Reviewerly/exHarmony huggingface dataset:
Confidence-Calibrated Adversarial Training: Towards Robust Models Generalizing Beyond the Attack Used During Training

Adversarial training yields robust models against a specific threat model, e.g., $L_\infty$ adversarial examples. Typically robustness does not generalize to previously unseen threat models, e.g., other $L_p$ norms, or larger perturbations. Our confidence-calibrated adversarial training (CCAT) tackles this problem by biasing the model towards low confidence predictions on adversarial examples. By allowing to reject examples with low confidence, robustness generalizes beyond the threat model employed during training. CCAT, trained only on $L_\infty$ adversarial examples, increases robustness against larger $L_\infty$, $L_2$, $L_1$ and $L_0$ attacks, adversarial frames, distal adversarial examples and corrupted examples and yields better clean accuracy compared to adversarial training. For thorough evaluation we developed novel white- and black-box attacks directly attacking CCAT by maximizing confidence. For each threat model, we use $7$ attacks with up to $50$ restarts and $5000$ iterations and report worst-case robust test error, extended to our confidence-thresholded setting, across all attacks.
Methods for Visualization of Gastric Endoscopic Mapping Data From Three-Dimensional, Non-Uniform Electrode Arrays

Methods were developed for visualizing three-dimensional endoscopic slow wave mapping data. Simulations representative of normal and abnormal slow wave propagation patterns were generated, allowing qualitative and quantitative evaluation of gridded and spherical interpolation algorithms. Three-dimensional isochronal maps provided a visual representation of slow wave propagation patterns, while mean absolute errors provided a quantitative metric for interpolation performance. Spherical thin plate spline interpolation provided an improvement over current gridded interpolation methods, with a 1.5 to 3.0 fold reduction of mean absolute errors (0.25-0.30 s to 0.08-0.15 s) over three classes of propagation patterns. Different electrode arrangements and densities were tested. A 128-electrode Fibonacci spiral arrangement was proposed as an efficient layout for capturing slow wave dynamics. These methods provide a new visualization technique suitable for endoscopic mapping, and provide a framework for testing and evaluating new interpolation techniques and device designs.
DISCERN: diversity-based selection of centroids for k-estimation and rapid non-stochastic clustering

One of the applications of center-based clustering algorithms such as K-means is partitioning data points into K clusters. In some examples, the feature space relates to the underlying problem we are trying to solve, and sometimes we can obtain a suitable feature space. Nevertheless, while K-means is one of the most efficient offline clustering algorithms, it is not equipped to estimate the number of clusters, which is useful in some practical cases. Other practical methods which do are simply too complex, as they require at least one run of K-means for each possible K. In order to address this issue, we propose a K-means initialization similar to K-means++, which would be able to estimate K based on the feature space while finding suitable initial centroids for K-means in a deterministic manner. Then we compare the proposed method, DISCERN, with a few of the most practical K estimation methods, while also comparing clustering results of K-means when initialized randomly, using K-means++ and using DISCERN. The results show improvement in both the estimation and final clustering performance.
Airfield detection based on JPEG2000 compressed domain

With the rapid increase of optical remote sensing (RS) images, on-orbit specific target detection has been facing more and more challenges: limited processing environment, wireless bandwidth, space, power and storage. To resolve this issue, visual characteristics in the compressed domain are exploited to represent and recognise specific objects. In this study, a new saliency method and an airfield detection framework in the JPEG2000 compressed domain is proposed. First, the authors exploit the header information in raw JPEG2000 code streams to generate structural saliency map, and a great deal of non-structural regions in RS images are eliminated. Second, airfield candidates are extracted from low frequency wavelet sub-bands using line segment detection and the parallel density model. Finally, the geometrical properties of airfield candidates are represented by the speed-up robust features descriptor, and the support vector machine classifier is utilised to gain the final detection results. The proposed framework is evaluated on self-made dataset. Compared with the existing relevant state-of-the-art approaches, the proposed method reduces the processing time by 60% while guaranteeing the detection rate.
The City Is Not a Computer

In this chapter, I will explore the longevity and limitations of city-as-computer scenarios. While contemporary tech companies’ and theorists’ visions reveal their origins in an age of big data and cloud computing, these algorithmic dreams are rooted in earlier reveries. I begin by tracing the history of urban metaphors, particularly that of the city-as-information-processor. Then, moving beyond “information” and its “processing” in creating more generous, inclusive maps of urban information ecologies, I look to other sites and collections—archives, libraries, museums, and repertoires of embodied culture—where urban intelligence is generated, organized, preserved, distributed, and activated. Finally, I reassess the power of these urban metaphors to condition urban design, planning, and administration, and consider alternative epistemological models that are better equipped to encompass the breadth of intelligences embodied in cities.
A Method to Suggest Solutions for Software Bugs

For developers, the debugging process is a huge consumer of time and effort. They receive many bug reports that they must address by reproducing the bugs and reviewing the code for errors. Therefore, an automated system to help the developers in these tasks is very much required. This paper presents a system to find potential solutions in the Stack Overflow (SO) forum of questions and answers focusing on programming issues. It finds the similar problems, which have relevance to the reported bugs in a bug report, analyzed by the experts in SO. We combine two similarity measures to rank relevant SO posts that suggests the solutions for software bugs. Our experimental evaluations on several open-source projects show that the combination of similarity measures performs better than applying the similarity measures individually.
A Linked Open Data Approach for Web Service Evolution

Web services are subject to changes during their lifetime, such as updates in data types, operations, and the overall functionality. Such changes may impact the way Web services are discovered, consumed, and recommended. We propose a Linked Open Data (LOD) approach for managing Web services new deployment and updates. We propose algorithms, based on semantic LOD similarity measures, to infer composition and substitution relationships for both newly deployed and updated services. We introduce a technique that gathers Web service interactions and users’ feedbacks to continuously update service relationships. To improve the accuracy of relationship recommendation, we propose an algorithm to learn new LOD relationships from Web service past interaction. We conduct extensive experiments on real-world Web services to evaluate our approach.
Russian market of electronic resources: providers and users

Aim. The article aims at the analysis of the dynamics and the structure of the Russian markets of scholarly electronic information broken by reference groups of providers and users. Materials and Methods. Materials comprise results of the data processing of the Russian surveys on acquisition budgets in 2012–2018 and published results of the international surveys. We analyze three main reference groups and four sub-groups of the Russian organizations and three reference groups of providers of the electronic scholarly information. We obtained market shares of different reference groups of Russian subscribers and analyzed temporal dynamics of the market structure in 2012–2018. We obtained subscription chains and preferences broken by resource providers in Russia and compared our results with the results of the 2018 survey of American academics. We developed Russian rating of information providers and estimated market shares of each reference group. Results. The market of electronic scholarly information shows continuous concentration towards the group of universities. In 2018, relative share of the university segment of the market of electronic resources made 94%. Since 2015, the share of the reference group of the universities of the 5/100 project increased from 36% to 46%, whereas the share of two national Russian universities shrank from 12% to 9% in 2017–2018. The Russian market of electronic resources is broken in three nearly equal parts related to three groups of resource providers and producers: 35% belong to the group of international publishers, 36% – to the Russian subscription agents and 29% – to the Russian producers and providers of electronic information. Nine of ten organizations responded that they subscribe via Russian information vendors and subscription agents and four of ten – directly via international publishers. This result corresponds to the results of the Academic Library Collection Development Survey 2018. Conclusions. One can conclude that the Russian market of electronic resources is monopolized as referred to the users/consumers of scholarly electronic information and non-monopolized referring the providers and producers of electronic resources. The market comprises three almost equal segments related to three reference groups of providers and producers of electronic resources. The majority of Russian organizations subscribe to electronic resources via Russian electronic information producers or agents.
Tamper Detection of Medical Images Using Modified Hashing Algorithm

In the present modern scenario, health remains as the top most priority of every human being. The identification of the problem and its diagnosis is complicated and remains as the most important part of it. Recently, many of our health related activities use data in the digital format. Digital data is easy and remains in a more comfortable form for transferring the data over long distances. Exchange of Medical Images must be done in a protective and secured manner due to security threats and the attacks of the unidentified intruders. If the privacy is questionable in medical data sharing, then the life of an individual concerned will remain under risk. This has led to the demand for integrity and authentication of medical images. In this paper, an algorithm based on the Secure Hashing Algorithm is proposed to maintain the medical image’s integrity. The Region of Interest (RoI) is separated using spatial co-ordinates and the hash value of the RoI is generated and embedded into the Region of Non-Interest (RoNI) before transmission.
Development of Respiration Measuring Robot

In this study, we developed and tested a monitoring robot to measure the respiration of a person. Upon detecting any abnormality, such as a subject falling down of a person, the monitoring robot moves closer to the person. Subsequently, it automatically extracts the pectoral region from the images and determines the respiration using the measured pectoral movements. We demonstrated that our monitoring robot can automatically perform this series of operations.
Performance Analysis of Reversible Logic-Based Full Adder Using BSIM4 Model

In the current scenario, low power circuits can be designed using the concept of reversible logic. Here in this paper, reversible logic-based digital circuit like full adder is presented. The full adder circuit is implemented by using CMOS BSIM4 model. Design of reversible logic-based full adder circuit is efficient by considering various factors like the number of gates required, quantum cost, number of garbage outputs, and constant inputs. The reversible logic-based design is implemented and simulated with the help of tanner EDA tool having a version of tanner 13.0 tools. It has some performance parameter which is compulsorily considered for the completion of reversible logic circuit. System ideas of reversible logic circuits are cryptography, digital signal processing, computer graphics, and network congestion.
Determining the Initial Value of Carrier Phase Smoothing Pseudorange by Least Squares Straight Line Fitting Technique

In the two-way ranging system of the inter-satellite link, the pseudo-code tracking method is generally used to obtain the ranging accuracy. Because the carrier measurement accuracy is better than the pseudo code, the carrier phase smoothing pseudorange method can be used to further improve the pseudorange measurement accuracy. As for the smoothing method proposed by Hatch, the convergence time will be long when the initial error of the smooth pseudorange is large. To solve this problem, this paper presents a method to determine the initial value of smooth pseudorange using the least squares straight line fitting technique. The simulation analysis results show that the convergence time can be shortened to more than 200 symbols, and the ranging accuracy is with 0.3m, where there is no dynamic condition and the Eb/N0 is 4dB.
A Study on the Current Status of Digital Literacy Education in Secondary Mathematics Curriculum and Lesson Plan

The purpose of this study is to examine the current status of digital literacy education of the mathematics in accordance with the 2015 revised national curriculum and to draw up substantial improvements to foster digital literacy education in mathematics. This study intends to carry out a multi-layered inspection on how contents related to digital literacy has been adopted in the mathematics curriculum, how the math teacher perceive digital literacy education, and how they put this into practice in real classes. The study investigated how digital literacy has been adopted according to the changes of the mathematics curriculum and aggregate and considerate aspects how mathematics adopted digital literacy by characteristics in mathematics through analysis of standards in the 2015 revised national mathematics curriculum. In addition, this study analysis the current status of digital literacy education in mathematics education through surveying teaching cases, and exploring the improvements for digital literacy education in Mathematics education Through this study drew three suggestions so as to enhance digital literacy education of the mathematics: reinforcement of learning contents for strengthen digital literacy education of mathematics; activation of cooperative learning for digital literacy education of mathematics; and establishing a system to improve math teachers’ professionality.
Author Correction: Evaluating FAIR maturity through a scalable, automated, community-governed framework

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
ПРО ПРИРОДНИЙ ТА ШТУЧНИЙ ІНТЕЛЕКТ КІБЕРНЕТИЧНИХ СИСТЕМ

It is proposed as part of the concept of the “cybernetic system” to distinguish the following components: - cybernetic systems impervious to information, as a control system; - cybernetic systems permeable to information: intelligent functional systems based on natural intelligence; Intelligent information systems based on artificial intelligence. From an analysis of the content of the concept of “artificial intelligence,” it follows that at present there is no unambiguous definition of the content of this concept. Almost all authors agree that artificial intelligence should be similar to human intelligence. From an analysis of the content of the concept of “natural intelligence,” it follows that its basis is the central regularity of the integrative activity of the brain. It is proposed to define thinking as the possibility of representing things in measure, and intelligence as the ability to implement the process of measuring things. The measure is the presentation of a thing in the form of a dialectical unity of concepts general (qualitative definition) – single (quantitative definition). It is shown that the main problem that has not been solved so far for artificial neural networks is the problem of the formation of a capable mathematical model of a natural neuron based on the central regularity of integrative brain activity. The second problem requiring its solution is the need to teach the artificial intelligence system to "measure" things, as well as their properties. Without mastering this ability, no artificial intelligence system can implement the actions that characterize the activity of the natural neural network. The third problem is the need to train the artificial intelligence system to remember the previous experience. Manipulating knowledge is possible only by applying the laws of natural intelligence. Therefore, to form the knowledge base, experts are involved as a source of knowledge and knowledge engineers, as specialists in the extraction of knowledge from experts. Moreover, between the concepts of “data” and “information”, as well as “information” and “knowledge”, there is a dialectical connection in the form of “single” – “general”. Intelligent information technology can be the basis for the implementation of cybernetic systems permeable to information: intelligent functional systems; intelligent information systems. The fundamental task that needs to be solved is the task of establishing the composition and content of the concept of “unit of knowledge”.
Effectiveness of learner-centered reading activities through movie appreciation on Korean college students’ reading achievement

The purpose of this study is to investigate the effectiveness of using movies in an English reading course at the college level. In order to achieve this purpose, the following questions were constructed; 1) How have reading activities through movies affected Korean college students’ reading achievement?, 2) How have those activities affected the students’ attitudes toward English study?, and 3) How have the students responded this movie-used reading class affectively? Thirty two college students participated, and a paired t-test was conducted to compare two observations, before- and after- scores on the students’ reading achievement and their attitudes toward English study. The results of data analysis showed that statistically significant differences were found between pre- and post-reading achievement tests, and those reading activities through movies positively affected students’ interest and confidence in English reading. Also, this quantitative result has been verified by qualitative data such as students’ reflective journals and in-depth interviews with students, that added credibility to the statistical findings. Therefore, this study suggests that using movies in the classroom attract students’ attention, and provide language learners with live language. Pedagogical implications are also made on the effective teaching of English reading in Korean classroom settings.
A Bayesian nonparametric test for conditional independence

This article introduces a Bayesian nonparametric method for quantifying the relative evidence in a dataset in favour of the dependence or independence of two variables conditional on a third. The approach uses Polya tree priors on spaces of conditional probability densities, accounting for uncertainty in the form of the underlying distributions in a nonparametric way. The Bayesian perspective provides an inherently symmetric probability measure of conditional dependence or independence, a feature particularly advantageous in causal discovery and not employed in existing procedures of this type.
A Knowledge and Probabilistic Based Task Planning Architecture for Service Robotics

Service robots have to face task diversity, large, uncertain and partially observable environments, which are inherent aspects of the domestic domain and increase the task planning problem’s complexity. Thus, in an attempt to overcome these challenges, in this work a task planning architecture for service robotics is proposed, which integrates a knowledge base approach with partially observable Markov decision processes (POMDP), and is constituted by three main components: (a) a knowledge base, (b) a POMDP construction module and (c) a task controller. Through a knowledge representation scheme, domain relevant information is exploited to define useful sub-regions in the planning search space. Once the search space is segmented, local POMDP policies are computed for each sub-region, then, a graph-based policy for the main task is built as a collection of these policies, for which the controller will determine the order in which they will be executed. Additionally, our architecture is able to integrate new functionalities as the robot is endowed with them. For evaluation purposes, a mobile robot navigation problem was used as case study to test our architecture, which shows the advantages of using domain specific knowledge in a task planning problem.
Investigating Convolutional Neural Networks using Spatial Orderness

Convolutional Neural Networks (CNN) have been pivotal to the success of many state-of-the-art classification problems, in a wide variety of domains (for e.g. vision, speech, graphs and medical imaging). A commonality within those domains is the presence of hierarchical, spatially agglomerative local-to-global interactions within the data. For instance in natural images, neighboring pixels are more likely contain similar values than non-neighboring pixels which are further apart. To that end, we propose a statistical metric called spatial orderness, which quantifies the extent to which the input data (2D) obeys the underlying spatial ordering at various scales. In our experiments, we mainly find that adding convolutional layers to a CNN could be counterproductive for data bereft of spatial order at higher scales. Furthermore, we present a theoretical analysis (and empirical validation) of the spatial orderness of network weights, where we find that using smaller kernel sizes leads to kernels of greater spatial orderness and vice-versa.
Three-coordinate Definition of Color Mark and Distance To Objects According to Strereo Image

This article discusses the determination of distances to objects in three coordinates. To determine the distance of objects, a depth map is constructed using the SAD algorithm; to determine the offset, a color mark is determined and its movement in the frame is calculated by calculating the coordinates of the center of gravity of the color mark on two frames.
A Service Performance based Dynamic Provisioning Approach in Containerized Cloud Environments

Along with the evolution of cloud technology and big data technology, cloud service is becoming an emerging trend for big data processing. Cloud services are facing the challenges of dynamic provisioning and adaptation to the unpredictability of business requirements. The emergence of container technologies provides new technical opportunities for the optimization of service performance and the dynamic provisioning in cloud environments. In this paper, a service performance based dynamic provisioning approach in containerized cloud environments is proposed. The approach continuously monitors and collects the system metrics and based on the metrics customized scheduling strategies of the cloud environment are dynamically designed and adjusted. The feasibility of the approach is verified by experiments, and the experimental results show that the proposed approach can successfully completed the dynamic provisioning of the cloud environment, and it can improve the availability and reliability of cloud services. It is a new attempt of the cloud support environment to meet the business requirements.