Reviewerly/exHarmony huggingface dataset:
Hybrid self-calibration method for reference surface elimination in subaperture stitching interferometry

Subaperture stitching interferometry (SSI) is an essential method for the map testing of large-aperture optical components. The surface map of a reference surface is a typical error source. In this study, we propose a hybrid self-calibration method to eliminate the reference surface error in SSI by combining the modified shift-rotation method and the maximum likelihood method. The traditional shift-rotation method is a general full-aperture absolute interferometric measurement that can retain localized irregularities. The shift-rotation operations are leveraged to generate a couple of subapertures covering the surface under test, whereby a ring of subapertures and a central subaperture are acquired by rotations and a lateral shift, respectively. The modified shift-rotation method is proposed to obtain the rotationally asymmetric components of the test surface in the ring of subapertures. The same components within the central subaperture are retrieved using the maximum likelihood method. Then, the rotationally symmetric components of the test surface are acquired using the least squares method, utilizing the measured data before and after the shift. Reference surface maps are sufficiently eliminated from the measured data. High-frequency components of the test surface are also retained, which engender high-accuracy SSI. Simulations are conducted to verify the proposed method. The positioning errors of the proposed method are analysed and discussed. Subaperture testing experiments of a 100-mm aperture flat are performed and compared with full-aperture absolute measurement results. The stitched errors with 0.018 λ PV and 0.003 λ RMS are obtained.
Face and Eye Detection for Interpreting Malpractices in Examination Hall

Abstract: One of the most difficult problems in computer vision is detecting faces and eyes. The purpose of this work is to give a review of the available literature on face and eye detection, as well as assessment of gaze. With the growing popularity of systems based on face and eye detection in a range of disciplines in recent years, academia and industry have paid close attention to this topic. Face and eye identification has been the subject of numerous investigations. Face and eye detection systems have made significant process despite numerous challenges such as varying illumination conditions, wearing glasses, having facial hair or moustache on the face, and varying orientation poses or occlusion of the face. We categorize face detection models and look at basic face detection methods in this paper. We categorize face detection models and look at basic face detection methos in this paper. Then we’ll go through eye detection and estimation techniques. Keywords: Image Processing, Face Detection, Eye Detection, Gaze Estimation
Operation Method for Using Hand Position Information by QZSS to Manipulate Display Device

This paper describes a method for operating a display device in which a straight line connecting the shoulder and hand of a user is extended to a display device via the usage of the "Michibiki" Quasi-Zenith Satellite System (QZSS) and a two-frequency-band Real Time Kinematics (RTK) module. The two-frequency-band RTK module is attached to the user&#x2019;s hand, and the module serves as the controller. A method is thereby proposed where a straight line connecting the two points of the shoulder and hand of the user is calculated so as to operate the display device. Our experiment has conducted swipe operations as horizontal movements and scroll operations as vertical movements. It was seen that the display device could be operated according to how the user&#x2019;s arm had moved. Therefore, it has been proven that the proposed method is effective because the positioning of the two points of the shoulder and hand of the user can be performed thereby allowing a display device to be operated with high accuracy.
Investigating the efficiency of marginalising over discrete parameters in Bayesian computations

Bayesian analysis methods often use some form of iterative simulation such as Monte Carlo computation. Models that involve discrete variables can sometime pose a challenge, either because the methods used do not support such variables (e.g. Hamiltonian Monte Carlo) or because the presence of such variables can slow down the computation. A common workaround is to marginalise the discrete variables out of the model. While it is reasonable to expect that such marginalisation would also lead to more time-efficient computations, to our knowledge this has not been demonstrated beyond a few specialised models. We explored the impact of marginalisation on the computational efficiency for a few simple statistical models. Specifically, we considered two- and three-component Gaussian mixture models, and also the Dawid-Skene model for categorical ratings. We explored each with two software implementations of Markov chain Monte Carlo techniques: JAGS and Stan. We directly compared marginalised and non-marginalised versions of the same model using the samplers on the same software. Our results show that marginalisation on its own does not necessarily boost performance. Nevertheless, the best performance was usually achieved with Stan, which requires marginalisation. We conclude that there is no simple answer to whether or not marginalisation is helpful. It is not necessarily the case that, when turned 'on', this technique can be assured to provide computational benefit independent of other factors, nor is it likely to be the model component that has the largest impact on computational efficiency.
Leveraging Block Chain for Ensuring Trust in IoT in Health Care

Internet of Things (IoT) devices has completely new challenges regarding security and privacy. Blockchain technology could be a great to mitigate challenges of data security and privacy relay in the IoT. Crypto currency networks like Bit coin, can prove to be required towards understanding concept of decentralized, security and Leveraging of blockchain for privacy preserving. Differential privacy is a mathematical technique of adding a controlled amount of randomized noise to a dataset to prevent anyone from getting information about individuals in the dataset. The added randomized noise is in controlled manner. Therefore, the resultant dataset is still accurate enough to generate aggregate output while maintaining the privacy of individual participants. As Block chain is a peer-to-peer distributed ledger, it is an optimal way for preventing identity, monitoring, non-repudiation and providing tracking in IoT, so due to these aspects we can explore future research challenges to preserve privacy in blockchain.
English Language Teaching Curriculum and Material Production: Comprehensive Q&amp;amp;A

Artikel ini menyajikan bahan seputar English Language Teaching Curriculum and Material Production: Comprehensive Q&amp;amp;A yang di rangkum dari beberapa sumber seperti: Brown, James Dean. (1995). The Elements of Language Curriculum: A Systematic Approach to Program Development. Massachusetts: Heinle &amp;amp; Heinle Publisher.Graves, Kathleen. (2008) The Language Curriculum, in Language Teaching Journal, pp. 147—181. Richard, Jack C. &amp;amp; Theodore S. Rodgers. 1986. Approaches and Methods in Language Teaching. Cambridge: Cambridge University Press.
Compositional Data Analysis (CoDA) of Clinopyroxene from Abyssal Peridotites

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at G-Cubed. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]Compositional Data Analysis (CoDA) of Clinopyroxene from Abyssal PeridotitesAuthorsIkuyaNishioiDKeitaItanoiDPedroWatertonAkihiroTamura HasebeKristofferSzilasTomoakiMorishitaSee all authors Ikuya NishioiDCorresponding Author• Submitting AuthorKanazawa UniversityiDhttps://orcid.org/0000-0003-2889-6497view email addressThe email was not providedcopy email addressKeita ItanoiDAkita UniversityiDhttps://orcid.org/0000-0003-2382-8698view email addressThe email was not providedcopy email addressPedro WatertonUniversity of Copenhagenview email addressThe email was not providedcopy email addressAkihiro Tamura HasebeKanazawa Universityview email addressThe email was not providedcopy email addressKristoffer SzilasUniversity of Copenhagenview email addressThe email was not providedcopy email addressTomoaki MorishitaKanazawa Universityview email addressThe email was not providedcopy email address
IMAGE SENTIMENTAL ANALYSIS: AN OVERVIEW

Visual content, such as photographs and video, contains not only objects, locations, and events, but also emotional and sentimental clues. On social networking sites, images are the simplest way for people to communicate their emotions. Images and videos are increasingly being used by social media users to express their ideas and share their experiences. Sentiment analysis of such large-scale visual content can aid in better extracting user sentiments toward events or themes, such as those in image tweets, so that sentiment prediction from visual content can be used in conjunction with sentiment analysis of written content. Despite the fact that this topic is relatively new, a wide range of strategies for various data sources and challenges have been created, resulting in a substantial body of study. This paper introduces the area of Image Sentiment Analysis and examines the issues that it raises. A description of new obstacles is also included, as well as an assessment of progress toward more sophisticated systems and related practical applications, as well as a summary of the studys findings.
Neural Processes with Stochastic Attention: Paying more attention to the context dataset

Neural processes (NPs) aim to stochastically complete unseen data points based on a given context dataset. NPs essentially leverage a given dataset as a context representation to derive a suitable identifier for a novel task. To improve the prediction accuracy, many variants of NPs have investigated context embedding approaches that generally design novel network architectures and aggregation functions satisfying permutation invariant. In this work, we propose a stochastic attention mechanism for NPs to capture appropriate context information. From the perspective of information theory, we demonstrate that the proposed method encourages context embedding to be differentiated from a target dataset, allowing NPs to consider features in a target dataset and context embedding independently. We observe that the proposed method can appropriately capture context embedding even under noisy data sets and restricted task distributions, where typical NPs suffer from a lack of context embeddings. We empirically show that our approach substantially outperforms conventional NPs in various domains through 1D regression, predator-prey model, and image completion. Moreover, the proposed method is also validated by MovieLens-10k dataset, a real-world problem.
A STUDY ON THE EVALUATION OF IDIOM USAGE IN INSTAGRAM AS ONE OF THE SOCIAL MEDIA TOOLS

Social media is a mass communication tool that emerged with Web 2.0 technology and allows users to not only be buyers but also produce content. Instagram is the second most preferred social media tool by users. As it offers good options for photo and video editing, enables users to interact with each other easily, acts as a bridge by including the features of other social media tools, the fact that the average age of users is young, and its accessibility is facilitated by the widespread use of mobile phones, has made Instagram one of the most preferred social media tools by secondary school age group. The aim of this study is to detect the idioms that are used in Instagram posts. In this research, 84 contents from 14 different categories that are followed by the students are analyzed. In the study, which has a descriptive nature in the screening model, the contents are evaluated with the systematic analysis approach. In the end of the research, we detected 95 idioms from 50 contents out of 84. While the usage of 45 idioms out of 95 is true, the other 50 idioms are used wrong with syntax errors and with changes that will break the pattern of the idiom. Key Words: Social Media, Instagram, Idioms
Elicitation, Computational Representation, and Analysis of Mission and System Requirements

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Strategies for evaluating the impact of mission requirements on the design of mission-specific vehicles are needed to enable project managers to assess potential benefits and associated costs of changes in requirements. Top-level requirements that cause significant cascaded difficulties on lower-level requirements should be identified and presented to decision-makers. This paper aims to introduce formal methods and computational tools to enable the analysis and allocation of mission requirements. Initial results for three interrelated research problems are discussed: (1) understanding the current practices of interrelationships between requirements. the requirements elicitation and change management processes using a case study approach; (2) requirement elicitation using gamification strategies; and (3) computational representation of the technical requirements and identification The case study approach involves interviewing the stakeholders that participate in the requirements generation process to collect data on the current practices of requirements elicitation. Systematic requirements generation strategies, change management processes, limitations, and areas for improvement are the outcomes of this study. A gamification strategy is also deployed to study requirements elicitation and change management processes by incentivizing the users based on their performance on a set of metrics. Two surveys, one with and the other without gamification, are designed to study the impact of gamification methods on requirements elicitation. Lastly, text analytics tools are developed to extract requirements from textual descriptions and identify their inter-relationships to be stored in the requirement graph representation.&lt;/div&gt;&lt;/div&gt;
Development of a methodological approach to determine regression equations in the study of the technology for manufacturing tablets based on quercetin

When developing the technology of tablets and tablet masses one of the tasks is to determine the amounts of excipients required to obtain pharmaco-technological quality indicators that meet the requirements of the State Pharmacopoeiaof Ukraine (SPhU). Aim. To develop an algorithm for determining the type of three-factor mathematical models with dependent variables. Materials and methods. The study object was experimental observations of the quantitative effect of excipients in the tablet composition based on a solid dispersion of quercetin on the pharmacopeial characteristics of this dosage form, in particular on its flowability. The experimental data were processed by the planned experiment using Mathcad 15 and MS Excel software according to the algorithm proposed. Results and discussion. It has been found that the identification of mathematical models in pharmaceutical studies with three dependent factors, which total value is determined by the quantitative composition of the dosage formand fixed at a certain level, is difficult to perform due to the difficulty of interpreting the multiple regression parameters as characteristics of factors in isolation through their correlability. It has been proven that the replacement of variablesleads to the determination of a mathematical model that does not reveal the mechanism of the factors’ action and is a static description of their overall impact on the indicator studied. Conclusions. As a result of the research conducted, regression equations were found to determine the effect of the amount of these excipients on the tablet flowability. It has been found that the most influential role in determining the target in the factor space studied is played by the interaction of factors. The algorithm for determining the mathematical description of the dependence with three variables has been proposed. Based on the fact that the research is conditioned by strict conditions in the quantitative composition, the chosen mathematical model of the dependence of the quadratic equation with two factors, for which there are limitations, has no correlation. The model determined is characterized by the possibility of providing the graphical interpretation and simplification of analysis and can be used for forecasting and optimization.
Evaluation of Environmental Geochemistry of Trace Metal Pollutant in Sediments of Outlet Jeneberang River, Indonesia

The Jeneberang River flows between settlements, rice fields, traditional ports which are located in the southernmost part of Makassar. Regional development and increasing population are anthropogenic as a source of heavy metal input to rivers, and require a sustainable geochemical study of the environment. Study objectives, concentration and spatial distribution, use of sediment samples for grain size and Coupled Plasma-Osiloscope Emission Spectroscopy (ICP–OES) method for trace elements. The average yield of the seven river sediment samples was (Cr)149 mg kg-¹ (Mn)1388.14 mg kg-¹, (Cd)0.74 mg kg-¹, (Cu)54.71 mg kg-¹, (Zn)130.28 mg kg- , (Pb)3675 mg kg-1.&#x0D; The conclusion on the grain size of the sand, it is known that the order is dominated by concentration: Mn&gt;Zn&gt;Cr&gt;Pb=Cu then changes to the grain size of silt clay: Mn&gt;Cr&gt;Zn&gt;Cu&gt;Pb, showing indications of migration, exchange phase and heavy metal enrichment. The order of heavy metal contamination uses the Igeo average value: Cd&gt;Cr=Pb&gt;Mn&gt;Cu&gt;Zn is class 1, namely 0 &lt; Igeo &lt; 1 = not polluted to moderately polluted, and the order of heavy metal enrichment uses EF: Cu (0.64), Mn (0.58), Pb (0.56), Zn (0.73), Cd (0.41), Cr (0.55), generally EF &lt; 2 is deficiency to minimal enrichment. It seems that the heavy metals in the minimum contamination and enrichment criteria which are strengthened by statistical analysis of correlation factors and multiple scatter are Pb and Zn.
Lightning Protection Safety Risk Assessment Method for Key Units of Meteorological Disaster Prevention

Based on the key units of meteorological disaster prevention in Shanghai as a specific object, the research on lightning protection safety risk assessment method is carried out. By analyzing the attribute characteristics of key units of meteorological disaster prevention, combined with three important factors such as lightning risk factor, disaster bearing body exposure and disaster prevention ability, the lightning protection safety risk assessment index system and calculation model are established, The key meteorological disaster prevention units are quantitatively evaluated and the risk grade classification standard is formulated, so as to dynamically determine the lightning disaster risk grade of key units.
Estimating Child’s Participation to Class Activity from Teaching Scene Image Analysis

Evidence-based education is important for personalizing education and improving the quality of learning. However, it is difficult to collect evidence for preschool and early elementary school-aged children. In this study, we propose a method to estimate children's participation in classroom activities by collecting children's gazes from video images in the classroom.
Virtually Real

Due to the rapid pace of digitalization, Virtual Production (VP) in film is gaining importance. With this gamified production process, live-action and computer graphics can be combined in real-time while filming on set. This paper focuses on an interdisciplinary research project that investigates the effects of VP on visual aesthetics, on the changing workflows of filmmakers and actors, and on the perception of a cinema audience. To systematically compare conventional filmmaking with new virtual forms of production, two short feature films were shot both conventionally (in real locations) and virtually (in the digitally scanned versions of these locations). The filmmakers aspired to keep all parameters of the production the same so that wherever possible, the only differences would be in terms of spatial representation. The process of VP included shooting with green-screen and pre-visualization based on real-time image rendering in a moderate quality. The high-resolution variants, however, were still processed in post-production. The methodology comprised a combination of qualitative, practice-based research and quantitative, empirical approaches, in the tradition of mixed methods. As VP continues to develop, green-screens are being replaced by large arrays of LED-displays, as in, for example, The Mandalorian. The present study shows that in the first phase of VP, in which green-screen procedures are still predominant, composition artifacts occur mainly in the context of moderate production resources and are still measurable in terms of image quality.
3D Vehicle Surround View Algorithm for Embedded Platform

Abstract Although surround view systems have been widely used in advanced automotive, processing speed is still a bottleneck for the embedded system. This paper presents a 3D surround-view algorithm suitable for embedded platforms. Using methods such as extracting regions of interest (ROI) and HSV color screening to improve the efficiency of image registration, there is no need to manually select feature points, which reduces the difficulty of operation. In addition, we designed a bowl-shaped three-dimensional model to be used as a projection surface. In terms of optimization, methods such as look-up table (LUT) and hardware acceleration significantly reduce computational time.
Seeing Makes the Difference: Augmented Reality in the OR

Although many surgeries, including spinal procedures, have been much improved with robotics in recent years, the additional technology has created associated issues with its use in the space constraints of the operating room (OR). This is especially true with monitors and their small screen sizes, which make it difficult for surgeons to see details during procedures. Solving such problems and finding the optimal position for viewing as well as ensuring integration with current technology were primary objectives in the development of iSight, a wireless augmented reality (AR) system designed by Dr. Chetan K. Patel, MD, in collaboration with startup Altair Innovations [1]. Patel is an orthopedic spine surgeon and executive medical director for spine surgery at AdventHealth Neuroscience Institute (Figure 1).
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