Reviewerly/exHarmony huggingface dataset:
Modeling and Reasoning Event-B Models Based on Mathematica

Event-B is a formal method for modeling and reasoning about complex systems, its open toolset Rodin supports integer numbers, but does not support real numbers and mathematical notations like trigonometric functions. The mathematical software Mathematica provides built-in data types and plenty of predicates and functions. In this paper, an approach for modeling and reasoning Event-B models based on Mathematica is proposed, both integer and real numbers, built-in mathematical notations in Mathematica can be utilized directly for modeling, and the simplification and reduction functions in Mathematica are proposed to reason about the generated proof obligations. The experimental results demonstrate the practicability of modeling and reasoning Event-B models based on Mathematica.
Wart Treatment Selection with a Decision Tree-Based Approach

Warts are benign tumors caused by human papillomaviruses (HPVs). Although warts can grow in all parts of the human body, plantar warts which are most commonly known as warts, grow on the soles of the hands and feet. Various types of treatment methods can be used to cure the disease. Two of the most common methods for wart treatment is cryotherapy and immunotherapy. Other than that, the most successful treatment method could be selected related to patient attributes. Selection of the best treatment method for wart treatment is an important topic which is researched in many studies in recent years. In this study, the decision tree based algorithm was developed to help physicians to choose the optimum treatment methods for wart treatment. Analyzing the response of patients to the treatment method is the underlying procedure in the algorithm. For this purpose, a dataset that included 180 patients, with plantar and common warts, who had referred to the dermatology clinic of Ghaem Hospital, Mashhad, Iran was used. The proposed method in the study gave a good accuracy result in both treatment methods while predictive values in ROC Curves were very high which could help the physicians to select optimum treatment related to patient attributes. Therefore, time and cost will be saved for both physicians and patients.
Cross-domain Clothing Image Retrieval Based on Hybrid Shape Feature

Nowadays, Islamic woman garment attracts many users, indicated by the increasing amount of garment industry in many countries. Most of garment purchasing is done electronically. Keywords are inputted to the online shopping system to choose the expected garment model. However, it is very complicated to describe a garment model using keywords. Sketch-based image retrieval (SBIR) is an approach of retrieving a garment based on the content of the clothing. The objective of this paper is to enhance Pyramid Histogram of Oriented Gradient (PHOG) performance on SBIR for Islamic woman garment. This research combined the PHOG and Moore-Neighbour tracing (MNT) method for extracting a new feature. The oriented gradient of the image is calculated; the MNT was used to detect the boundary of the image. Then, the hybrid feature of the oriented gradient and the image boundary is created. The spatial pyramid is then generated from the feature. We refer the proposed method as pyramid histogram of oriented gradient cross-feature (PHOGXF). We conducted simulations on 450 image datasets, which consisted of three categories: blouse-pant, long-dress, and tunic. We did a cross-domain retrieval; we retrieved the clothing images in the database using a sketch image as the query. The result showed that the proposed method obtained the precision value of 73.5% for blouse-pant, 90.4% for long-dress, and 52.1% for the tunic, while the PHOG only achieved the precision value of 18.0% for blouse-pant, 65.4% for long-dress, and 21.0% for the tunic. We concluded that the proposed method (PHOGXF) has significant performance; more than twice as good as the PHOG method.
Augmented Reality with Swift in ARkit and Their Applications to Teach Geometry

Augmented Reality technologies are now entering in a maturing process. We can see major computer technologies companies developing it. For example Google with ARCore born in 2018 or Apple with ARKit born in 2017. These options allow us to develop a very friendly augmented reality environment with a few steps and a very friendly computer-human interaction. An iOS App needs to be developed using Swift a young language born in 2014. This work shows the application of ARkit to ease the learning of Geometry in R3 space.
K-ACE: A Flexible Environment for Knowledge-Aware Multi-Agent Systems

In this paper we consider complex application scenarios, typically concerning smart Cyber-Physical Systems, where several components and subsystems interact among themselves, with human users and with the physical environment, and employ forms of intelligent reasoning for meeting the system’s requirements and reaching its overall objectives. We propose a new multi-component multi-level architecture called K-ACE, which provides a high degree of flexibility in the system’s definition, though within a formal semantics.
Correction of complex purple fringing by green‐channel compensation and local luminance adaptation

In natural photography, defects in camera imaging pipeline often result in some form of colour noise or distortion. Nature of this distortion is generally intertwined with scene dependent variables such as positioning, intensity and composition of light source and local object colour reflectivity. One such defect is called purple fringing aberration (PFA). PFA problems are of two types, one of which corresponds to a localised fringing effect near high contrast zones (termed as Isolated PFA or IS-PFA) and the second which corresponds to a widespread semi-transparent purple haze over a large part of natural scene (termed as complex PFA or C-PFA). Much of the PFA-correction solutions have been driven towards IS-PFA and very little towards C-PFA. Based on a premise that in C-PFA, green channel is heavily suppressed and noisy, while colour information in red and blue channels are largely conserved, authors propose a green-channel compensation algorithm for restoring true natural colours in fringe affected region. To correct white-tuft produced by proposed compensation algorithm, they also devise a suitable localised luminance adaptation procedure to equalise perceived changes in luminance profile. Comparisons with state-of-the-art methods devised to combat this purple haze effect yield promising results for a majority of test cases.
Cybersecurity: 'Guard your front door' and other steps to improve your online security

Contrary to popular belief, hacking is not an art, it's exploitation. We may think of hacking as geeks locked away in dark rooms breaking into your defenceless system. That's not really the case. It's not your computers that are the weakest part of your IT infrastructure - it's you!
Analysis of Inverse Kinematics Method for Human Movement In 2D Animation

Creating a 2D animated human character is a challenging task, especially when using traditional techniques. Several problems arise when the scene gets more complicated and requires a large number of frames, making the animation process takes time even longer. Therefore, the animator needs an efficient method for animating human movement to make the process faster and easier. Inverse kinematics is a method that used for animated characters which have articulated bodies by animate the whole chain of joint with just the end effector. However, this method creates body movements that have no limit on the joints and do not match with human anatomy. In this research, we explore the inverse kinematics method to create a turn-around animation and apply the degree of freedom to the character. The result shows that by adjusting the degree of freedom for each joint, it can make the animation process a lot easier and produce an animation that has body movement with an accuracy of 95%.
Dataset

Semantic metadata standards for buildings such as Brick and Project Haystack show promise in enabling wide-scale deployment of energy-efficiency measures and advanced building management technologies. However, techniques for converting existing diverse and idiosyncratic forms of building metadata to these standard forms is an area of active research. To encourage and facilitate research into the development and evaluation of such techniques, we are releasing an open dataset of metadata pulled from real building management systems, containing attributes for 103,064 points over 92 buildings. In addition, we are releasing an open-source tool for scraping and cleaning metadata from building management systems (BMS) for contribution to the dataset.
Entropy Projection Curved Gabor with Random Forest and SVM for Face Recognition

In this work, we propose a workflow for face recognition under occlusion using the entropy projection from the curved Gabor filter, and create a representative and compact features vector that describes a face. Despite the reduced vector obtained by the entropy projection, it still presents opportunity for further dimensionality reduction. Therefore, we use a Random Forest classifier as an attribute selector, providing a 97% reduction of the original vector while keeping suitable accuracy. A set of experiments using three public image databases: AR Face, Extended Yale B with occlusion and FERET illustrates the proposed methodology, evaluated using the SVM classifier. The results obtained in the experiments show promising results when compared to the available approaches in the literature, obtaining 98.05% accuracy for the complete AR Face, 97.26% for FERET and 81.66% with Yale with 50% occlusion.
GRanDE: Graphical Representation and Design Space Exploration of Embedded Systems

Tasks executing computer vision and machine learning algorithms are becoming popular on embedded platforms. A key characteristic of such tasks is the presence of modes providing different levels of application performance in terms of metrics like accuracy. The system designer has the flexibility to select an appropriate mode for executing such tasks. Secondly, the designer also has the traditional flexibility of choosing suitable components to build the execution platform. Thirdly, the system performance might vary with various external factors (known as context), and during the initial stages of system design, the designer might have the flexibility to support only a subset of the possible contexts. This three-fold flexibility in the hands of the designer has not been explored simultaneously in prior works and raises the complexity of designing embedded systems many-fold. In this paper, we address the design of such systems through a novel framework named GRanDE (Graphical Representation and Design Space Exploration). GRanDE consists of a comprehensive graphical representation to capture the three aspects of the design space discussed earlier. Further, we transform this representation into Constraint Logic Programming (CLP) constructs, which could be used to interactively explore and prune the design space. We demonstrate the applicability of the proposed framework on an embedded system named MAVI having ~1.3 million design points. The generated CLP program could prune up to 99.74% of the design space of MAVI.
Challenges Associated with Generative Forms of Multimedia Content (Keynote Talk)

This short paper presents what is currently the main challenge associated with using Generative Adversarial Networks (GANs) to generate visual media. That challenge is around automatically determining the authenticity of an image/video, which is of increasing importance as fake videos and images start to proliferate on social media, especially when associated with political campaigning. The paper introduces GANs, outlines how they are used to generate visual media and summarises this major challenge.
Stochastic Models to Improve E-News Recommender Systems

Several recommender systems have been proposed in the literature. Some of them address the problem of recommending news to users of newspaper sites. The context of online news presents some particularities: highly dynamic data volume, users access without registration, quick accesses of a few readings, and content is time-dependent. Online newspapers generate in real-time the recommendation lists with few items. The recommenders have a short time to model access, create the list, and present it to the user. All these characteristics make the problem of news recommendation an exciting challenge that has been studied by the academic community with new proposals. However, scarce works study users reading behavior before proposing new methods. In this work, we are interested in characterizing online newspaper users via stochastic models and using attributes extracted from this characterization in recommender systems. First results demonstrate that models who use only information from the recent past are the best. Next, we will look at whether these models are best, varying data contexts, and how to generate more personalized models. Finally, we intend to add all the knowledge in a recommender system, improving or creating a new one.
A Proposal: Must We Ecologize?

October 01 2019 A Proposal: Must We Ecologize? Eric C.H. de Bruyn Eric C.H. de Bruyn Eric C.H. de Bruyn is Professor of Modern and Contemporary Art at the Free University of Berlin. He is an editor of Grey Room and, with Sven Lütticken, editor of Futurity Report (Sternberg, forthcoming). The ecology dossier that he organized for this issue will be complemented by a public lecture series, Kunst und Umwelt: Räume, Orte, Systeme (Art and ecology: Spaces, sites, systems), at the Free University in Berlin, during the winter semester of 2019–20. Search for other works by this author on: This Site Google Scholar Author and Article Information Eric C.H. de Bruyn Eric C.H. de Bruyn is Professor of Modern and Contemporary Art at the Free University of Berlin. He is an editor of Grey Room and, with Sven Lütticken, editor of Futurity Report (Sternberg, forthcoming). The ecology dossier that he organized for this issue will be complemented by a public lecture series, Kunst und Umwelt: Räume, Orte, Systeme (Art and ecology: Spaces, sites, systems), at the Free University in Berlin, during the winter semester of 2019–20. Online Issn: 1536-0105 Print Issn: 1526-3819 © 2019 by Grey Room, Inc. and the Massachusetts Institute of Technology.2019Grey Room, Inc. and the Massachusetts Institute of Technology. Grey Room (2019) (77): 58–65. https://doi.org/10.1162/grey_a_00279 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Eric C.H. de Bruyn; A Proposal: Must We Ecologize?. Grey Room 2019; (77): 58–65. doi: https://doi.org/10.1162/grey_a_00279 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsGrey Room Search Advanced Search This content is only available as a PDF. © 2019 by Grey Room, Inc. and the Massachusetts Institute of Technology.2019Grey Room, Inc. and the Massachusetts Institute of Technology. Article PDF first page preview Close Modal You do not currently have access to this content.
The Cloud Repository

The previous four chapters have focused exclusively on the steps and processes necessary to get PeopleSoft Cloud Manager up and running in the Oracle Cloud. From this point forward, we will be focused on the process of provisioning PeopleSoft environment in the cloud and understanding and utilizing all the features and tools that PeopleSoft Cloud Manager offers. There are four key components that need to be understood in order to properly provision and manage PeopleSoft instance in Cloud Manager: the repository, the topology, the template, and finally the PeopleSoft environment. These four components work together to automate and streamline the environment provisioning process within Cloud Manager.
A Corpus-Based Study of the Rate of Changes in Frequency of Syntactic Bigrams in English and Russian

The article describes general regularities of frequency dynamics of syntactic bigrams and the method used to analyse them. The work objective is to quantitatively estimate the typical rate of change in frequency of syntactic bigrams in English and Russian. Both changes in frequency of words contained in syntactic bigrams and changes in the co-occurrence of these words influence the total rate of changes in frequency of syntactic bigrams. Their contribution to the total rate of frequency changes was estimated using decomposition of the Kullback-Leibler symmetrized divergence. It was also determined to what extent frequencies of the syntactic bigrams respond to major social events. Data on frequencies of syntactic bigrams from the English and Russian sub-corpora of Google Books Ngram were used as a study material. It was found that the regularities of the syntactic bigram usage are similar in English and Russian. The proposed approach can be used in other fields of science.
On-Camera Digital Watermarking and its Application for Law Enforcement and Public Safety

This research explores Law Enforcement Agency (LEA) applications for digital watermarking performed on the camera in real time, combining this with Distributed Ledger Technology (DLT) to suggest workable systems for data cataloguing and image integrity. Reference implementations of both technologies are developed and evaluated for their effectiveness and suitability for these purposes.
Beyond Cause-Effect Pairs

The cause-effect pair challenges focused on the development of inference methods to determine the causal relation between two variables. It is natural to then ask how such methods could generalize beyond the two variable case to settings that either involve more variables—such as is the case in graph learning—or to settings where the relationship between the candidate variables does not fall into one of the classes defined by the challenges. This chapter explores the extension of the proposed methods to such cases. It comes to the conclusion that such extensions are not likely to naturally evolve from the approaches that won the pair challenge.
Life and Professional Activities of a Graduate of the Department of Engineering of Riga Polytechnic Institute Mikhail Krivoshapkin (1888–1943)

Rigan, a graduate of the Department of Engineering (1914) of Riga Polytechnic Institute (RPI) Mikhail Krivoshapkin, after studies worked as an engineer in Russia, where he built grain elevators. From 1920 until deportation to Siberia in 1941 he lived in Riga and was the author of several bridge projects in Latvia, worked as an engineer at Riga Construction Board and was a member of the Riga City Council (1925–1934). He worked in various public organizations. His descendants – grandchildren and great-grandchildren also pursue careers in engineering.
RGB-D Sensors and Signal Processing for Fall Detection

Globally, falls are a major public health problem, and an important cause of morbidity and mortality in the older population. As such, fall detection is one of the most important application areas within the framework of Ambient-Assisted Living (AAL) solutions. Studies report that the majority of falls occur at home, as a person’s living environment is filled with potential hazards, predominantly in the living room and in the bedroom. In addition, recent studies report that fall kinematics varies depending on the weight and size of the falling person, and that most people fall in the evening or during the night. All these features may be captured by RGB-D sensors properly installed in the environment, and detected by suitable processing of the signals generated by the sensors themselves. Fall detection based on RGB-D signal processing has gained momentum in the past years, thanks to the availability of easy-to-use sensors that are able to provide not only raw RGB-D signals but also preprocessed data like joints and skeleton spatial coordinates; additionally, depth signal processing allows to maintain adequate privacy in human monitoring, especially at the levels deemed acceptable by monitored subjects in their own home premises. This chapter will first provide an overview of the RGB-D sensors mostly used in fall detection applications, by discussing their main properties and the modalities by which they have been used and installed. Then, the most relevant signal processing approaches aimed at fall detection will be presented and analyzed, together with an overview of their performances, advantages and limitations, as discussed and presented in the most relevant and up-to-date literature. The aim of the chapter is to provide the reader with a basic understanding of what is reasonably expectable, in terms of detection capability, from RGB-D sensors, applied to fall detection; what are the main depth signal processing approaches according to the sensor usage, and what type of information can be extracted from them.
Absorbing the structural rules in the sequent calculus with additional atomic rules

We show that if the structural rules are admissible over a set $$\mathcal{R}$$ of atomic rules, then they are admissible in the sequent calculus obtained by adding the rules in $$\mathcal{R}$$ to the multisuccedent minimal and intuitionistic $$\mathbf{G3}$$ calculi as well as to the classical one. Two applications to pure logic and to the sequent calculus with equality are presented.
Transactions of Real-Time Medical Services Using Smart Card to Support the Role of Smart Campus

Abstract To improve health service, we can do by using new technology. One example of technology development in health is telemedicine. In this case, the patient data management integrated with electronic checks payments with one card. For that, in this final project is made using smart card system integrated with Unhas Clinic Website. Smart cards that are used by researchers are based on the Consortium Smart Card Indonesia iRFC v 1.0, while the PHP programming language is used to design the website. The creation of MySQL databases and Apache web server responsible for the request-response HTTP are combined in an application called XAMPP. This forms a system that uses a smart card which can save patients’ medical records and perform electronic payment transactions (e-payment). There are 10 people who have been registered as patients on the Website System of Unhas Clinic where 2 of them are insurance patients and have successfully completed the examination. In addition, the examination process at the Website of Unhas Clinic can be done on short distance (0 Km) and long distance (20,3 Km) by using Wireless Fidelity (Wi-fi) network operating system (uplink: 2,94 Mbps; downlink: 20.37 Mbps) and cellular networks such as Provider 1 and Provider 2 (average uplink: 7.1 Mbps; downlink: 5.15 Mbps) with fast connectivity.