proposes an open-source simulation tool for knowledge-oriented physics-based motion planning by extending The Kautham Project, a C++-based open-source simulation tool for motion planning. The proposed simulation tool provides a flexible way to incorporate the physics, knowledge, and reasoning in planning process. Moreover, it provides ROS-based interface to handle the manipulation actions (such as push/pull) and an easy way to communicate with the real robots.
Big Data Concept in Small and Medium Enterprises: How Big Data Effects Productivity

The topic of data mining is a popular subject, especially nowadays. Data mining is a process which accesses the information among large-scale data and mine the knowledge. The most widespread use in the literature is to process large amounts of data automatically or semi-automatically to find meaningful patterns. Depending on the pace of the spread of Internet usage, digital media takes the place of traditional media, so the number of textual forms in digital media is increasing day by day. For this reason, text mining techniques should be used for text review. Such as text mining, data mining, machine learning technologies are related to the big data concept, and these technologies are used for increasing productivity in too many areas. According to the analysis in the United Kingdom and the United States, companies adopting decision-making based on data have been observed to be 5–10% higher in output and productivity than firms using only information technology components such as software products. So, even if small and medium enterprises can adopt these technologies in their life cycle can gain more productivity and economic profit in their areas.
Influence of remote education on consumer value of university education

Purpose The purpose of this paper is to study the influence of remote education on the consumer value of university education by the example of modern Russia. Design/methodology/approach The authors determine the consumer value of university education in modern Russia in the conditions of the availability of predominantly traditional education; determine socio-economic problems that are caused by the low consumer value of university education in modern Russia; determine the potential of remote education in the increase of the consumer value of university education; and develop recommendations for the increase of the consumer value of university education in modern Russia through the development of remote education. Findings It is concluded that traditional university education is dominating in Russia. It is standardized and does not allow for the full consideration of individual capabilities and needs of each separate student, which causes the low consumer value of university education. The limitation of traditional and remote education, caused by the fact that educational services in each form are provided by completely different universities, hinders the development of the potential of remote education in stimulating the increase of the consumer value of university education. Originality/value In order to solve this problem, it is recommended to unify traditional and remote education within the diversification of the forms of the provision of educational services by modern Russian universities. For that, a conceptual model for increasing the consumer value of university education in modern Russia through the development of remote education is presented. This model focuses on applicant and students with their individual capabilities and needs and universities with their material and technical, intellectual, marketing and other resources. At that, the educational form goes to the background, being not a self-goal but a method of its achievement – the provision of the high consumer value of university education.
Flash Animation Watermarking Algorithm Based on SWF Tag Attributes

This paper presents a Flash animation watermarking algorithm based on SWF tag attributes. First, the SWF file is converted into an XML file, and the watermark image is converted into a binary data stream. Second, filter and categorize the tags and their attributes that have minimal effect on the animation in the XML file, and embed the binary data stream into the XML file according to a certain sequence of tag attributes. Finally, the XML file embedded in the watermark information is converted into a SWF file. Experiments show that the algorithm proposed in this paper has good transparency and invisibility, and it has the characteristics of high hiding capacity.
A New Bi-Level Encoding and Decoding Scheme for Pixel Expansion Based Visual Cryptography

Mapping of image-based object textures to ASCII characters can be a new modification towards visual cryptography. Naor and Shamir proposed a new dimension of Information security as visual cryptography which is a secret sharing scheme among N number of participants with pixel expansion. Later on, many researchers extended the visual secret sharing scheme with no expansion of pixel regions in binary and color images. By stacking k shares the secret can be decoded using normal vision. In this paper the authors have proposed a modification towards visual cryptography by converting the message in the form of printable ASCII character-based numerical encoding patterns in a binary host image. The encoding of the message is represented as ASCII numeric and a texture of those numeric are arranged to form a binary host image. Then, N numbers of shares are built up but after stacking all the shares the decoding of the message is achieved by converting ASCII numeric to the secret.
Semi-doubly optimal concentric circles fitting with presence of heteroscedasticity

Previous studies focus on homogeneous and isotropic assumptions about the noisy data. Many methods have been developed recently for fitting concentric circles to data. In this paper, these statistical assumptions have been relaxed. To the best of our knowledge, only one iterative method has been recently developed. Due to its complexity, no such algorithm is available to compute the reliable maximum likelihood estimator (MLE). Accordingly, we have developed four new methods that outperform the existing methods including the orthogonal distance regression (ODR). We also discuss which of these methods is superior according to the four principles: statistical efficiency, accuracy, robustness, and computational efficiency. Numerical experiments on synthetic and real images have been conducted to validate our findings.
Databases for evaluating interferences between affective content and image quality

The two databases here described were generated to evaluate the role of affective content while assessing image quality (Corchs et al., 2018) [1]. The databases are composed of images JPEG-compressed together with the subjective quality scores collected during psychophysical experiments. To reduce interferences in quality perception due to image semantic, we have restricted the semantic content, choosing only close-ups of face images, and we have considered only two emotion categories (happy and sad). We have selected 23 images with happy faces and 23 images with sad faces of high quality. For what concerns image quality we have considered JPEG-distortion with 4 levels of compression, corresponding to q-factors 10, 15, 20, 30. The first image database, hereafter called MMSP-FaceA, is thus composed of 230 images (23+23) × 5 quality levels (including the original high quality pristine images). To better consider only interferences in quality perception due to affective content, we have generated a second image database where the background of images belonging to MMSP-FaceA has been cut off. This second image database is labelled as MMSP-FaceB. Psychophysical experiments were conducted, on a controlled web-based interface, where participants rated the image quality of the two databases in a five point scale. The two final databases MMSP-FaceA and MMSP-FaceB are thus composed of 230 images each, together with the raw quality scores assigned by the observers, and are available at our laboratory web site: www.mmsp.unimib.it/download.
Interactive visual analysis of spatiotemporal characteristics in tropical cyclone trajectory data

This paper presents an integrated visualization system that enables interactive visual analysis of trajectory data of tropical cyclones. This system couples together a novel visual exploring interface with a progressive-partition based trajectory clustering algorithm to enable users to interactively explore spatiotemporal patterns of tropical cyclone. The position, intensity change, and movement of cyclone can be observed vividly from the 2D spatial view. The occurrence frequencies, the lifetime, seasonality distribution, and other statistical features are computed on the fly during analysis and are inspected in multiple linked views. The experimental results with real cyclone data show the effectiveness of the proposed approach.
A novel multisignature scheme based on chaotic maps

In this paper, a novel multisignature scheme based on chaotic maps is proposed. The purpose of multisignatures is to manage the complexities of a document signed by numerous signatories. The chaotic system is an encryption method proposed in recent years that has received widespread attention in th e field of cryptography. This paper first examines the methods of multisignatures and chaotic maps, and then proposes a multisignature scheme that was designed using chaotic maps. During the processing of a multisignature scheme, to authenticate the precision of the received document, the signatory must first obtain the signed document, and then utilize the characteristics of chaotic maps to recover the original document. If the recovered document is meaningful, this indicates that no errors exist in the signature, thus the signatures are valid and the document can be signed. If the recovered document is not sufficiently clear, signing is denied. At present, because no relevant literature exists that has proposed utilizing chaotic maps to establish a multisignature system; this paper aims to develop a novel research method.
The Impact of Mobile Devices on Self-Directed Learning and Achievement

As mobile devices have become increasingly ubiquitous in society, the potential for impacting student learning in classroom settings has been the subject of debate. Instant information access and collaboration have been mentioned as potential benefits of mobile device access. However, the potential for mobile devices to foster self-directed learning in students and improve student achievement on open-ended design problems has not been explored. Therefore, this chapter presents the findings from research with middle school students working in small groups on an engineering design challenge. The findings explore the relationships between access to mobile devices, student achievement, and student self-directed learning.
Access Control in the Wild Using Face Verification

In the past few years, face recognition has received great attention from both research and commercial communities. Areas such as access control using face verification are dominated by solutions developed by both the government and the industry. In this chapter, a face verification solution is presented using open-source algorithms for access control of large-scale events under unconstrained environments. From the type of camera calibration to the algorithms used for face detection and recognition, every stage has a proposed solution. Tests using the proposed solutions in the entrance of a building were made in order to test and compare each solution proposed.
A Seismic Signal Denoising Method Based on Wavelet Comprehensive Threshold

The wavelet comprehensive threshold is used to inherit and develop the advantages of hard threshold and soft threshold denoised method. Based on the small wavelet coefficients of the noise signal and the large wavelet coefficients of the seismic signal, the simulation experiment of the Ricker signal and the noise reduction experiment is carried out. The simulation results show that the MSE of the wavelet comprehensive threshold is the closest to the original signal waveform after noise reduction, and the energy of the high frequency part of the waveform is reduced and the low frequency part is suppressed. Finally, the actual seismic waveform, for example, the noise reduction of the actual waveform can be the first time of the waveform, and the waveform of the effective signal energy, noise signal energy is suppressed.
Revisiting the Secret Hiding Assumption Used in Verifiable (Outsourced) Computation

Privacy-preserving Verifiable (outsourced) Computation (PVC) is a hopeful primitive that enables a resource-constrained client to outsource expensive and sensitive workloads to powerful but possibly untrusted servers and to verify the correctness of the returned results. Specifically, the privacy property is of significance for this type of primitive. Then, how to provide the privacy property has become a central interest of many researchers. At ACM-ASIACCS 2010, Atallah and Frikken introduced a new hardness assumption called the Secret Hiding assumption (SH), which includes the Weak SH assumption (WSH) and Strong SH assumption (SSH). Moreover, for the outsourcing of the multiplication of large-scale matrices, the authors constructed two concrete PVC protocols whose privacy is based on the decisional-WSH assumption and decisional-SSH assumption, respectively. Until our work, to the best of our knowledge, there is no paper that precisely explored the hardnesses of the WSH assumption and SSH assumption. Thus, in this paper, we first propose an analysis method, using the rank distribution of the matrix as the basic strategy, to evaluate the hardnesses of two problems corresponding to the decisional-WSH assumption and decisional-SSH assumption. Unfortunately, our analysis can efficiently break the decisional-WSH assumption and decisional-SSH assumption for a wide range of parameters with overwhelming probability. Then we employ the idea of the above analysis for breaking the SH assumption to similarly break the privacy of Atallah and Frikken's PVC protocols. The results show that the adversary's advantages are non-negligible. Finally, we present some detailed experimental results to support our theoretical argument.
Picturing agreement between clustering solutions using multidimensional unfolding: An application to greenhouse gas emissions data

When evaluating a clustering solution, we often have to compare alternative solutions – e.g., to address clustering stability or external validity. Each comparison essentially relies on a contingency table referring to a pair of (crisp) clustering solutions. These data is commonly used as an input to: (1) an assignment problem, to match the clusters of the two partitions; (2) determine several indices of agreement; (3) represent the two partitions in a two-dimensional map resorting to Correspondence Analysis. We propose using the Multidimensional Unfolding (MDU) technique to picture the cross-classification data between two partitions, complementing a clustering evaluation analysis and overcoming some limitations of the traditional approaches (1) to (3). This approach relies on a new similarity measure that excludes agreement between clusters due to chance alone. The resulting MDU map is very easy to interpret, picturing agreement between clustering solutions: the further apart are the clusters (represented by points) from the two partitions, the larger the (Euclidean) distances between the corresponding points. Two applications illustrate the relevance of this approach: an application to a data set on UCI Machine Learning Repository to access clustering external validity; and an application to greenhouse gas emissions data to address the temporal stability of clustering solutions, the clusters of European countries, which have homogeneous sources of pollutant emissions, being compared over three years.