Reviewerly/exHarmony huggingface dataset:
Optimal Algorithms for Stochastic Three-Composite Convex-Concave Saddle Point Problems

We develop stochastic first-order primal-dual algorithms to solve a class of convex-concave saddle-point problems. When the saddle function is strongly convex in the primal variable, we develop the first stochastic restart scheme for this problem. When the gradient noises obey sub-Gaussian distributions, the oracle complexity of our restart scheme is strictly better than any of the existing methods, even in the deterministic case. Furthermore, for each problem parameter of interest, whenever the lower bound exists, the oracle complexity of our restart scheme is either optimal or nearly optimal (up to a log factor). The subroutine used in this scheme is itself a new stochastic algorithm developed for the problem where the saddle function is non-strongly convex in the primal variable. This new algorithm, which is based on the primal-dual hybrid gradient framework, achieves the state-of-the-art oracle complexity and may be of independent interest.
cOAlition S: Response to PNAS

We thank Marcia McNutt (1) for her opinion piece in PNAS where she supports the goal of open access (OA). We agree with her assertion that further changes in scholarly publishing are inevitable as it “aspires to serve science and society.” This ambition is at the heart of the Plan S principles. We seek to work in partnership with funders and other stakeholders—including learned societies—to ensure that the outputs of funded research can be accessed and used by all.The opinion piece very much focuses on the challenges that learned societies and researchers will face in the transition to full and immediate OA. It concludes with a rhetorical question: What problem is Plan S designed to solve? The answer is simple: We believe that by maximizing access to research results—including by digital technologies such as artificial intelligence and text and data mining—we stand a better chance of understanding and addressing the many challenges society now faces.As research funders, we are dedicated to serving the research … [↵][1]1To whom correspondence should be addressed. Email: r.kiley{at}wellcome.ac.uk. [1]: #xref-corresp-1-1
Alexandria: Unsupervised High-Precision Knowledge Base Construction using a Probabilistic Program

Creating a knowledge base that is accurate, up-to-date and complete remains a significant challenge despite substantial efforts in automated knowledge base construction. In this paper, we present Alexandria -- a system for unsupervised, high-precision knowledge base construction. Alexandria uses a probabilistic program to define a process of converting knowledge base facts into unstructured text. Using probabilistic inference, we can invert this program and so retrieve facts, schemas and entities from web text. The use of a probabilistic program allows uncertainty in the text to be propagated through to the retrieved facts, which increases accuracy and helps merge facts from multiple sources. Because Alexandria does not require labelled training data, knowledge bases can be constructed with the minimum of manual input. We demonstrate this by constructing a high precision (typically 97\%+) knowledge base for people from a single seed fact.
SceneCode: Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations

Systems which incrementally create 3D semantic maps from image sequences must store and update representations of both geometry and semantic entities. However, while there has been much work on the correct formulation for geometrical estimation, state-of-the-art systems usually rely on simple semantic representations which store and update independent label estimates for each surface element (depth pixels, surfels, or voxels). Spatial correlation is discarded, and fused label maps are incoherent and noisy. We introduce a new compact and optimisable semantic representation by training a variational auto-encoder that is conditioned on a colour image. Using this learned latent space, we can tackle semantic label fusion by jointly optimising the low-dimenional codes associated with each of a set of overlapping images, producing consistent fused label maps which preserve spatial correlation. We also show how this approach can be used within a monocular keyframe based semantic mapping system where a similar code approach is used for geometry. The probabilistic formulation allows a flexible formulation where we can jointly estimate motion, geometry and semantics in a unified optimisation.
Light-cone and local front dynamics of a single-particle extended quantum walk

We study the light-cone and front dynamics of a single particle continuous time extended quantum walk on a one dimensional lattice with finite range hopping. We show that, in general, for an initially localized state, propagating wave fronts can be characterized as ordinary or extremal fronts with the latter exhibiting an anomalous sub-diffusive scaling behaviour in the front region. We investigate the dynamical global and local scaling properties of the cumulative probability distribution function for the extended walk with nearest and next-nearest neighbour hopping using analytical and numerical methods. The global scaling shows the existence of a 'causal light-cone' corresponding to excitations travelling with a velocity smaller than a maximal 'light velocity'. Maximal fronts moving with fixed 'light velocity' bound the causal cone. The front regions spread with time sub-diffusively exhibiting a local Airy scaling which leads to an internal staircase structure. At a certain critical next-nearest neighbour hopping strength, there is a transition from a phase with one 'causal cone' to a phase with two nested 'causal cones' and the existence of an internal staircase structure in the corresponding cumulative distribution profiles. We also connect the study to that in spin chain systems and indicate that a single particle quantum walk on the one dimensional lattice already captures the many body physics of a spin chain system. In particular, we suggest that the time evolution of a single particle quantum walk on the one dimensional lattice with an initially localized state is equivalent to the time evolution of a domain wall initial state in a corresponding spin chain system.
TRANSFORMING PUBLIC LIBRARIES INTO DIGITAL KNOWLEDGE DISSEMINATION CENTRE IN SUPPORTING LIFELONG BLENDED LEARNING PROGRAMMES FOR RURAL YOUTHS

This research aims to examine how commissioning, transforming and maximum utilization of the digital technology infrastructure in public libraries through blended mode digital education platform could support open and distance lifelong learning in upgrading knowledge, livelihood and human capital for the constant improvement and upgrading of knowledge/skills among village youths.Mixed-method research design was implemented including administration of survey, interviews and observation.The five dimensions of enhancing the innovative open and distance digital platform to support a blended-mode dissemination of knowledge were examined, including demographic, digital technology availability, Open Education Resources in public libraries, learning culture and corporate support.Findings show that there are significant differences among factors stated above which will upgrade the potential of village youths technical and livelihood knowledge to be relevant and competitive in building human capital.The use of a blended digital education platform in public libraries could be beneficial to village folks in upgrading their knowledge and skills.This model could be used as framework of practice for enhancement of life skills among developing nations as well as under-developed countries in line with SEAMEO's Education Agenda to promote lifelong learning and 21 st century skills.If such technology-enhanced skills development programme could be implemented from earlier stages in educational settings in line with Sustainable Development Goals (SDGs) and Malaysian Education Blueprint, more skilled workers could be produced to raise the performance in the workplace and contribute to the worldwide improvement of human capital.Legal and policy issues on digital facilities will be discussed as to advocate lawful and ethical application of this initiative.Future direction of studies to develop a comprehensive structural model will also be deliberated.
Focus areas for data acquisition for potential domestic sources of critical minerals—Rare earth elements

First posted March 14, 2019 Revised July 14, 2022 For additional information, contact: Mineral Resources ProgramU.S. Geological Survey913 National Center12201 Sunrise Valley Drive Reston, VA 20192Email: Minerals@usgs.gov Rare earth elements (REEs) are critical mineral commodities for the United States. In response to a need for information on potential domestic sources of REEs in mineral deposits, the U.S. Geological Survey (USGS) identified broad focus areas throughout the conterminous United States and Alaska as a guide for selecting new geoscience research areas. This study was done to support the USGS Earth Mapping Resources Initiative (Earth MRI).Focus areas are identified in four regions of the United States (Alaska, West, Central, and East) by mineral deposit type. The areas are described in a companion USGS data release that consists of a map in a geographic information system and accompanying tables that document the rationale for each focus area (C.L. Dicken and others, 2019, https://doi.org/10.5066/P95CHIL0). This open-file report describes the methodology that was used to identify focus areas and determine new data acquisition needs. Deposit types that are likely to be of interest for future exploration and development of domestic nonfuel REE resources include deposits associated with carbonatites and peralkaline rocks, iron oxide-apatite deposits, monazite-bearing placers, and REE-enriched phosphorites.
A deformable multimodal image registration using PET/CT and TRUS for intraoperative focal prostate brachytherapy

In this paper, a deformable registration method is proposed that enables automatic alignment of preoperative PET/CT to intraoperative ultrasound in order to achieve PET-determined focal prostate brachytherapy. Novel PET imaging agents such as prostate specific membrane antigen (PSMA) enables highly accurate identification of intra/extra-prostatic tumors. Incorporation of PSMA PET into the standard transrectal ultrasound (TRUS)-guided prostate brachytherapy will enable focal therapy, thus minimizing radiation toxicities. Our registration method requires PET/CT and TRUS volume as well as prostate segmentations. These input volumes are first rigidly registered by maximizing spatial overlap between the segmented prostate volumes, followed by the deformable registration. To achieve anatomically accurate deformable registration, we extract anatomical landmarks from both prostate boundary and inside the gland. Landmarks are extracted along the base-apex axes using two approaches: equiangular and equidistance. Three-dimensional thin-plate spline (TPS)-based deformable registration is then performed using the extracted landmarks as control points. Finally, the PET/CT images are deformed to the TRUS space by using the computed TPS transformation. The proposed method was validated on 10 prostate cancer patient datasets in which we registered post-implant CT to end-of-implantation TRUS. We computed target registration errors (TREs) by comparing the implanted seed positions (transformed CT seeds vs. intraoperatively identified TRUS seeds). The average TREs of the proposed method are 1.98&plusmn;1.22 mm (mean±standard deviation) and 1.97&plusmn;1.24 mm for equiangular and equidistance landmark extraction methods, respectively, which is better than or comparable to existing state-of-the-art methods while being computationally more efficient with an average computation time less than 40 seconds.
Guidelines for defining user requirement specifications (URS) of manufacturing execution system (MES) based on ISA-95 standard

To standardize the authoring of user requirement specifications (URS) for manufacturing execution system (MES) proposed by manufacturing enterprises from users' perspectives, and facilitate a quick and effective communication between them and MES vendor or integrator, an approach for URS definition was introduced based on the ISA-95 standard, in which a method for requirement elicitation based on goal and scenario was combined. In this approach, a framework for MES problem space was constructed first from three dimensions: generic activity model for manufacturing operations management (MOM), manufacturing operations categories and supporting activities, and then a series of guidelines for standard application, scenario authoring and requirement arrangement were established to guide the users in seeking the needs and writing them in a normalized sentence form step by step. Additionally, a structure of the table of content for URS documentation was recommended to help the users organizing the textual requirement description. Finally, a case study for applying this approach was performed in a pharmaceutical company's example, which illustrates the application prospect in MES product selection.
Toward location privacy protection in Spatial crowdsourcing

Spatial crowdsourcing is an emerging outsourcing platform that allocates spatio-temporal tasks to a set of workers. Then, the worker moves to the specified locations to perform the tasks. However, it usually demands workers to upload their location information to the spatial crowdsourcing server, which unavoidably attracts attention to the privacy-preserving of the workers’ locations. In this article, we propose a novel framework that can protect the location privacy of the workers and the requesters when assigning tasks to workers. Our scheme is based on mathematical transformation to the location while providing privacy protection to workers and requesters. Moreover, to further preserve the relative location between workers, we generate a certain amount of noise to interfere the spatial crowdsourcing server. Experimental results on real-world data sets show the effectiveness and efficiency of our proposed framework.
The Common Vulnerability Scoring System vs. Rock Star Vulnerabilities: Why the Discrepancy?

Meltdown & Spectre came as natural disasters to the IT world with several doomsday scenarios being professed. Yet, when we turn to the de facto standard body for assessing the severity of a security vulnerability, the Common Vulnerability Scoring System (CVSS), we surprisingly notice that Meltdown & Spectre do not command the highest scores. We witness a similar situation for other rock star vulnerabilities (vulnerabilities that have received a lot of media attention) such as Heartbleed and KRACKs. In this manuscript, we investigate why the CVSS ‘fails’ at capturing the intrinsic characteristics of rock star vulnerabilities. We dissect the different elements of the CVSS (v2 and v3) to prove that there is nothing within it that can indicate why a particular vulnerability is a rock star. Further, we uncover a pattern that shows that, despite all the beautifully elaborated formulas, magic numbers and catch phrases of the CVSS, there is still a heavy presence human emotion into the scoring as rock star vulnerabilities that were exploited in the wild before being discovered tend to have a higher score than those that were discovered and responsibly disclosed by security researchers. We believe that this is the principal reason of the discrepancy between the scoring and the level of media attention as the majority of 'modern' high level vulnerabilities are introduced by security researchers.
DIGITAL TECHNOLOGIES IN THE CONTENT OF MASTER’S EDUCATIONAL PROGRAMS OF TRAINING TECHNOLOGY TEACHERS

The article presents an analysis of the influence of modern digital technologies on the content of new master’s programs of pedagogical education for the preparation of technology teachers. Currently, the development of modern industrial technologies in the world occurs in the paradigm of Industry 4.0, which highlights such fundamental technological directions as robotics, modeling, big data, industrial Internet of things, cloud computing, additive technologies, augmented reality, etc. These areas need to be included in the content of technological education at school, and this, in turn, requires highly qualified teachers who also know the basics of the technologies under consideration and are able to form pupils’ competences in the field of modern digital technologies. One of the opportunities to get the teacher competence in the field of modern technologies, including digital technologies, is training in the magistracy. Master's programs can more quickly respond to changes in educational markets, including new content and new educational technologies. The article analyzes more than 30 programs of Russian universities, in the disciplines of which such modern industrial technologies as robotics, Internet of things, 3D modeling, big data, cloud computing, virtual and augmented reality, computer modeling, etc. are presented.
The Emotionally Intelligent Robot: Improving Social Navigation in Crowded Environments

We present a real-time algorithm for emotion-aware navigation of a robot among pedestrians. Our approach estimates time-varying emotional behaviors of pedestrians from their faces and trajectories using a combination of Bayesian-inference, CNN-based learning, and the PAD (Pleasure-Arousal-Dominance) model from psychology. These PAD characteristics are used for long-term path prediction and generating proxemic constraints for each pedestrian. We use a multi-channel model to classify pedestrian characteristics into four emotion categories (happy, sad, angry, neutral). In our validation results, we observe an emotion detection accuracy of 85.33%. We formulate emotion-based proxemic constraints to perform socially-aware robot navigation in low- to medium-density environments. We demonstrate the benefits of our algorithm in simulated environments with tens of pedestrians as well as in a real-world setting with Pepper, a social humanoid robot.
Evaluating Player Performance and Experience in Virtual Reality Game Interactions using the HTC Vive Controller and Leap Motion Sensor

An important aspect of virtual reality (VR) interfaces are novel natural user interactions (NUIs). The increased use of VR games requires the evaluation of novel interaction techniques that allow e ...
Application of Modified PageRank Algorithm for Anomaly Detection in Movements of Older Adults

It is a well-known statistic that the percentage of our older adult population will globally surpass the other age groups. A majority of the elderly would still prefer to keep an active life style. In support of this life style, various monitoring systems are being designed and deployed to have a seamless integration with the daily living activities of the older adults while preserving various levels of their privacy. Motion tracking is one of these health monitoring systems. When properly designed, deployed, integrated, and analyzed, they can be used to assist in determining some onsets of anomalies in the health of elderly at various levels of their Movements and Activities of Daily Living (MADL). This paper explores how the framework of the PageRank algorithm can be extended for monitoring the global movement patterns of older adults at their place of residence. Through utilization of an existing dataset, the paper shows how the movement patterns between various rooms can be represented as a directed graph with weighted edges. To demonstrate how PageRank can be utilized, a base graph representing a normal pattern can be defined as what can be used for further anomaly detection (e.g., at some instances of observation the measured movement pattern deviates from what is previously defined as a normal pattern). It is shown how the PageRank algorithm can detect simulated change in the pattern of motion when compared with the base-line normal pattern. This feature can offer a practical approach for detecting anomalies in movement patterns associated with older adults in their own place of residence and in support of aging in place paradigm.
Reduction of Artefacts in JPEG-XR Compressed Images

The JPEG-XR encoding process utilizes two types of transform operations: Photo Overlap Transform (POT) and Photo Core Transform (PCT). Using the Device Porting Kit (DPK) provided by Microsoft, we performed encoding and decoding processes on JPEG XR images. It was discovered that when the quantization parameter is >1-lossy compression conditions, the resulting image displays chequerboard block artefacts, border artefacts and corner artefacts. These artefacts are due to the nonlinearity of transforms used by JPEG-XR. Typically, it is not so visible; however, it can cause problems while copying and scanning applications, as it shows nonlinear transforms when the source and the target of the image have different configurations. Hence, it is important for document image processing pipelines to take such artefacts into account. Additionally, these artefacts are most problematic for high-quality settings and appear more visible at high compression ratios. In this paper, we analyse the cause of the above artefacts. It was found that the main problem lies in the step of POT and quantization. To solve this problem, the use of a "uniform matrix" is proposed. After POT (encoding) and before inverse POT (decoding), an extra step is added to multiply this uniform matrix. Results suggest that it is an easy and effective way to decrease chequerboard, border and corner artefacts, thereby improving the image quality of lossy encoding JPEG XR than the original DPK program with no increased calculation complexity or file size.
Investigating demotivational factors in Indonesian EFL classrooms: The case of madrasa students

Compared to motivation, demotivation is still a relatively new topic in the field of language learning. This present study aims to investigate demotivational factors among Madrasa (religious educational institution) students in the Indonesian EFL context. This study employed a mixed-methods approach with an explanatory design in which the quantitative phase was conducted before the qualitative phase. A 25-close-ended questionnaire along with one open-ended question were filled by 190 Madrasa students. To expand the results of the questionnaire, interviews with two students were conducted. Through a descriptive analysis and thematic analysis, five key demotivators were revealed, they are a) the nature of the target language, b) lesson-specific factors, c) learning materials, d) teacher-related factors, and e) the learning environment. The results also indicated some factors which are not included in the questionnaire, they are a) lack of self-confidence, b) lack of intrinsic motivation, c) lack of learning community, and d) teacher gender. Although previously students’ religious beliefs were said to affect the students’ demotivation, it appeared that half of the students did not consider them to be demotivating. Instead of religious beliefs, the students found the nature of English as the most demotivating factor, which contradicts the findings of previous demotivation studies that found teachers as the main demotivating factor.