Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvement of the method for assessing the level of speech information security

Assessment of the level of speech information protection from leakage through acoustic and vibration channels is carried out according to international and national standards and in compliance with regulatory documents. To assess its security level, regulatory documents in many countries imply the use of signal/noise ratio. However, the method has a series of significant shortcomings, which do not make it possible to determine the real state of security level. The improved objective evaluation method, which is based on determining the coefficient of residual intelligibility for a test-signal after its recovery by the methods of mathematical analysis (adaptive filtration, correlation and spectral analyses, wavelet transformation, etc.) was proposed. The coefficient of residual intelligibility is determined for each word included in a short phrase, a test signal. The analysis of frequency of using the phonemes in the Ukrainian speech was performed. It was shown that given the definition of the term "allophone" and the number of native speakers, it is possible to assume that the total number of allophones tends to infinity. To reduce the calculation complexity, we proposed the formalized approach based on the simplified linguistic model – a phoneme (a letter), a diphone (two letters), and a triphone (three letters). As a source of information, it is possible to use text documents. We proposed analytical dependences for calculating the coefficient of residual speech intelligibility and its components – coefficients of frequency of using allophones in the words of the Ukrainian language and the importance of allophone recognition for the word recognition. The interrelations of the SPC (speech privacy class) and word intelligibility W were shown. On their base, the scale of objective estimation of the degree of speech information privacy on the boundary of the controlled zone by the criterion of residual speech intelligibility was proposed
Effect of Eight- Week Consumption of Purslane Extract on Peroxidane / Antioxidant Balance in Women with Type 2 Diabetes

Background and Objective : Imbalance Between antioxidant defensive system and increased production of free radicals leads to oxidative stress that can be effective in making cellular damage and causing some diseases such as diabetes. The aim of the current study was to investigate the effect of eight-week purslane extract consumption on some peroxidant and antioxidants indicators in patients with type 2 diabetes. Material and Methods : The Participants were 16 women with type 2 diabetes who had not the history of once a week regular physical activity program, in previous five years. They were randomly divided into two groups of experimental, purslane supplementation for eight weeks, and control. Blood sampling was performed in two stages. Results : After eight weeks of purslane consumption, resting levels of MDA, SOD and CAT in Supplementation group showed a significant decrease compared to those of control group. Conclusion : Purslane consumption can improve peroxidant/antioxidant balance in women with type2 diabetes.
Architectural alignment of process innovation and digital infrastructure in a high-tech hospital

ABSTRACT Two central approaches to IT-enabled organisational change are process innovation and digital infrastructure research. In this study, we investigate the alignment between them, both from a theoretical and a practical perspective. They have quite different basic assumptions on evolution; process innovation is a top-down approach, while digital infrastructures evolve bottom-up and are partly outside direct managerial control. Our research question is, how can a process innovation initiative successfully align with an underlying digital infrastructure? Our empirical evidence is an in-depth case study at a new high-tech hospital in Norway. Building on a proposed framework of alignment between process innovation and digital infrastructure, we identify, analyse three architectural alignment mechanisms. We found that (i) the careful deployment of lightweight IT in onsite configuration, loosely coupled from the infrastructure activities, allows for fast process innovation while leveraging the slow and nonlinear evolution of infrastructure (ii) the interaction between lightweight IT and large clinical systems by a set of boundary resources resolves the tension between innovation and infrastructure. For practitioners, we show that lightweight IT can serve as a mediating technology in the configuration.
Developmental Assets in Adolescent Basketball Players: Influence of Age, Maturation, Size and Functional Capacities

Sports participation has been referred as having important influence in positive youth development (PYD) in many life-long aspects, as social, physical, physiological and intellectual components. The aim of this study was to verify influences of body size, growth-related changes and age in developmental assets. This cross-sectional design study considered 45 male adolescent basketball players aged 13.6 ± 1.5 years. Participants were engaged in a club structured training program and competed at state level competition, supervised by the Federacao Paulista de Basketball (Sao Paulo´s state basketball Federation). There was substantial variation between athletes for all variables. Inspection of credible intervals showed a substantial variation in body size and functional capacity indicators between players grouped by age group and by maturity status. However, substantial variation by both age group or maturity status was present for DAP dimensions. No relation was observed between DAP dimensions with body size and functional capacity, partitioning the substantial variation between players by age group and maturity status. In the present study there was no substantial variation in developmental assets of adolescent basketball players by age or estimated maturity status. Also, from a multidimensional perspective, there was no influence of body dimensions and functional capacities with developmental assets.
Input–Output Finite-Time Estimation for Complex Networks With Switching Topology Under Dynamic Event-Triggered Transmission

This article investigates the problem of input–output finite-time estimation for a class of discrete-time complex networks with switching topology. The dynamic event-triggered communication manner is proposed to conduct the data transmission of the switching signal and measurement outputs subject to random sensor nonlinearities. The asynchronism of the switching and triggering actions also leads to the received switching index by the designed estimator being inconsistent with that of the estimated switched complex networks. Then, a novel piecewise Lyapunov functional, which is proved to be less conservative than the general one, is then constructed for handling the input–output finite-time estimation under the unmatched circumstance. Sufficient conditions are formulated to ensure that the underlying estimation error systems are input–output finite-time stochastically stable with respect to the norm bounded inputs within a finite time. Finally, the superiority and applicability of the developed approach are verified by a simulation example.
Attention-based Multi-modal Fusion Network for Semantic Scene Completion

This paper presents an end-to-end 3D convolutional network named attention-based multi-modal fusion network (AMFNet) for the semantic scene completion (SSC) task of inferring the occupancy and semantic labels of a volumetric 3D scene from single-view RGB-D images. Compared with previous methods which use only the semantic features extracted from RGB-D images, the proposed AMFNet learns to perform effective 3D scene completion and semantic segmentation simultaneously via leveraging the experience of inferring 2D semantic segmentation from RGB-D images as well as the reliable depth cues in spatial dimension. It is achieved by employing a multi-modal fusion architecture boosted from 2D semantic segmentation and a 3D semantic completion network empowered by residual attention blocks. We validate our method on both the synthetic SUNCG-RGBD dataset and the real NYUv2 dataset and the results show that our method respectively achieves the gains of 2.5% and 2.6% on the synthetic SUNCG-RGBD dataset and the real NYUv2 dataset against the state-of-the-art method.
MCPIP1 Deficiency Increases Insulin Sensitivity But Impairs Hepatic Insulin Sig- nal Transduction in Mice

MCPIP1 Deficiency Increases Insulin Sensitivity But Impairs Hepatic Insulin Signal Transduction in Mice Brett B. Holdaway2, Joshua D. Moody2, Lauren F. Brooks2, Mingui Fu3, Pappachan Kolattukudy4, and Yingzi Chang1* 1Department of Pharmacology, Kirksville College of Osteopathic Medicine, A.T. Still University of Health Sciences, Kirksville, Missouri, USA 2Kirksville College of Osteopathic Medicine, Kirksville, Missouri, USA 3Department of Basic Medical Science, School of Medicine, University of Missouri Kansas City, Kansas City, Missouri, USA 4Burnett School of Biomedical Sciences College of Medicine, University of Central Florida, Orlando, Florida, USA *Corresponding author: Dr. Yingzi Chang, M.D., Ph.D., Department of Pharmacology, Kirksville College of Osteopathic Medicine, A.T. Still University of Health Sciences, 800 West Jefferson Street, Kirksville, MO 63501, Tel: 1-660-626-2327; Fax: 1-660-627-2728; Email: ychang@atsu.edu Received: 07-01-2015 Accepted: 09-08-2015 Published: 10-09-2015 Copyright: © 2015 Yingzi Original Research
Contour Pattern Recognition with MNIST Dataset

We train a convolutional neural network for handwritten digits from the MNIST dataset. The aim the paper is to test the network for extremal datasets. Actually, we take digits contours as the validating set. The recognition accuracy is expectedly reduced, since the interior of an image carries significant information for the classifier. To obtain the contour of a MNIST -digit, we use the Canny detector and methods of mathematical morphology. The decreasing of the network accuracy may be treated as a part of information which is contained in the interior of handwritten digits.
A Lightness-aware Nearest Neighbor Search Method for Exampled-based Color Transfer

Transferring the color from an example image to a source image is a fundamental task in image editing. One recent color transfer method builds the connection between the source and example image under a mixture modeling framework, and utilize the EM algorithm to automatically modify the color style of the source image based on the example image. However, in real-world applications, users may want to intentionally generate multiple transferred results by varying a certain key feature in color style, such as lightness. In this paper, we propose a lightness-aware nearest neighbor search procedure that allows users to select the lightness style of the transferred image. Such a procedure selects the pixels in the example image according to the lightness to update the probability matrix in optimizing the parameters for the mixture model. Experiments demonstrate that our method can generate color transferred results with high/low lightness and high example consistency.
From Hospital to Home with NDIS Funded Support: Examining Participant Pathway Timeframes Against Discharge Expectations

ABSTRACT For patients with disability who require funded supports to leave hospital, the introduction of the National Disability Insurance Scheme (NDIS) represents opportunity and challenges. At a time of major reform, timely and supported discharge is reliant on overcoming interface complexities. The purpose of this study was to examine the NDIS participant pathway timeframes against discharge expectations for hospitalised adults with spinal cord injury (SCI) or acquired brain injury (ABI) and interrogate delays for the two groups. Administrative data on 54 participants (ABI = 18 and SCI = 36) were analysed. Both groups experienced delays to discharge and significant variability in timeframes between NDIS pathway processes and extent of delays. Group differences were identified regarding inefficiencies across the continuum, with type of support a factor to investigate further. This study has uncovered critical points in the NDIS pathway that could impact discharge of participants and where collaboration and adaptive strategies could be targeted to improve processes. IMPLICATIONS Ensuring the National Disability Insurance Scheme (NDIS) pathway operates effectively in the hospital setting is critical to the timely discharge of people with complex needs who require funded supports. Monitoring implementation of the NDIS in the health setting is important to avert interface problems that impede timely discharge and access.
The power to structure: exploring social worlds of privacy, technology and power in the Tor Project

ABSTRACT As Internet freedom movements build infrastructures to promote online privacy, they enrol a wide range of different kinds of of technological work [Coleman, E. G. , & Golub, A. (2008). Hacker practice: Moral genres and the cultural articulation of liberalism. Anthropological Theory, 8(3), 255–277]. I explore the cultures of the wider forms of technical work involved in these struggles through a sociological study of the Tor Project, involving twenty-six qualitative interviews with people in the Tor community and extensive archival research in Tor’s mailing lists and design documents. Tor is an online privacy infrastructure whose practice of radical transparency makes it uniquely accessible, and it constitutes an example of a successful, widely used infrastructure which directly undermines the centralisation of governmental power online. Tor is not united around a single worldview, instead exhibiting three distinct framings of its work. Using Susan Leigh Star's social worlds framework, I characterise these three ‘social worlds’ of Tor. I argue that Tor has in the past accommodated its internal clashing perspectives through an ambiguity around politics and a shared construction of the users of Tor, which allow individuals to bridge and translate between these worlds. In recent years, this political ambiguity has become unsustainable. As Internet platforms and infrastructures extend further into social life around the world, so too are they being forced to come to terms with the shaping forces they exert on society and the values they represent. Tor is not exempt from this, and as it navigates these issues it is becoming increasingly mindful of its own relationships to power, values and politics.
Effects of density dependence and climatic factors on population dynamics of Cricetulus barabensis: a 25-year field study

Rodents often act as keystone species in communities and play important roles in shaping structures and functions of many ecosystems. Understanding the underlying mechanisms of population fluctuation in rodents is therefore of great interest. Using the data from a 25-year field survey carried out in Inner Mongolia, China, we explored the effects of density dependence, local climatic factors, and a large-scale climatic perturbation (El Niño–Southern Oscillation) on the population dynamics of the striped hamster (Cricetulus barabensis), a rodent widely distributed in northern China. We detected a strong negative density-dependent effect on the population dynamics of C. barabensis. Rainfall had a significant positive effect on population change with a 1-year lag. The pregnancy rate of C. barabensis was negatively affected by the annual mean temperature in the current year, but positively associated with the population density in the current year and the annual Southern Oscillation Index in the previous year. Moving-window analyses suggested that, with a window length of 12 years, there was a significant interaction between rainfall and density dependence, with increasing rainfall alleviating the negative effect of density dependence. As C. barabensis often causes agricultural damage and can transmit zoonotic diseases to human beings, our results also have implications for pest and disease control.
Neural Networks Based Interaction Matrix Approximation for IBVS Applications

Visually guided robots should interpret what they see and they should accomplish their task by acting according to this interpretation. The method of using visual information as a feedback signal in a closed-loop robot system is named as visual servoing (VS). As the most popular type of VS, image-based visual servoing (IBVS) may encounter a common problem in realization: singularity of the pseudoinverse of the interaction matrix. Although the pseudoinverse of this matrix for IBVS can be applicable, the control law is useless in the case of singularities.In this study, the pseudoinverse of the interaction matrix is approximated with different types of trained neural networks to get rid of the singularity problem. The results of these approximations are given with MSE values.
Performance Analysis of WebRTC Embedding Optimized HEVC CodeC

Web Real-Time Communications (WebRTC) is an open-source platform, supporting developer to build voice- and video-communication solutions. Video compression engine is one infrastructure in WebRTC. As video stream accounting for more than 90% bandwidth requirement in real-time communication. The performance of embedded video encoder in WebRTC determines the Quality of Experience of communication, including the picture quality, the communication latency and the playback smoothness. In our WebRTC, we implemented the high performance HEVC software encoder as a substitute of the VP8 encoder in WebRTC. We improve the compression efficiency of HEVC encoder significantly. As compared with the most advanced x265, the averaged 34.6% rate saving was achieved by our encoder, especially in low-latency coding applications. As compared to the default WebRTC integrated with VP8, up to 90.2% bandwidth requirement was saved by our optimizations.
Geometry-appearance Ensemble Object Association for Semantic SLAM

Semantic visual simultaneous localization and mapping (SLAM) is a fundamental capability for autonomous driving. The high performance of semantic SLAM algorithm is based on the assumption of correct object association. However, most previous work utilize a single method to associate objects, which cannot remove the ambiguity of object association very well. Incorrect object association can degrade the semantic SLAM performance. In this paper, we propose an ensemble association method to associate objects. We combine geometric features with object appearance information to consider the effect of multiple information on object association results. Additionally, the bag-of-words algorithm is introduced to measure the similarity of object appearance for better association decisions. Experimental results on the KITTI dataset show that the method improves both the accuracy of object association and the performance of semantic SLAM.
Bibliometric Review of the Knowledge Base on Healthcare Management for Sustainability, 1994–2018

In response to the United Nations’ (UN) Sustainable Development Goals (SDGs), health care organizations throughout the world have adopted management initiatives designed to increase their sustainability. This review of research used bibliometric methods to analyze a dataset comprised of 477 documents extracted from the Scopus database. The review sought to document research on sustainable healthcare management (SHM) that has accumulated over the past 25 years. Results indicated that the intellectual structure of this body of knowledge is comprised of three schools of thought: (1) sustainable change in health care services, (2) innovations in managing health care operations, and (3) prioritizing and allocating resources for sustainability. The review also highlighted the recent topical focus of research in this literature. Key topics were linked to organization and management of health care services, quality of patient care, and sustainability of health care delivery.
Corporate social responsibility and employee behavior: Evidence from mediation and moderation analysis

Corporate social responsibility (CSR) has become a prominent subject due to its major implication for the practitioners in the corporate arena. Based on the theory of engagement, theory of social exchange, and theory of social identity, a conceptual framework was established in this study to evaluate the employee engagement (EE), and organizational commitment (OC) as a resultant of CSR initiatives. The study further examined the impact of distributive justice (DJ), procedural justice (PJ), and job satisfaction (JS) as mediating variables, and the influence of collectivism (COL) as a moderating variable between CSR initiatives and OC and EE. Data from 989 employees of the Pakistani pharmaceutical industry was collected and analyzed using the structural equation modeling and exploratory and confirmatory inferential models. Results demonstrate that CSR initiatives have a significant positive impact on OC and EE. Similarly, the mediation of JS, PJ, and DJ was established between the exogenous and the endogenous variables. Finally, the COL has a significant impact as a moderating variable between CSR initiatives, and OC and EE. The conclusions obtained in this study provide significantly practical and theoretical implications for managers of involved firms to improve employee behavior, mold employee attitude, and enhance organizational performance via CSR strategy, especially for firms located in countries along the route of belt and road initiative.
Decoding service brand image through user-generated images

© 2020, Emerald Publishing Limited. Purpose: Despite the growing number of studies surrounding user-generated content (UGC), understanding of the implications, potential and pertinence of user-generated images (UGI), the visual form of UGC, on brand image in services is limited. The purpose of this paper is to introduce the concept and a comprehensive framework of image word of mouth (IWOM), which identifies UGI as visual articulations of service experiences that result in consumer judgment of service brand image. The framework takes a consumer-focussed approach and covers key branding issues relevant to services marketers such as identifying and linking valued services dimensions, made evident through IWOM, to ideas and thoughts inferred by consumers (viewers) of the brand image and consequent consumer intentions. Design/methodology/approach: The paper reviews and synthesises current services, marketing and branding literature surrounding electronic word of mouth (WOM) and UGC, where it highlights the need to consider interpretations of UGI as persuasive forms of visual WOM or IWOM, as well as a critical stimuli of brand image. Findings: The paper illuminates the importance of adopting a visual perspective that applies constructs developed in cognitive psychology, to decode how viewers (consumers) interact and form associations of brand image via IWOM. Originality/value: The paper examines, integrates and adds to extant literature surrounding WOM, UGC, visual images and brand image within services.
Do compassionate firms outperform? The role of organizational learning

Based on a new management paradigm rooted on care and compassion, this study explores the consequences of compassion at work on organizational learning and firm performance. ,Structural equation modeling (SEM) was employed to analyze the research model by using data from two different samples. ,Results confirm that compassion increases firm performance through organizational learning capability; however, compassion do not enhances directly firm performance. ,The study findings indicate that when compassion is propagated among organizational members, organizations are better able to learn so they obtain a competitive advantage that is difficult to imitate and leads to higher firm performance. ,This study takes a step forward on literature by providing empirical evidence for a promising area of management research such is compassion in organizations.