Reviewerly/exHarmony huggingface dataset:
Feature isolation and quantification of evolving datasets

Identifying and isolating features is an important part of visualization and a crucial step for the analysis and understanding of large time-dependent data sets (either from observation or simulation). In this proposal, we address these concerns, namely the investigation and implementation of basic 2D and 3D feature based methods to enhance current visualization techniques and provide the building blocks for automatic feature recognition, tracking, and correlation. These methods incorporate ideas from scientific visualization, computer vision, image processing, and mathematical morphology. Our focus is in the area of fluid dynamics, and we show the applicability of these methods to the quantification and tracking of three-dimensional vortex and turbulence bursts.
Improved chopper circuit uses parallel transistors

Parallel transistor chopper circuit operates with one transistor in the forward mode and the other in the inverse mode. By using this method, it acts as a single, symmetrical, bidirectional transistor, and reduces and stabilizes the offset voltage.
The Psychology of Robotization of Work: Four Fantasies of Technology

It was not long ago that technology and robotization were not of any interest to work psychologists or organizational scholars. The impact of technology on people and organizations was not something worth researching, and there were more pressing issues, such as the aging workforce, engagement, or work-life balance. However, this has changed dramatically during the last years. In this paper, I discuss four main fantasies that are present in our discourses around technology and work, and debunk these myths.
Research and technology: Report, FY 1982

Sensor systems, data analysis programs, agriculture and resources inventory survey through aerospace remote sensing (AgRISTARS), applied research and data analysis, joint research project, and testing and evaluation are reported.
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xcrun: error: invalid active developer path (/library/developer/commandlinetools), missing xcrun at: ...
Application of mixed reality technology in endoscopic ear surgery

Mixed reality (MR) is a further development of virtual reality technology. This technology builds an interactive feedback information loop between the virtual world, the real world and users by introducing real scene information into the virtual environment to enhance the reality of user experience. This study explores the application and value of MR technology in endoscopic surgery. In this study, patients with middle ear cholesteatoma who are to undergo endoscopic surgery were selected. After obtaining the informed consent of the patients, temporal bone CT is used to obtain clinical data information. The 3D model was built by online editing platform. When viewing the 3D digital model in the real environment of VR helmet, the model can also be moved, rotated, scaled and measured. Through MR technology, doctors can fully observe the details of the lesion, deeply excavate the image information, distinguish the relationship between the facial nerve, auditory ossicular chain and cholesteatoma lesion, and then work out a safer and more reasonable surgical plan. The application of MR technology in endoscopic surgery can build effectively communication between doctors and patients, and formulate a reasonable operation plan through ear canal approach, it can also help young doctors train their surgical skills.Key words: mixed reality; Endoscopic; Surgical Procedures, Operative
Library Guides: Activities for Kids during COVID-19 Closings: Miscellaneous

Here are some possible activities to do with your kids at home while schools are cancelled.
To have or not to have? Open discussion about library publishing advisory boards

Some library publishing operations make use of a Publications Advisory Board to oversee the process, provide insight and input, and to approve publication proposals submitted to the program. We will share different perspectives on Advisory Boards and their roles in library publishing programs, culminating in a shared document for the use of library publishing programs that have, or are considering the creation of, a Publications Advisory Board. Topics discussed will include the general mission and activities of the Board, the composition of a Board, how to facilitate engagement with Board members, and the benefits and drawbacks of having a Publications Advisory Board. Audience input will be gathered regarding the document, and particularly sought from audience members who have been considering implementing a Publications Advisory Board, or who have decided not to pursue a Board.
HySamBS: A Hybrid Sample-based Background Subtraction Method

Background subtraction technique is the foundation of video analysis applications. Although many background subtraction methods have been proposed, it is still challenging due to the various nature of video scenes. In this paper, we propose an improved method named HySamBS based on the traditional Self-Balanced Sensitivity Segmenter. This method mainly consists of three framework: 1) modified pixel-wise adaptive feedback, 2) region-wise refinement of segmentation results, 3) frame-wise camera motion compensation. The improved feedback mechanism limits the excessive increasing of segmentation threshold. As the traditional sample-based methods are inefficient for detecting intermittent motion objects, the proposed method extra estimates the initialized reference background image via existent background samples. “Ghosts” suppression can be accelerated with identifying whether motion objects exist in the reference background image. The cancellation of neighborhood diffusion prevents motion objects from being absorbed into background samples. In addition, the effect of camera motion on foreground segmentation is further resisted by feature points matching. Finally, comprehensive evaluation results on the ChangeDetection.net dataset indicate proposed method can adapted to diverse challenging videos scenes, and the overall evaluation metric is competitive with state-of-the-art sample-based methods. The complete source code is publicly available at https://github.com/HuangLian126/HySamBS .
Gigapixel Images Connect Sports Teams with Fans

Technology developed at Ames Research Center to take high-resolution imagery on Mars is now being used in baseball stadiums across the country. New York City-based Major League Baseball Advanced Media LP customized the platform to accommodate in-game shots that capture nearly the whole stadium. Fans navigate the photos online and tag themselves and their friends using social media tools.
Image Deblurring and Localization for Disaster Response and Humanitarian Assistance

This paper focuses on enhancing videos taken from a moving camera capable of capturing videos at any speed and in multiple directions. The second objective is to locate humans in the video to be able to conduct surveillance in case of disasters, without risking human lives. Most reported work for disaster management deals with satellite images. Indoor disaster management using image processing has been less explored. This work addresses applications involving disasters like a building on fire, wherein it will be useful to send a camera in to scan the rooms and locate people if present. This allows rescue teams/robots to make informed decisions and act accordingly. In this paper, the working of a 3600 camera is emulated using multiple ordinary cameras and the location of people is estimated using image processing techniques without Internet connectivity. The challenge is to train the model with a small dataset and accurately determine the location without any hardware setup (like sensors). Combination of Blind Deconvolution followed by Lucy-Richardson method gave optimal results. The frames were enhanced by de-noising using median filter, sharpening using unsharp mask and contrast enhancement using histogram equalization in order to make the object detection more accurate. Humans in the video were identified using either body or facial detection. Their locations were estimated with respect to a reference point and were quantified by predicting distance, angle and direction. In order to increase the accuracy, a fine-tuning mechanism has been proposed for location estimation using a non-linear curve, which gave acceptable accuracy within a range of 0.01m.
CHLO-Packing-dataset

These have 3 directories (i) datasets where the data are, (ii) Solutions (where the solutions are provided) and Readme.txt as a read me file. Note each directory has many files.
From the Experience of Using Online Platforms in Teaching a Foreign Language in Economic University

The article is devoted to some options of the usage of e-learning teaching methods in Economic University. Modern approaches with information technology involvement were studied. The pedagogical experience of the application of open-source learning platforms Moodle, Zoom, Platonus while foreign languages teaching is paid attention to.
White Library: FreeSources: Virtual Tours

Looking for free (or really inexpensive) resources during the COVID19 crisis? Look no further!
Estimation and Control of Nodes in an Abstract Space

It is very common to deploy multi-mobile robots in swarm robotic applications that is targeted for co-ordinated tasks that needs specific formations. The coordination and hence the formations require a good framework of communication, positioning, and controls. Many proposed architectures for indoor systems depend on a camera or another kind of beaconing system for positioning the robots. The paper describes a method using a relative coordinate system without the need for external sensors and is applicable to indoor systems. The initial setup needs the designated global master node and all other nodes to be placed in pre-determined form so that the initial relative distances between the global master and other nodes are known. At the start-up of the system, the configured global master robot node scans and builds the list of all available robot nodes. The global master node will assign the roles of leaders and followers including the global master node itself so that the controls will be distributed. The formation controls are achieved by limiting the communication of the local master to the slaves. Each local master also has the role of a slave to propagate the position with master being the head of the swarm in this chain. The formulated system has been prototyped with generic flow charts and the performance measured show the results to indicate that they can be well utilised in real time system projects.
Statistical effective and ineffective Fault Attacks against Advanced Encryption Standard implementations

Along with technological progress, information security has become a serious issue that must be taken into account when sensitive and personal data happens to be exposed to a threatening environment. Embedded devices are an example of targets whose security can be violated by an attacker in order to find a secret variable of interest. To provide an adequate protection against any possible leakage, cryptographic algorithms can be integrated into electronic devices in order to help reinforcing data protection against the different possible cryptanalysis attacks. The standard algorithms are mostly considered as secure from a purely mathematical point of view. However, the implementation of said algorithms can contain vulnerabilities that can be exploited to break the algorithm security. Fault attacks are a well-known example of active cryptanalysis implementation attacks that rely on the voluntary introduction of a perturbation during the execution of a cryptographic algorithm in order to later exploit the created errors. In particular, this work details one specific class of fault attacks: Statistical Ineffective Fault Attacks (SIFA). This class of attacks was recently published in the international Conference on Cryptographic Hardware and Embedded Systems 2018 (CHES) and relies on a statistical analysis approach in order to break the cryptographic algorithm. In the related-field literature, such an approach was already presented with another class of fault injection attacks that can be therefore considered as SIFA predecessor: Statistical Fault Attacks (SFA) . Both SFA and SIFA strongly rely on the deployment of statistical estimators, even if in a slightly different way, to successfully deploy the attack. The most important advantage about SIFA is that they rely on the ineffective results of faulted computations and therefore provide some significant improvements that overcome some of the limitations of a general fault induction attack. This work focuses on the working principle of both SIFA and SFA against the Advanced Encryption Standard (AES) , the current worldwide used standard for electronic data encryption established by the american National Institute of Standards and Technology (NIST) in 2001. The theoretical aspects linked to the two attacks are supported by means of software simulations and real implementations. In particular, the mentioned attacks have been applied in a practical context, by deploying the targeted attack on a Field Programmable Gate Array (FPGA) device. Specifically, the attack has been physically implemented according to the voltage glitch technique, which consists in a sudden variation of the line voltage of the device, in order to introduce a perturbation inside the AES algorithm computation.
Putting ASP.NET Core in Context

ASP.NET Core is Microsoft’s web development platform. The original ASP.NET was introduced in 2002, and it has been through several reinventions and reincarnations to become ASP.NET Core 3, which is the topic of this book.
Organization Features of the Information System for Admission of Applicants at Large Universities

The article addresses the problem of setting up a unified information space for the work of the admission office at a large university in which more than 3000 people are enrolled for the freshman year. The use of information systems is the only tool using which it is possible to store and process a significant amount of miscellaneous personal data of applicants and to make decisions in semi-automatic mode within a short period of time as specified by the current legislation. The problem of arranging automated acceptance of the documents of applicants from the submission of documents to the issuance of enrollment orders is considered taking as an example the Federal Budgetary Education Institution the National Research University Moscow Power Engineering Institute (NRU MPEI). The basic modular structure of the NRU MPEI admission office information system is described, and the composition of its modules is given. The features of the NRU MPEI admission office information system are demonstrated. Owing to the functionality of an applicant’s personal account incorporated in the information system, the applicants receive the necessary information in compliance with the standards and requirements of the current legislation in the field of personal data. In addition, owing to this functionality, the procedure of submitting the documents along with some related procedures are greatly simplified. The problem of information exchange between the NRU MPEI branches and the head higher school is analyzed, and methods for solving it are proposed. Versions of a distributed database, and exchange of data between local databases are described, and the method including changes in the database structure, which has been implemented at NRU MPEI, is described. Matters concerned with the need of transferring data to the federal information system of the state final attestation and admission in accordance with the current legislation are highlighted.
Anatolia College Libraries: Teaching & Learning Guide: Creating Teaching Video Tools

A guide on best practices on teaching & learning This is a simple Guide that displays free screencasting tools and helps you with the build from scratch your own Video Tutorials
Fourth Annual Earth Resources Program Review. Volume 2: University Programs

University research in data processing techniques to extract information on earth resources from remotely sensed areas - conference
StationRank: Aggregate dynamics of the Swiss railway

Increasing availability and quality of actual, as opposed to scheduled, open transport data offers new possibilities for capturing the spatiotemporal dynamics of the railway and other networks of social infrastructure. One way to describe such complex phenomena is in terms of stochastic processes. At its core, a stochastic model is domain-agnostic and algorithms discussed here have been successfully used in other applications, including Google's PageRank citation ranking. Our key assumption is that train routes constitute meaningful sequences analogous to sentences of literary text. A corpus of routes is thus susceptible to the same analytic tool-set as a corpus of sentences. With our experiment in Switzerland, we introduce a method for building Markov Chains from aggregated daily streams of railway traffic data. The stationary distributions under normal and perturbed conditions are used to define systemic risk measures with non-evident,valuable information about railway infrastructure.
GSU Library Research Guides: Web Savvy -- General Guide: Welcome to Web Savvy

A multi-page tutorial on evaluating web sites, for beginners and those who think they know. This is the introduction page and table of contents for the Web Savvy tutorial.
Earth Resources: A continuing bibliography (issue 32)

This bibliography list 580 reports, articles and other documents introduced into the NASA scientific and technical information system. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis.
Subject and Course Guides: Online Learning Resources : Stable Links

Best practices to sharing library resources in online learning environments. How can I link to Library resources on a course site?
Using the Platform Features, Part 1

ASP.NET Core includes a set of built-in services and middleware components that provide features that are commonly required by web applications. In this chapter, I describe three of the most important and widely used features: application configuration, logging, and serving static content. In Chapter 16 , I continue to describe the platform features, focusing on the more advanced built-in services and middleware. Table 15-1 puts the chapter in context.
Practice of “Education for Social Implementation” to Human Resource Development for Innovation through Science and Technology

This paper shows practice and its educational effects of education for social implementation. This paper presents educational effects, focusing on 1) student growth from the perspective of efforts, 2) student growth from the perspective of evaluation in contest, and 3) the effect of extension of basic social skills by the PROG competency test. Education for social implementation is one of groundbreaking engineering design educations, in which students take advantage of each other’s strengths and co-create with users while solving actual problems. Finally, this paper describes the summary of effect and future works of education for social implementation.
Deep Convolution Q-Learning for emulation of human behavior patterns in gaming bots

Reinforcement learning is a branch of machine learning that attempts to maximize reward by taking a suitable action dependent on the situation. In the field of gaming, it has been demonstrated by letting the algorithm play the game as an automated bot and predicting possible outcomes for the moves it makes. While usually, this is beneficial to demonstrate the capabilities of machine learning, we attempt to replicate this work and to possibly emulate actual human behavior where mistakes are also taken into account. Instead of estimating only the future rewards, we also take into account failures in a particular situation and let the bot act accordingly in an attempt to replicate how a human would be playing the game, which is established through the usage of parallel & competing algorithms. This can prove to be useful especially in online gaming where a disconnection usually leaves a user frozen, quit from the lobby or in rare cases replaced by a generic bot, all scenarios which can prove to be disadvantageous in case of team-based games. We believe an algorithm that can temporarily replace the player until they reconnect to the lobby or the round is over can prove to be of great help in these scenarios or could also be used for practice by playing against these bots when they are able to match more lifelike movements rather than generic ones which have a defined skill cap. For this we make use of convolutional neural networks(CNNs) trained with Q-learning for achieving both reward and failure rates to use as training data as compared to conventional algorithms earlier that focused only on the rewards.
Review of Denoising Techniques for Noisy Partial Discharge Signals

Partial discharge (PD) can cause the dielectric strength to weaken and the high voltage system finally breakdown due to occurrences of PD. Therefore, partial discharge measurement gives a warming to the corrosion of the insulation. PD testing also act as an indicator of initial errors. However, there is a difficult and challenging task during PD measurements which is the PD signal always suffers from the strong coupling of exterior noise.In order to eliminate those external noise, various methods of de-noising of partial discharge signal will be reviewed, studied, analysed and evaluated in this paper. All the testing will be conducted by using MATLAB. A better de-noising technique will be selected and implemented based on the current stage of study.Based on the comparative studies, it seems that determining of threshold value for de-noising of PD signals is a difficult and challenging task to be solved. A thresholding procedure plays an important role in de-noising of noisy partial discharge. The selection of threshold coefficients through hard or soft threshold functions should be determined properly in order to achieve the goals which is fast computation speed and great robustness during de-noising process.In this study, four main conventional threshold selection rules based on wavelet transform will be evaluated to select the best threshold coefficient for de-noising purpose. For example, 'rigrsure', 'sqtwolog', 'heursure' and 'minimaxi'. Instead of wavelet transform, various techniques such as Singular Spectral Analysis (SSA), Morphological filter and Power spectral subtraction (PSS) will be implemented also. Same PD and noise model with high level of noise with SNR = –10 dB and low level of noise with SNR = 10 dB will be conducted to evaluate the performance of the proposed methods. PSSD method proved that it is more powerful compared to SSA, MF and existing wavelet-based techniques, it is observed that PSSD yields better MSE and higher SNR according to the denoised PD pulses even in high noise level.
LibGuides: Introduction to Comics for Adults: Where Should I Start?: Notable Characters and Series

The world of comic books can be intimidating. This guide outlines various notable works, databases, and other resources to help you feel more confident the next time you enter a comic book shop or graphic novel section of your local public library. Comic books that are well-known or currently popular