Reviewerly/exHarmony huggingface dataset:
Challenges of Mobile Augmented Reality in Museums and Art Galleries for Visitors Suffering From Vision, Speech, and Learning Disabilities

In Today's digital world, AR is a tech which imposes layers of virtual segments on the real world. Research Practitioners and Designers in all applications seem to be more concerned about the learning facilities than keeping the visitors engaged in public art exhibitions, Museums, and holiday tourist locations. These ignored circumstances have provoked studies to emphasize more on the usability of Mobile Augmented Reality (M.A.R.) at Art galleries and Museums. According to the recent surveys, the current M.A.R. applications at target locations focus on healthy people without any disabilities, and not on those with disabilities. This chapter recommends major design elements of M.A.R. at museums and art galleries, and highlights all the challenges faced by visitors suffering from visual, speech, and Learning Disorders. The research discusses the 11 vital elements which include Usability, Design, Motivation, Interaction, Perceived control, Satisfaction, Attention, and others involving engagement of M.A.R. necessary for building an effective M.A.R. application for disabled people.
Increasing accuracy of classification physical activity based on smartphone using ensemble logistic regression with boosting method

Abstract At present, the smartphone is equipped with several sensors such as Accelerometer, Gravity sensor, and Gyroscope which can be used to recognize human physical activities such as walking upstair and walking downstairs etc. Machine learning is needed to group data and get information. Statistical methods have poor performance in classifying because procedures must be met. To overcome this, an ensemble technique was used. This study proposes the application of the gradientboost ensemble method to classify walking upstair and walking downstairs. The Android-based.apk system is designed for data retrieval using a smartphone. Then, the dataset will be partitioned into 70% training data and 30% test data. The results show that the performance of the ensemble boosting method produces 81.82% accuracy, 86.11% sensitivity and 77.50% specificity.
Geometry Guided Feature Aggregation in Video Face Recognition

Video-based face recognition has attracted a significant amount of research interest in both academia and industry due to its wide applications such as surveillance and security. Different from image-based face recognition, abundant information, extracted from a series of frames in a video, would contribute a lot to successful recognition. In other words, the key to improving video face recognition capability is aggregating and integrating profuse information within a video. Existing methods of feature aggregation across frames narrowly focus on the importance of a single frame, while ignoring the geometric relationship among frames in feature space. In this work, we present a geometry-based feature aggregation method rather than a better recognition model. It considers not only the importance of each frame but also the geometric relationship among frames in feature space, which yields more distinguishing video-level representation. Extensive evaluations on IJB-A and YTF datasets indicate that the proposed aggregation method considerably outperforms other feature aggregation methods.
Memory-Augmented Attention Network for Sequential Recommendation

An increased interest in sequential recommendation has been observed in recent years. Many models have been proposed to leverage the sequential user-item interaction data, which includes those based on Markov Chain or recurrent neural networks. Most of these models are designed for the scenario where each historical record composed of single item. However, the records could be a subset of items (or session) such as music playlists and baskets in e-commerce applications. How to leverage the session structure to improve the effectiveness of the recommendation system is a challenge. To this end, we propose a MEmory-augmented Attention Network for Sequential recommendation (MEANS), to effectively recommend next items given the sequential session data. The most recent sessions are stored into external memory after a max-pooling operation. The long-term user preference are learned through an attention network which is stacked on the memory layer. Finally, the mixture of long-term and short-term preference is feeded into the prediction layer to make recommendations. Extensive experiments on four real datasets show that MEANS outperforms various state-of-the-art sequential recommendation models.
Representation and classification of whole-body motion integrated with finger motion

This paper presents a novel approach toward representing human whole-body motions with fingers and classification of human motions while performing tasks that require delicate finger movements, such as holding or grasping. Human whole-body motions are recorded using an optical motion capture system that measures positions of markers attached to a performer. Additionally, the performer wears data gloves with strain gauges fixed at the finger joints to measure flexions and extensions. Combining whole-body motion with finger motions forms a representation of integrated motion, which is subsequently encoded into a probabilistic model whose parameters are optimized such that the model most likely generates the training data for the integrated motion. Observations of integrated motion are classified into the relevant probabilistic model with the largest probability of generating the observation. Synchronous measurements of human whole-body and finger motions created a dataset of integrated human motions. We tested our proposed approach on this dataset, thereby demonstrating that representations of whole-body motion integrated with finger motions improved classification of human motions while manipulating objects.
Educational Potential of Internet Communications

The modern Internet environment has great potential for education, as the functionality of Internet communication allows to make the educational process more technical, practical, coordinated, expanding the possibilities of access to both teachers and students to high-tech content. The article considers the functions of Internet communication and provides data on the study of the implementation of these functions from the point of view of students of leading Moscow universities.
Online Aggregated-Event Representation for Multiple Event Detection in Videos

Event detection is used to locate the frames corresponding to events of interest in given videos. Real-world videos contain multiple events of interest, and they are rarely segmented. Existing online methods can only detect segments containing single event instances, and this is not suitable for processing videos with several event instances. There are multiple event detection methods, but they are all relatively inefficient and offline methods. To handle the online detection of several events, we propose a novel framework with three modules that are: the event proposal generation, aggregated-event representation, and refined detection modules. The first module can locate time intervals that are likely to contain target events, termed as proposals. The second module can aggregate all events before the current time to form a temporal context that will be used to generate initial detection results of multiple events. The refined detection module finally refines the results based on event proposals and object detection. The proposed method achieves a detection accuracy of 24.88% on a multi-event dataset - Charades, which is higher than state-of-the-art methods.
Teachers’ perceptions of Grades 8–10 English First Additional Language learners’ reading habits, attitudes and motivation

Background: Owing to the dearth of reading practices within the South African literacy landscape, many learners neither engage in productive reading habits, nor exhibit a positive attitude towards English First Additional Language (EFAL) reading. Consequently, many learners experience reading challenges, which negatively impact on their academic performance. Objective: This study investigated the reading habits, attitudes and motivation of Grades 8–10 EFAL learners through the perceptive lens of EFAL teachers. Method: This qualitative study employed a case study design and a thematic data analysis process. The purposively selected sample for the semi-structured interviews consisted of six Grade 8–10 EFAL teachers from two high schools in the Tshwane South district. Results: Teachers believe that learners experience academic challenges because they do not habitually engage with texts, have a negative attitude towards printed text and read only to progress academically. The results further indicated that all these teachers concurred that there is a corresponding relationship between productive reading habits, a positive attitude towards reading and the academic performance of learners. Regrettably, the data analysis reported that the teachers have a pessimistic perception of the EFAL learners’ reading habits, attitudes and motivation to read. More disturbingly, most of the teachers lacked the responsibility for their contribution towards the ongoing demise of productive reading practices among learners in their classrooms. Conclusion: The findings revealed grave implications about learners’ reading habits, attitudes and motivation to read. Alarmingly, one of the most remarkable findings produced by this study is that the teachers themselves harbour negative perceptions about the reading practices of the learners in their classrooms.
Poster

The OS kernel, which has entire system privileges, is an attractive target of attackers. To reduce this threat, we need to find security bugs in the kernel prior to the attackers, and system call fuzzing is a widely used technique for this purpose. However, many system call fuzzers have not been evaluated for coverage performance which is an important indicator in fuzzing. In this poster, we propose a methodology to evaluate the code coverage performance of system call fuzzers with a strategy that combines virtualization and Intel Processor Trace (PT). First, we extract all the functions in the kernel that can be executed by system calls. Then we perform fuzzing with the target system call fuzzer on the guest OS, and record coverage information by leveraging the Intel PT. Finally, we evaluate system call fuzzers by comparing the list of functions related to system calls with the executed functions logged by Intel PT while fuzzing.
Sketching Streaming Histogram Elements using Multiple Weighted Factors

We propose a novel sketching approach for streaming data that, even with limited computing resources, enables processing high volume and high velocity data efficiently. Our approach accounts for the fact that a stream of data is generally dynamic, with the underlying distribution possibly changing all the time. Specifically, we propose a hashing (sketching) technique that is able to automatically estimate a histogram from a stream of data by using a model with adaptive coefficients. Such a model is necessary to enable the preservation of histogram similarities, following the varying weight/importance of the generated histograms. To address the dynamic properties of data streams, we develop a novel algorithm that can sketch the histograms from a data stream using multiple weighted factors. The results from our extensive experiments on both synthetic and real-world datasets show the effectiveness and the efficiency of the proposed method.
To couple or not to couple

Purpose The predominant narrative is that contemporary organisations, motivated by economic-rationalist aspirations, adopt cloud applications on the premise of achieving cost-savings and efficiency gains. However, how they actually adopt and rollover such new or emerging technologies may be influenced by acts, patterns and processes of institutional legitimacy. Therefore, the purpose of this paper is to explore the dynamics surrounding decisions on how specific cloud applications are adopted from the context of institutional theory, with a particular focus on the concepts of coupling and decoupling. Design/methodology/approach To examine this phenomenon, two qualitative case studies, using a reflexive research approach, of an Australian and a Swedish university have been undertaken, both of which adopted commercial cloud applications for e.g. e-mail, collaboration and storage (as examples of software as a service) at different points in time. One of the universities was known for its early adoption of cloud applications, but had decelerated further deployment of such services, while the other, despite its conservative reputation, has made rapid strides in this regard. Findings The findings of the dual case studies reveal that organisations, contrary to economic-rationalist claims, may or may not decide to adopt particular commercial cloud-based offerings for the support of core operations, on the basis of how they perceive their institutional legitimacy being affected by a complex network of influential actors, both internally and in the external spaces. Therefore, this paper offers an institutional theory-based discourse and rich illustrations on how the role of technology is played out in enhancing relationships between an organisation and such actors in terms of legitimacy focusing acts of coupling and decoupling. Originality/value In the analysis and findings the authors, in a novel way, illustrate how organisations strive for: institutional legitimacy through acts of coupling, and the revelations of consequential decoupling. The value is based on a rich case description, analysis and application of institutional theory.
Class Activation Mapping-Based Car Saliency Region and Detection for In-Vehicle Surveillance

This paper describes a class of problem where a detection and localization of car are addressed simultaneously using in-vehicle camera. While the current state-of-the-art researches have tackled the detection problems, in fact, there several rooms for the improvement. One of them is to optimize the detection processes. In this research, we introduce the use of activation map obtained from the last layer of the convolutional network to localize the saliency region of the car and to perform detection of the car objects by collaborating deep architecture trained weight. Our study also finds the benefit of changing the last layer of the network, from fully-connected layer to Global Average Pooling (GAP), which alleviates the overfitting problem. Experiment results on various optimization methods show the impact of the performance, where the proposed GAP-based deep learning and ADAM optimization gives the best results, up to 99.83%. It imply the possibilities of utilizing our method for real case usage scenario.
Text Steganography with High Embedding Capacity Using Arabic Calligraphy

Text is a challenging media for steganography due to the limited amount of redundancy bits in text and the ease of detecting minor changes in it. In linguistic steganography, the features of a language are used to hide data. The more features we have in a language, the more capacity of hiding data we can get. The Arabic language is rich in its features, many of which are still not used in text steganography. For example, Arabic calligraphy includes a variety of fonts and shapes for the Arabic alphabet. In this paper, by modifying a string matching algorithm and using suffix tree, the generation of Arabic stego text according to a secret message is implemented. The generation process is performed using a linguistic framework that utilizes Arabic calligraphy (AC-STEGA). In the presented work, multiple shapes of letters in Arabic font (Naskh) are used to increase the capacity of hiding data. This work comes as an extension of previous work to apply one shape of letters in (AC-STEGA). The evaluation showed an improvement in capacity of 65.4% compared to 25.4% presented in previous work. To satisfy security requirement, we did not use cover, the cover represents the secret message itself.
JoyHolder

One-handed mobile use, which is predominantly thumb-driven, presents interaction challenges like screen occlusion, reachability of far and inside corners, and an increased chance of dropping the device. We adopt a Research through Design approach around single-hand mobile interaction by exploring a variety of back-of-device tangibles (including a touchpad, scroller, magnetic button, push button, slider, stretchable spiral and a ring joystick). The latter 'joy'-stick was inspired from the recent popular but passive ring phone 'holders', which we combined into ?JoyHolder' - a joystick-based interactive phone holder for tangible back-of-device input interactions. We demonstrate our low-fidelity and medium-fidelity prototypes (using crafting and digital fabrication methods) and our interactive JoyHolder to encourage discussion on tangible back-of-device interactions. Preliminary insights from a pilot-study we ran reflects the hesitation for adopting some of these tangibles, the potential of others and the importance of physical feedback while using back-of-device input modalities.
Bilateralism and invalidities

There are many ways of understanding what it is for an argument to be valid. Although we usually identify the concept of validity with (classical first-order) logical validity and, in turn, we typically take this to capture the notion of necessary preservation of truth in virtue of logical form, this is just one way in which validity can be explained. A different understanding of the notion of validity that has received some attention recently is based on the idea that an argument is valid just in case accepting its premises is incoherent with rejecting its conclusion. The main claim of the paper will be that, under this understanding of the notion of validity, the usual reasons to privilege a treatment of validities over a treatment of invalidities loose much of their force. Validity and invalidity are on a par, which means that there are no strong reasons to treat validities primitively and to define invalidities in terms of them.
Exploiting MDE for Platform-Independent Testing of Service Orchestrations

Service Oriented Architecture (SOA) is a common design pattern that allows building applications composed of several services. It promotes features as interoperability, scalability, and software reuse. Services composing a SOA system may evolve and change during runtime, often outside the control of the owner of the application, which makes the verification and validation processes complex. Among all the automated techniques to validate the behavior of an SOA application, is Model-Based Testing (MBT). MBT requires an accurate model of the application in order to generate suitable test cases. However, the intrinsic of a SOA application sets significant challenges to MBT effectiveness. In this paper we discuss the challenges in the testing of SOA applications, and we propose the use of Model-Driven Engineering (MDE) to improve the flexibility of testing tools. Finally, we outline our plan for realizing MDE-driven MBT within an existing online testing framework.
Core-concavity, Gain Functions and Axioms for Information Leakage

This work explores connections between core-concavity and gain functions, two alternative approaches that emerged in the quantitative information flow community to provide a general framework to study information leakage. In particular (1) we revisit “Axioms for Information Leakage” by replacing averaging with $$\eta $$ -averaging and convexity with core-concavity. An interesting consequence of these changes is that the revised axioms capture all Rényi entropies, including the ones not captured by the original formulation of the axioms. (2) We provide an alternative proof for the Coriaceous Theorem based on core-concavity. The general approach of this work is more information theoretical in nature than the work based on gain functions and provides an alternative foundational view of quantitative information flow, rooted on the essential properties of entropy as a measure of uncertainty.
Characterisation of the Neoarchean Fortescue Group Stratigraphy – Integrated downhole geochemical mineralogical correlation from new diamond drilling

SummaryThe flood basalts and gold-bearing basal sediments of the 2775-2629 Ma Fortescue Group unconformably overlie the Mesoarchean West Pilbara Superterrane to the south of Karratha, Western Australia. Fresh exposures of the sedimentary units are lacking and their geochemical, mineralogical composition and sequence stratigraphy under cover are largely unknown. This research outlines the results of integrated downhole geochemistry and hyperspectral mineralogy of two new diamond drill holes, 4 km apart, which intersect the Fortescue group stratigraphy into the Mesoarchean Pilbara basement. This has been combined with trace element geochemistry, and high-resolution XRF mapping of representative samples provide micro-structural insights and in-situ geochemistry with textural context.The lithostratigraphy of the holes was defined using automated geochemical logging and tessellation methods, which provide objective classification of geologic units based on geochemistry and mineralogy. Individual basalt flows within the Kylena Formation can be correlated across holes based on chlorite content and geochemistry, and a chromium-rich geochemical marker horizon has been identified at the top of the siliciclastic Hardey Formation. The granitic basement rocks show evidence of significant fluid flow are interpreted to be a southern extension of the Maitland River Supersuite, consistent with regional geophysical anomalies that show a continuous gravity low.This dataset provides an unprecedented view into the Fortescue Group stratigraphy and its geochemistry. Correlation of this dataset with previous drilling provides insights into the regional tectonic and depositional history of the basin. The depth to basement increases from 650 m to >2200 m over ~12km N-S and the thickness of the clastic sedimentary basal Hardey Formation increases from ~150 m to 1050 m respectively. This indicates significant variation in the geometry of the basement during the deposition of the basal Hardey Formation, which was likely influenced by synsedimentary rifting. This has implications on the distribution of potential gold-bearing conglomerate facies unconformably overlying the basement, and in the Hardey Formation.
PROJECT MANAGEMENT IMPLEMENTATION IN GOVERNING INSTITUTIONS OF RUSSIA: AIMS AND RESULTS

Purpose: The article views applied aspects of an important scientific problem - efficiency improvement of state management based on project management that allows solving complex tasks under the conditions of severe restrictions in time, financial and other resources.&#x0D; Methodology: Methodical approach to project management includes process and targeted approaches that provide current operating activity long with innovative solutions implementation.&#x0D; Result: The article proves the implementation approach of project management in governing institutions based on the corporate culture, motivation and employee competencies transformation.&#x0D; Applications: This research can be used for universities, teachers, and students.&#x0D; Novelty/Originality: In this research, the model of Project Management Implementation In Governing Institutions of Russia: Aims and Results are presented in a comprehensive and complete manner.
Preface to the special issue – Exploration models for New Zealand’s hard rock gold deposits

This special issue comprises a group of nine papers resulting from the 4-year (2014–2018), New Zealand Government-funded, Gold Exploration Models research programme carried out collaboratively by G...