Reviewerly/exHarmony huggingface dataset:
A Confidence-based Iterative Solver of Depths and Surface Normals for Deep Multi-view Stereo

In this paper, we introduce a deep multi-view stereo (MVS) system that jointly predicts depths, surface normals and per-view confidence maps. The key to our approach is a novel solver that iteratively solves for per-view depth map and normal map by optimizing an energy potential based on the locally planar assumption. Specifically, the algorithm updates depth map by propagating from neighboring pixels with slanted planes, and updates normal map with local probabilistic plane fitting. Both two steps are monitored by a customized confidence map. This solver is not only effective as a post-processing tool for plane-based depth refinement and completion, but also differentiable such that it can be efficiently integrated into deep learning pipelines. Our multi-view stereo system employs multiple optimization steps of the solver over the initial prediction of depths and surface normals. The whole system can be trained end-to-end, decoupling the challenging problem of matching pixels within poorly textured regions from the cost-volume based neural network. Experimental results on ScanNet and RGB-D Scenes V2 demonstrate state-of-the-art performance of the proposed deep MVS system on multi-view depth estimation, with our proposed solver consistently improving the depth quality over both conventional and deep learning based MVS pipelines. Code is available at https://github.com/thuzhaowang/idn-solver.
A Shift in Our Thinking: Reframing Shared Research Resources as Investments in Education and Innovation, Not Subsidized Science

For many researchers, Shared Research Resources are often the most cost-effective means of using state-of-the-art (not to mention expensive) instrumentation. Along with access to the instruments themselves, Shared Research Resources also offer individualized training by highly qualified Shared Research Resource staff-again at deeply discounted costs compared to the operational costs of the facilities. Traditionally, this gap in revenue has been termed a subsidy. But, as with many words, connotation matters, and we posit that this language ought to be changed to reframe our thinking and impart the true impact of Shared Research Resources. We argue here that rather than a subsidy, the revenue gap is better described as an investment. Furthermore, investments of Shared Research Resources lead to positive externalities, including education and innovation.
Remote sensing mapping and 3D modelling of Petelovo Au-epithermal system, Panagyurishte ore district, Bulgaria

Remote sensing drone-based study combined with field mapping, XRD and XRF tests for mineral detection outlined advanced argillic, argillic and propylitic alteration domains within the Petelovo silica cap to demonstrate quick approach for mineral alteration mapping. Mineral alteration modelling by 3D Leapfrog Geo outlined zonal patterns around epithermal high-sulphidation Cu-Au mineralization could be employed as a pathfinder for gold enrichment.
INTERNET OF THINGS (IOT) APPLIED IN CONSTRUCTION INDUSTRY: A SYSTEMATIC REVIEW

The Internet of things (IoT) involves several internet-connected devices that interact with each other to learn and share information between humans and machines and between machines and machines, making the related processes more comprehensive, innovative, simple, and efficient. There are several applications of IoT in construction, such as using computational tools in structural design, georeferencing, construction management, and using technological tools in construction sites. Therefore, this article presents a systematic review of the most relevant studies from Industry 4.0 and the application of IoT in the construction industry to present the impacts these technologies can promote in construction. On this, the 4.0 technology implementation and their construction innovations can improve work conditions through innovative tools, machines, and devices, increasing productivity and reducing production costs. Therefore, drone operation is one of the most used construction technologies, mainly because the costs are low for construction companies and their owners. However, technologies such as BIM and robotics are widely used.
A Linguistic Study of Offensive Language in Online Communication Chatgroups

Since offensive language, words and expressions are widely used nowadays on the internet; the current paper is an attempt to discover and investigate offensive language that is used in one medium of electronic communication, which is “chatgroups”. The study focuses on analyzing and explaining offensive words and expressions found in chatgroups with their types and functions. The data of this study are a type of screenshots, (20) screenshots are randomly gathered from synchronous chatrooms. The analyses reveal different types of offensive language; these types are (vulgarity, insult, epithet, taboo, obscenity, and profanity). Besides, the functions of these offensive words and expressions are (body part, sexual, connotative, metaphoric, and expletive).
Factors Implanted in the Successful Implementation of Forensic Accounting: An Empirical Study on Academicians and Practitioners

This study aimed at exploring factors implanted in the successful implementation of forensic accounting emphasizing both organizational and people derived factors. Organizational factors were limited to information technology solutions and creative accounting practices, while people factor was related to knowledge, skills, and experience. Prior research was reviewed for two purposes. First, to lay the foundations of research theoretical framework and hypotheses development. Second, to develop the questionnaire of the study by which the required data were gathered. A sample of academicians and practitioners comprising 120 participants was purposively selected. A total of 107 responses were used in the statistical phase, which was carried out with IBM SPSS and AMOS. The results showed that information technology solutions, absence of creative accounting practices, forensic accounting education, forensic accounting training, and forensic accountants’ experiences were significant predictors of the successful implementation of forensic accounting. Based on the results, this study contributes to the literature of forensic accounting by providing evidence on organizational and human factors that affect the successful implementation of forensic accounting. In addition, the results offer insightful educational and managerial implications. Universities, organizations, and accounting firms are recommended to consider the suggested model in order to elevate their implanting of forensic accounting efforts to detect fraud crimes.
Freedom of Speech and Democracy

In recent years ‘freedom of speech’ has been hotly contested, at times weaponised in political debates. Policies of ‘no-platforming’ and at times strong reactions, even protests, against certain speech have led some to worry about what they call ‘cancel culture’. In addition to the explicit fight over freedom of speech seen, for example, in current feminist debates, the last 18 months have seen a rise in the popularity and presence of conspiracy theories, including theories about Covid vaccinations and the Covid pandemic. Mixed in with the so-called ‘anti-vaxxers’ are a medley of conspiracy theorists ranging from climate change deniers, supporters of ‘ethnic replacement conspiracy theories’ through to the astonishingly long-lived, antisemitic myths about child sacrifice and world domination. The spread of such conspiracy theories is problematic if they directly or indirectly cause harm. Anti-vaccination conspiracy theories are harmful if they facilitate the spread of a deadly disease, or if they spread misinformation and thereby vilify (marginalised) individuals or groups and undermine the trust necessary for peaceful coexistence and cooperation in democratic societies.&#x0D; However – while concern about such harms is important – freedom of speech is often regarded as such a basic right that any infringement has been considered harmful in itself. &#x0D; In this article I will look at two examples that pose challenges to freedom of speech and analyse them with reference to what I take to be the most plausible account of the grounds and scope of freedom of speech, a democratic defence of freedom of speech. Seeing freedom of speech as primarily grounded in democracy has important implications in situations when speech can be seen as harmful in a relevant sense and in consideration of what we can or should do about harmful speech. In the end I will suggest a possible way of weighing up value and dangers with respect to the cases and also in a broader sense.
An investigation of vocabulary knowledge on students' writing performance

The aim of the research is finding out the level of the student’s vocabulary knowledge, the level of the students writing performance, and the correlation of vocabulary knowledge on students’ writing performance. The data source in this research were the students who were studying English at Muallimin Muhammadiyah Senior High School in Makassar, South Sulawesi, Indonesia. To obtain the data in the field, the researchers distributed writing and vocabulary test. This research found that the level of the students’ vocabulary knowledge is categorized as “good” classification. Most of students of Muallimin Muhammadiyah Senior High School Makassar got score 70 – 79 with the mean score is 66.84. This research also found that the level of the students’ writing performance is categorized as “fair” classification. Most of students of Muallimin Muhammadiyah Senior High School Makassar got score 60 – 69 with the mean score is 69.28. Finally this research revealed that there was a significant and positive correlation between students’ vocabulary knowledge and writing competence.
Integrated Skills Approach (ISA) in writing class: A case study of Business English Communication (BEC) students of Universitas Negeri Makassar

The study aims to describe (1) the nature of the Integrated Skills Approach in writing class, (2) whether the Integrated Skills Approach (ISA) is effective in facilitating the students to write English compositions. The study was conducted in the Business English Communication (BEC) writing class of the English Department, Faculty of Languages and Literature, Universitas Negeri Makassar. The subject of this study was the BEC students, consisting of 20 students. This study was essentially quantitative research. The data were taken from the students’ writing compositions and analyzed using the pre-experimental method with one group pre-test and post-test design. This design involves one group, which was pre-tested (X1), then exposed to treatment (T), and post-tested (X2). The study shows some results as follows: 1) Integrated Skills Approach (ISA) could enthusiastically involve the students in learning activities. 2) Integrated skills sequence leads the students to share ideas about the topic of writing composition. 3) Integrated Skills Approach (ISA) effectively facilitates students' English composition writing.
Optimization of wavefront reconstruction accuracy for conjugate shift differential absolute testing

Abstract The conjugate shift differential method, based on Fourier transforms, is critical for surface error testing of high-precision optical elements. However, this common approach is also prone to periodic spectrum loss. As such, this paper proposes conjugate double shift differential (CDSD) absolute testing, which can effectively compensate for spectrum loss and achieve accurate wavefront reconstructions. Spectrum loss in the single shift differential method is analyzed through a study of the Fourier reconstruction process. A calculation model for the proposed CDSD method is then established and constraint conditions for shift quantities are provided by analyzing double shear effects observed in transverse shear interference. Finally, the reconstruction accuracies of various spectrum compensation methods are compared. Results showed that spectrum loss became more evident with increasing shift amounts. However, the CDSD method produced the smallest measurement error compared with conventional direct zero filling and adjacent point averaging, suggesting our approach could effectively improve absolute shape measurement accuracy for planar optical elements.
Single Image Dehazing using Extended Local Dark Channel Prior

Abstract Image dehazing is an important technique aimed at eliminating the haze in the atmosphere to enhance the image's visual quality. There are many applications where it has been used as a prepossessing step, such as in event detection. In recent years, the dark channel prior methodology has been recognised as an effective approach for eliminating haze from hazy images. However, the main drawback of the existing dark channel prior methodology is that it only considers a single color channel of the RGB image with pixels having minimum intensity values. This non-uniform selection of the dark channel from a single channel eradicates the effect of the transmission across the different channels of the hazy image. Hence, the haze cannot be removed to a great extent using the existing method. So, here we propose an approach where the dark channel will be computed from all three channels of an image by selecting the minimum intensity. The main advantage of using the proposed prior-based methodology for image dehazing over deep neural network-based models such as CNN or GANs is that training deep models requires a large amount of training data, thus resulting in a longer training time. Experimental outcomes exhibit that the proposed technique outperforms state-of-the-art methods on synthetic datasets as well as real-world hazy images. The findings demonstrate that the proposed technique obtains better accuracy as compared to the state-of-the-art methods and recent deep learning-based models over the D-HAZY, I-HAZE, and O-HAZE databases.
SWIFT

The proposed project is a Web-Based Application that provides users a user-friendly interface for better experience. It overcomes the problem of using different applications for different features. As social media is a very important factor in analyzing modern society as a whole, their values, norms, and behaviors, as being a part of our everyday life. The web application has been developed to allow a user to follow specific accounts they know and categorize the posts on those accounts based on the user needs. The benefit of this project is that any user can communicate and spread smiles while being connected to each other, and it enables anyone to have better insight about society as a whole, their values, norms, what they find interesting, and many other things. This tool is also useful for different companies to track the user feedback on social networks for their products and be vast in their respective fields.
Comparison of Feature detection using SIFT and ORB detector

In Recent days there are many developments in computer vision applications like self-driving cars, pedestrian detection, traffic flow analysis, road condition monitoring, medical applications, industry applications, image reconstruction, image matching, and object detection. In this all applications basic or the foundation of the subject is detection this is the reason our focus of the paper is on the detector. This article describes a detection of features in the image. Different method of detectors are available based on the application we can choose the specific detectors. The Deep learning algorithm also shows the enhancement in the detection performance. In this paper, our focus is on SIFT and ORB detector which is widely used in computer vision applications. Keypoint detection of SIFT and ORB was measured and compared. The computation time of the ORB and SIFT is also necessary parameter in the detection process. The proposed work measured the computation time of both the detectors with different keypoints.
Tool-use training in augmented reality: Plasticity of forearm body schema does not predict sense of ownership or agency in older adults

In young adults (YA) who practised controlling a virtual tool in augmented reality (AR), the emergence of a sense of body ownership over the tool was associated with the integration of the virtual tool into the body schema (BS). Agency emerged independent of BS plasticity. Here we aimed to replicate these findings in older adults (OA). Although they are still able to learn new motor tasks, brain plasticity and learning capacity are reduced in OA. We predicted that OA would be able to gain control over the virtual tool indicated by the emergence of agency but would show less BS plasticity as compared to YA. Still, an association between BS plasticity and body ownership was expected. OA were trained in AR to control a virtual gripper to enclose and touch a virtual object. In the visuo-tactile (VT) but not the vision-only (V) condition, vibro-tactile feedback was applied through a CyberTouch II glove when the tool touched the object. BS plasticity was assessed with a tactile distance judgement task (TDJ) where participants judged distances between two tactile stimuli applied to their right forearm. Participants further rated their perceived ownership and agency after training. As expected, agency emerged during the use of the tool. However, results did not indicate any changes in the BS of the forearm after virtual tool-use training. Also, an association between BS plasticity and the emergence of body ownership could not be confirmed for OA. Similar to YA, the practice effect was stronger in the visuo-tactile feedback condition compared with the vision-only condition. We conclude that a sense of agency may strongly relate to improvement in tool-use in OA independent of alterations in the BS, while ownership did not emerge due to a lack of BS plasticity.
Path and Direction Discovery in Individual Dynamic Factor Models: A Regularized Hybrid Unified Structural Equation Modeling with Latent Variable

There has been an increasing call to model multivariate time series data with measurement error. The combination of latent factors with a vector autoregressive (VAR) model leads to the dynamic factor model (DFM), in which dynamic relations are derived within factor series, among factors and observed time series, or both. However, a few limitations exist in the DFM representatives and estimation: 1) the dynamic component of DFM contains either directed or undirected contemporaneous relations, but not both, 2) selecting the optimal model in exploratory DFM is a challenge, 3) the consequences of structural misspecifications on estimation and model selection is barely studied. Our paper serves to advance DFM with a hybrid VAR representations and the utilization of LASSO regularization to select the dynamnic relations in a data-driven manner. A simulation study is presented to investigate the sensitivity of finding the true hybird dynamic relations in the structural model and the specificity of excluding the false relations using LASSO-regularization versus pseudo-ML. We also examine the robustness of parameter estimates in the selected model using LASSO-regularization, pseudo-ML, and model-implied instrumental variable two-stage least squares estimation. We aim to offer researchers guidance on model selection and estimation in person-centered dynamic assessments.
Random Walks on the Generalized Symmetric Group: Cutoff for the One-sided Transposition Shuffle

Abstract In this paper, we present a proof for the exhibition of a cutoff for the one-sided transposition (OST) shuffle on the generalized symmetric group $G_{m,n}$. Our work shows that based on techniques for $m \leq 2$ proven in \cite{M20}, we can prove the cutoff in total variation distance and separation distance for an unbiased OST shuffle on $G_{m,n}$ for any fixed $m \geq 1$ in time $n \log(n)$. MSC Classification: 60J10 , 20B05 , 20B25
Joint modelling of latent cognitive mechanisms shared across decision-making domains

Decision-making behavior is often understood using the framework of evidence accumulation models (EAMs). Nowadays, EAMs are applied to various domains of decision-making with the underlying assumption that the latent cognitive constructs proposed by EAMs are consistent across these domains. In this study we investigate both the extent to which the parameters of EAMs are related between four different decision-making domains and across different time points. To that end, we make use of the novel joint modelling approach, that explicitly includes relationships between parameters, such as covariances or underlying factors, in one combined joint model. Consequently, this joint model also accounts for measurement error and uncertainty within the estimation of these relations. We found that EAM parameters were consistent between time points on three of the four decision-making tasks. For our between-task analysis we constructed a joint model with a factor analysis on the parameters of the different tasks. Our two factor joint model indicated that information processing ability was related between the different decision-making domains. However, other cognitive constructs such as the degree of response caution and urgency were only comparable on some domains.
Psycho-Pedagogical Experience of Intellectual Education in the Views of Ukrainian and Foreign Pedagogues as the Basis of Modern Neuropedagogy

It is extremely important to reconsider psycho-pedagogical experience in the problem of intellectual education that is mainly highlighted on the pages of the leading periodical “Sovetskaya Pedagogika”. The research hypothesis is the possibility of using the pedagogical experience of the journal’s co-authors to justify the basic principles of neuropedagogy, which became widespread after its publication had ended. The research aims to identify and generalize the main areas of intellectual education on the pages of the journal based on a holistic retrospective analysis of professional publications and, thus, identify the factual material and theoretical approaches which have formed the basis of modern neuropedagogy. Research methods involve a set of general scientific and psycho-pedagogical methods: systematic search methods (identification, theoretical analysis and systematization of historical-and-pedagogical works and materials of pedagogical periodicals); historical-and-retrospective methods (analysis of the content and characteristics of reflection and solving of problems related to intellectual education on the pages of the journal); comparative methods (comparison of events, phenomena and facts mentioned in the journal, in particular, the views of national and international theorists and practitioners on the problems of intellectual education, which have formed the basis of modern neuropedagogy). In the paper, theoretical generalization and a new approach to solving a topical problem of generalizing the main areas of intellectual education on the pages of the periodical, namely, the problem of intellectual education in the context of developing an idea on the individual’s harmonious development; a comprehensive approach to the problem of intellectual education on the pages of the periodical; the problem of intellectual development as the basis of intellectual education on the pages of the periodical “; promotion of cognitive activity and independence as an effective means of intellectual education; pedagogical views on the problem of intellectual education on the pages of the periodical; foreign experience in promoting intellectual education on the pages of the periodical have been presented. The stages in the history of forming and developing the periodical “Sovetskaya Pedagogika” (1937–1991) have been concretized following the status and subordination. Particular facts, concepts and problems of the prominent educational journal in the context of establishing the ideas of neuropedagogy and neuropsychology have been specified. The significance of pedagogical periodicals as an important source of psycho-pedagogical research has been justified.