Reviewerly/exHarmony huggingface dataset:
OBDEX – Open Block Data Exchange System

Biobanks have become central structures for the provision of data. Raw data such as whole slide images (WSI) are stored in separate systems (PACS) or in biobank information systems. If segmentation or comparable information is to be exchanged in the context of the compilation of cases for the application of AI systems, the limits of proprietary systems are quickly reached. In order to provide these valuable (meta-) data for the description of biological tissue samples, WSI and analysis results, common standards for data exchange are required. Such standards are not currently available. Ongoing standardization developments, in particular the establishment of DICOM for digital pathology in the field of virtual microscopy, will help to provide some of the missing standards. DICOM alone, however, cannot close the gap due to some of the peculiarities of WSIs and corresponding analysis results. We propose a flexible, modular and expandable storage system - OBDEX (Open Block Data Exchange System), which allows the exchange of meta- and analysis data about tissue blocks, glass slides, WSI and analysis results. OBDEX is based on the FAIR data principles and uses only freely available protocols, standards and software libraries. This facilitates data exchange between institutions and working groups. It supports them in identifying suitable cases and samples for virtual studies and in exchanging relevant metadata. At the same time, OBDEX will offer the possibility to store deep learning models for exchange. A publication of source code, interface descriptions and documentation under a free software license is planned.
Specification of Agent Based Robotic Systems Using Hierarchical Finite State Automatons

The paper assumes the composition of robotic systems out of embodied agents. It presents a utilitarian decomposition of an agent into subsystems. Both subsystem behaviours and their selection can be described in terms of Finite State Automatons (FSA), thus Hierarchic FSAs result. Mathematical formalisation of this description enables the verification of correctness of some aspects of system operation.
Ding- dong

In this note the Storybell robot is described as the main touch-point of a remote reading aloud service which enables senior readers to read stories from their home to children. The Storybell acts as a tangible interface for children to interact with the community of readers as well as with the single reader. A research strategy based on Wizard of Oz (WoZ) and experience prototyping methods is described with the aim of probing parents' trust towards the remote readers as well as making parents reflect on their parental responsibility into guiding respectful interactions of their child with the community of readers. The note highlights the potential of the Storybell as both a tangible interface for children and a domestic embodiment for remote people and suggests involving parents as the wizards in WoZ experiments with their children to overcome trust issues and inspire strategies to guest the embodied remote readers at home.
A Tacit Assumption Behind Lewis Triviality That Is Not Applicable to Product Space Conditional Event Algebra

For a given (generally, assumed atomic) nontrivial Boolean algebra B and any a, b in B with b ≠ ∅, a conditional event (a|b) is said to exist if for all probability measures P over B, there exists some mapping P^(not necessarily a probability measure) and some algebra B^ (not necessarily Boolean) containing (a|b) such that if P(b) > 0, then P^((a|b)) = P(a|b), ordinary conditional probability of a given b. But, in turn, Lewis’ famous triviality result shows equivalently that if his forcing hypothesis holds—i.e., B and B^ at least overlap at B*(a, b, (a|b)), the Boolean subalgebra generated by a, b, and (a|b) (and for consistency P = P^)—then P must be trivial in the sense that a, b must be P-independent. The apparent informal implication of this, as gleaned from Lewis’ own comments and that of the numerous papers that are based on his result, is that this spells the “death knell” for Stalnaker’s thesis or even for any attempt at constructing a consistent nontrivial algebra of conditional events deriving from a Boolean algebra B. In this paper, we show two basic results contradicting this “conclusion”. First, fully consistent and nontrivial Boolean (in fact, sigma-) algebras of conditional events can always be constructed relative to any given Boolean algebra B, based upon a standard product probability space construction. This avoids Lewis’ forcing hypothesis—and thus Lewis triviality—yet satisfies natural isomorphic and homomorphic relations with B. Second, a key step in Lewis’ own proof, involving conditioning, when generalized to a setting where his forcing hypothesis no longer is imposed, leads directly to a simple criterion determining the structure of consistent nontrivial Boolean conditional event algebras. This criterion is also directly related to the well-known property of import/export in AI (Artificial Intelligence) systems and conditional logic.
A Generalized Net Model of the Hybrid System for Diagnostics

A generalized net model, which describes the diagnostic process of diseases using intelligent techniques is constructed in the paper. By analyzing the retrospective physiological, medical, individual-behavioral parameters of the patient we can find correlation to a particular disease, its progression and the likelihood of a response to treatment. The model can be used for monitoring and analysis of the process of assessment.
Heuristic Cloudlet Allocation Policy for QoS Improvement in Cloud

Cloud computing is an ocean of configurable set of computing resources allowing pervasive admittance to these resources located in the data centers. Quality of service (QoS) is a crucial research direction in cloud that identifies various critical issues such as optimizing response time, degree of load imbalance, makespan improvement, completion time of cloudlet (Task), loss of bandwidth, and the latency of the entire system. Scheduling plays a major role for connectivity of task (cloudlet) to virtual machine. It is tedious to design a distribution policy that works well for the binding of cloudlets to relevant resources in multi-faceted environments without deriding the QoS indicator. This work focuses a heuristic for distribution planning of cloudlets that appositely works in multi-faceted environments, in which selection of cloudlet performed in a hybrid manner such as shortest job first (SJF) follows by longest job first (LJF) manner. Finally, the cloudlets ceded to maximum power factor virtual machines (VMs) such as when this machine overloaded, load is transfer to next VM which has maximum power factor. This strategy uniformly distributes the cloudlets among the VMs that balance the load in excellent way. This also minimizes the overall finalization time (makespan) on the VMs and also on the hosts in the data center, reduces processing cost and maximizes the resource utilization. The experiment is carried out using CloudSim 3.0.3 toolkit, expanding some of the base classes of the simulator and comparing the results with existing distribution policy which shows our proposed policy outperformed the existing policy.
Generating Gray codes for weak orders in constant amortized time

A weak order is a way to rank n objects where ties are allowed. In this paper, we develop a generic framework to generate Gray codes for weak orders. We then describe a simple algorithm based on the framework that generates cyclic 2-Gray codes for weak orders in constant amortized time per string. This is the first known cyclic 2-Gray codes for weak orders. The framework can easily be modified to generate other Gray codes for weak orders. We provide an example of using the framework to generate the first shift Gray codes for weak orders in constant amortized time per string, where consecutive strings differ by a shift or a symbol change.
Quantization error in stereo imaging system with noise distributions

The problem of estimating quantization error in 2D images is an inherent problem in computer vision. The outcome of this problem is directly related to the error in reconstructed 3D position coordinates of an object. Thus estimation of quantization error has its own importance in stereo vision. Although the quantization error cannot be controlled fully, still statistical error analysis helps us to measure the performance of stereo systems that relies on the imaging parameters. Generally, it is assumed that the quantization error in 2D images is distributed uniformly that need not to be true from a practical aspect. In this paper, we have incorporated noise distributions (Triangular and Trapezoidal) for the stochastic error analysis of the quantization error in stereo imaging systems. For the validation of the theoretical analysis, the detailed simulation study is carried out by considering different cases.
Study on the Acupoint Location of <i>Sameumgyo</i> (SP6) - Regarding the Theory of 8 Cun above the Tip of the Medial Malleoulus -

Other SectionsAbstract서 론연구방법연구결과고 찰결 론AcknowledgementFundingData availabilityConflicts of interestReference
Optical Flow Prediction in Auto Driving from Single Image via Conditional Variational Auto-Encoder

In auto-driving tasks, visual prediction is very meaningful and difficult, because the motion of the predicted target has many possible outputs. It is very effective to predict the motion of the target by optical flow, but the output of the previous optical flow models is fixed. In this paper, we proposed an optical flow prediction model via Conditional Variational Auto-Encoder. In experiment, the model can effectively predict a variety of possible optical motions in the real world. A number of experimental results show that our models outperform all prior state-of-the-art on the test of a recent optical flow prediction competition.
Physicist and teacher K. D. Kraevich and his work for national education development in post-reform Russia

Abstract The article highlights the input of physicist and teacher K.D. Kraevich in the Physics education development in schools of post-reform Russia. It was during this time that the basis for modern Physics teaching was laid out. During this time a lot of physicists and academicians got their education, who then went on to make great discoveries in the XXth century. The article also highlights the importance of the works by K.D. Kraevich for contemporary teaching experience.
Color Inference from Semantic Labeling for Person Search in Videos

We propose an explainable model for classifying the color of pixels in images. We propose a method based on binary search trees and a large peer-labeled color name dataset, allowing us to synthesize the average human perception of colors. We test our method on the application of Person Search. In this context, persons are described from their semantic parts, such as hat, shirt, ... and person search consists in looking for people based on these descriptions. We label segments of pedestrians with their associated colors and evaluate our solution on datasets such as PCN and Colorful-Fashion. We show a precision as high as 83% as well as the model ability to generalize to multiple domains with no retraining.
Constitutional Norms for Pandemic Policy

The COVID-19 pandemic unleashed a torrent of legal and political commentary, and rightly so: the virus touches every corner of life and implicates many areas of law. In response to the virus, governments, civic institutions, and businesses struggled to protect public health, respect individual autonomy, and enable Americans to satisfy their elemental instinct to congregate with one another.Our early pandemic response largely failed. Our dysfunction led to deaths and lost livelihoods, in part because public perceptions about the virus, and interventions designed to address to it, substantially fell along predictable ideological lines. We must take stock of these failures so that we can do better when the next pandemic arrives, as it surely will.We argue that ingredients for broader consensus already exist, even if they remain obscured by political and policy rancor. Americans share the common goal to safely return to families, jobs, schools, places of assembly, pubs, parks, and the myriad of other settings that make up human lives, and also share a fidelity to basic constitutional legal norms that can inform how we respond to pandemics in ways that allow safer returns.This Article identifies four constitutional principles to shape pandemic policies and enable them to garner broader public acceptance: substantive and procedural rationality, respect for fundamental liberties, equal treatment of similarly situated persons and entities, and sufficient government flexibility to enable officials to nimbly and effectively address emergencies that threaten life itself. Recognition of these norms is essential for all institutions, public and private, because reopening safely can occur only through the cooperation of private individuals. They will cooperate only if they have adequate confidence in the ability of institutions to protect their safety, liberty, and equality.
Investigation of Imbalanced Big Data Set Classification: Clustering Minority Samples Over Sampling Technique

Most of the real-world data sets exhibit a skewed scenario of data distribution in contrast to the well-established data sets. The total number of instances of a particular class extremely surpasses the count of other classes. This uneven dispersal of classes leads to a state of imbalance data sets posing an extreme difficulty for learning procedures. Additionally, due to its intrinsic complex data features, analyzing such imbalanced data sets has setup an avenue for focused researchers. Imbalanced class distribution is effectively handled with over sampling of minority class data which is usually independent of the classifiers. A over sampling technique: Clustering minority samples over sampling technique (CMSOT) is proposed to enhance the classification of imbalanced data sets. The projected technique is implemented on Apache Hadoop under mapreduce environment. The data sets are mainly encompassed from the UCI repository. The effect of True Positive rates justifying the imbalance ratio including the examination of improved classification from the generated pool is studied. The achieved experimental results along with its corresponding statistical analysis of over sampled data sets clearly mark the supremacy of the planned technique to the selected benchmarking techniques.
A Comparative Study of Classification Techniques in Context of Microblogs Posted During Natural Disaster

Microblogs generally contribute to statements that are made in public by the users. Tweets made on the Twitter platform fall in the microblog category. Microblogging sites have become important source in disaster events. In this paper, we compare various algorithms to study the effectiveness of retrieval and classification of tweets that were collected during disasters. The overall goal is to identify the relief work and retrieve it efficiently from the microblog tweets. The evaluation metrics that were used are precision, recall and F-score. We have observed that support vector machine (SVM) has the highest accuracy in classification of tweets based on pre-defined retrieval criteria.
SI: Chalmers on Virtual Reality Introduction

Abstract In June 2016, David Chalmers delivered the Petrus Hispanus Lectures at the LanCog research group, University of Lisbon, on the subject of objects, properties, and perception in virtual reality environments. The paper resulting from these lectures was subsequently published in Disputatio as “The Virtual and the Real” (vol. IX, 2017, No. 46, pp. 309–52). In it, Chalmers defends virtual realism , according to which virtual objects are bona fide digital objects with virtual counterparts of perceptible properties such as colour and shape, and perception in virtual reality environments is typically veridical rather than illusory. This special issue collects responses to Chalmers due to Claus Beisbart, Jesper Juul, Peter Ludlow, Neil McDonnell and Nathan Wildman, Alyssa Ney, Eric Schwitzgebel, and Marc Silcox; together with a detailed response by Chalmers to each paper. You can read the target article (Chalmers 2017, “The Virtual and the Real”) under discussion in this Special Issue here: https://doi.org/10.1515/disp-2017-0009
Impact of bookshelf locations using eye-tracking methodology

Purpose This study aimed to understand better the user gaze behavior on bookshelves using eye-tracking technology. Design/methodology/approach An eye-tracking experiment in a public library with 11 participants was performed. The impact of vertical shelf location of books on the number of times the books are looked at, the impact of horizontal location and the relationship between user behavior and location impact were examined by the findings. Findings The results showed that the vertical location of books has a significant impact on the number of times the books are looked at. More than 80% of the time spent looking at bookshelves was spent on books on the top to fourth rows. It was also revealed that the horizontal location of books has a little impact. Books located on the left side of shelves will be looked at significantly more often than those on the right side. No significant relationships between type of user behaviors and location impact were observed. Originality/value The study explored the impact of the vertical location of books on time spent looking at bookshelves using eye-tracking methodology. Few published studies do such experiments to address user gaze behavior on bookshelves. The study explored that the vertical location of books has a great impact, and horizontal location has a little impact on user gaze behavior.
An Example-based Tone Mapping Algorithm for Monochrome Image

We propose an example-based tone mapping algorithm for monochrome image. Specifically, the distribution of pixel intensity of the example image is modeled with Gaussian mixture model (GMM) whose centroids are initialized by the source image. With GMM centriods iteratively shifted by expectation-maximization (EM) optimization, tone of the source image gradually approximates the example image. Experiment with qualitative results validate the effectiveness of our method.
Generalized Net Model of an Active Elbow Orthosis Prototype

This paper presents a novel approach for describing the functioning of an active elbow orthosis with the use of generalized nets modeling. The so proposed model will permit the development of user-oriented control of sEMG- powered elbow orthosis. We propose an abstract model based on the “on-off” myoelectric control, appropriate for maximum two degrees of freedom in the elbow joint.
Evaluation of heavy metal content of salts between Eskıkışla and Ocakbaşı (Kırıkkale) villages

Salt, which is the main nutrient, is a very important raw material in the life of living organisms and industry. Salt production and consumption have improved and increased due to technological developments and industrialization. Salt has been used in the world and in our country since very ancient times. It is used in many fields, especially in the chemical industry, metallurgy, textile, medicine, and agriculture. In addition to sea, lake and spring salts, Turkey has very rich rock salt reserves. The Neogene aged Çankırı-Çorum Basin is one of the important basins where evaporitic formations are observed in the Central Anatolia region. Chemical analyses were carried out to determine the amount of heavy metal in salt samples taken from Oligocene aged units observed in the area between Ocabaşı and Eskikışla springs (Delice) in the Çankırı-Çorum basin. SEM-EDX, XRF and ICP-OES devices were used to determine the geochemical properties and quantities of heavy elements. According to the results of XRF, Na % ( 33.70-38.30), Cl %(52.10 - 57.70) SO3 %(0.75-1.93), Al2O3 %(0.90-1.93), CaO %(0.58-2.69), MgO %(0.40-1.41) Fe2O3 % (0.18-0.64), SiO2 %(1.75-4.95), SrO, % (&amp;lt;0.010), BaO % (&amp;lt;0.010), Cr2O3 %(&amp;lt;0.010), K2O %(0.008-0.25), MnO %(&amp;lt;0.010) results are found. In the determination of heavy metals made with ICP-OES, it was determined that the heavy metals (Hg, As, Pb, Cd) published in the Turkish food codex salt communiqué were below the limit values.
Studying the Effect of Digital Stain Separation of Histopathology Images on Image Search Performance

Due to recent advances in technology, digitized histopathology images are now widely available for both clinical and research purposes. Accordingly, research into computerized image analysis algorithms for digital histopathology images has been progressing rapidly. In this work, we focus on image retrieval for digital histopathology images. Image retrieval algorithms can be used to find similar images and can assist pathologists in making quick and accurate diagnoses. Histopathology images are typically stained with dyes to highlight features of the tissue, and as such, an image analysis algorithm for histopathology should be able to process colour images and determine relevant information from the stain colours present. In this study, we are interested in the effect that stain separation into their individual stain components has on image search performance. To this end, we implement a basic k-nearest neighbours (kNN) search algorithm on histopathology images from two publicly available data sets (IDC and BreakHis) which are: a) converted to greyscale, b) digitally stain-separated and c) the original RGB colour images. The results of this study show that using H&E separated images yields search accuracies within one or two percent of those obtained with original RGB images, and that superior performance is observed using the H&E images in most scenarios we tested.
2019 IEEE Scientific Visualization Contest Winner: Visual Analysis of Structure Formation in Cosmic Evolution

Simulations of cosmic evolution are a means to explain the formation of the universe as we see it today. The resulting data of such simulations comprise numerous physical quantities, which turns their analysis into a complex task. Here, we analyze such high-dimensional and time-varying particle data using various visualization techniques from the fields of particle visualization, flow visualization, volume visualization, and information visualization. Our approach employs specialized filters to extract and highlight the development of so-called active galactic nuclei and filament structures formed by the particles. Additionally, we calculate X-ray emission of the evolving structures in a preprocessing step to complement visual analysis. Our approach is integrated into a single visual analytics framework to allow for analysis of star formation at interactive frame rates. Finally, we lay out the methodological aspects of our work that led to success at the 2019 IEEE SciVis Contest.
Virtual Reality Ethics

In this chapter, there is an emphasis on describing some of the ethical concerns that may arise from research, clinical applications, and even personal use of virtual reality and related technologies. Throughout, there will be attempts to offer straightforward recommendations for optimal outcomes and minimal risks.