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The present study used a minority stress theory framework to investigate the direct and indirect relations of minority stressors (transgender discrimination experiences, internalized transphobia, identity nondisclosure), sense of belonging, and hopelessness with depression and anxiety symptoms in a sample of 301 trans and gender-diverse adults living in the United States. This study also explored the moderating effect of having knowledge of antitrans legislative efforts in one's state of residence on the overall pattern of results through a nested model comparison of the hypothesized path analysis. Participants were recruited using Internet-based forums, listservs, and social media, and survey data were collected online. Significant moderation effects were found, such that for those who reported having knowledge of antitrans legislative efforts in their state of residence reported a stronger association of external stressors (discrimination) than internal stressors (internalized transphobia, identity nondisclosure) on sense of belonging and hopelessness than their peers who did not have any knowledge of such legislative efforts. Furthermore, hopelessness emerged as a stronger predictor for those who were aware of antitrans legislative efforts. Implications of study findings for counseling, advocacy, and future research are discussed.

This article studies the vision-based tracking control problem for a nonholonomic multirobot formation system with uncertain dynamic models and visibility constraints. A fixed onboard vision sensor that provides the relative distance and bearing angle is subject to limited range and angle of view due to limited sensing capability. The constraint resulting from collision avoidance is also taken into account for safe operations of the formation system. Furthermore, the preselected specifications on transient and steady-state performance are provided by considering the time-varying and asymmetric constraint requirements on formation tracking errors for each robot. To address the constraint problems, we incorporate a novel barrier Lyapunov function into controller design and analysis. Based on the recursive adaptive backstepping procedure and neural-network approximation, we develop a vision-based formation tracking control protocol such that formation tracking errors can converge into a small neighborhood of the origin in finite time while meeting the requirements of visibility and performance constraints. The proposed protocol is decentralized in the sense that the control action on each robot only depends on the local relative information, without the need for explicit network communication. Moreover, the control protocol could extend to an unconstrained multirobot system. Both simulation and experimental results show the effectiveness of the control protocol.

Computer aided diagnosis have made a significant breakthrough in skin lesion diagnosis employing deep learning (DL) frameworks over the years, but it hardly reveals the transparency of the DL architecture. To mitigate this issue, this article proposes an image visibility filter (IVF) based DL framework for skin lesion diagnosis. The proposed IVF-DL network employs a ResNet architecture where visibility patches, extracted from the image visibility graph (IVG), are used as the convolutional kernels to extract salient features from dermoscopic images. The primary aim of this article is not only to classify skin lesions but also to depict the interpretable results after each residual block in a supervised manner. An optimal performance has been obtained by tuning three hyperparameters of the proposed method. Furthermore, the final interpretable result has been analyzed via IVG to resemble its spatial characteristics. Experimental results reveal the efficacy of the proposed method both qualitatively and quantitatively.

Leveraging cloud computing services to improve the flexibility and scalability of the IT services delivered to end-users is becoming increasingly important. However, organizations using cloud computing services face many challenges: decreased visibility into the performance of services being delivered to their end-users. Organizations using cloud computing services need to have visibility not only into the performance of applications that have moved to the cloud, but also into the different computing resources on which these applications depend. The monitoring system monitors the running state of virtual machines, response time and throughput. By analysing this data, you can identify the causes of service delays. During the operation of the monitoring system, virtual machines are suspended, a service delay occurs in order to avoid this delay. Therefore in this paper, a cloud computing model is proposed that takes into account the time spent for monitoring, calculations and probabilities of delay and waiting time are made, blocking probabilities are also put to account and results are shown in diagrams and the effects are discussed.

The efforts of bisexual+ people to make their sexual orientation visible are associated with positive and negative outcomes, but little is known about the temporality or directionality of these associations. Using data from a 28-day diary study with 208 bi+ individuals, we found that bi+ visibility attempts were concurrently associated with more positive affect, higher identity affirmation, less depressed/anxious affect, as well as more anti-bisexual experiences and rejection sensitivity. Prospectively, the likelihood of consuming alcohol (but not marijuana) was higher the day after making a visibility attempt, and positive affect was higher the day before making an attempt. Making visibility attempts in contexts that may have been more supportive (e.g., with friends, partners, and lesbian/gay individuals) was associated with more positive outcomes (e.g., more positive affect), while making attempts in contexts that may have been less supportive (e.g., with family, strangers, people who are unaccepting of bi+ identities, and heterosexual people) was associated with more negative outcomes (e.g., higher rejection sensitivity and more discrimination). These findings suggest that the contexts in which visibility attempts are made may play an important role in the impact that bi+ visibility attempts have on stigma-related stress and wellbeing.

This work addresses the task of risk evaluation in traffic scenarios with limited observability due to restricted sensorial coverage. Here, we concentrate on intersection scenarios that are difficult to access visually. To identify the area of sight, we employ ray casting on a local dynamic map providing geometrical information and road infrastructure. Based on the area with reduced visibility, we first model scene entities that pose a potential risk without being visually perceivable yet. Then, we predict a worst-case trajectory in the survival analysis for collision risk estimation. Resulting risk indicators are utilized to evaluate the driver's current behavior, to warn the driver in critical situations, to give suggestions on how to act safely or to plan safe trajectories. We validate our approach by applying the resulting intersection warning system on real world scenarios. The proposed system's behavior reveals to mimic the general behavior of a correctly acting human driver.

With intrinsic non-uniform illumination variations in laparoscopic images, such images often suffer from insufficient lighting and low visibility. This in turn may cause incorrect targeting, surgical risk, and extended operating time during laparoscopic surgery. Although various methods for nature image enhancement have been proposed in past decades, surgical laparoscopic image enhancement still needs improving due to issues including naturalness, blurred texture, color cast, and extensive computational time. To address these problems, this paper proposes a distributed Retinex optimization method for laparoscopic image enhancement using refined information fusion. The proposed method minimizes a distributed optimization model with l 2 -norm regularization terms, resulting in a low computational complexity. By integrating the refined image information into the optimization process, our method significantly enhances dark regions while preserving naturalness and texture structures. Experimental results show that our optimization algorithm is more effective than conventional enhancement algorithms in terms of vision augmentation, performance index, and computation time.

Global installed wind power capacity has risen nearly 4.3 times in the last decade, from 120.7 GW in 2008 to more than 591 GW in 2018. On the other hand, installed wind power capacity in Turkey was reported as 7.37 GW in 2018, and it is scheduled to reach 12 GW in 2023. The aim of this paper is to assess the recent growth of wind power generation in Turkey in terms of power generation technologies, wind power potential, techno-economic feasibility, and visibility of onshore wind turbines. In this respect, several metrics such as cumulative installed wind power capacity (MW), total number of turbines, total swept area of turbines (km2), total hub height of turbines (km), number of the turbine per turbine power capacity (1/GW), swept area per turbine power capacity (m2/MW) and hub height per turbine power capacity (m/MW) are developed to assess wind power generation regionally between the years of 2010 and 2018. Results show that wind power generation capacity is on the rise in Turkey. But this growth also implies an increase in the number and size of turbines. Eventually, turbines with higher hubs and rotor diameters have become more abundant and visible in landscapes.

Visibility observed at different altitudes is favorable to understand the causes of air pollution. We conducted 4-years of observations of visibility at 2.8 and 60 m and particulate matter (PM) concentrations from 2015 to 2018 in Shenyang, a provincial city in Northeast China. The results indicated that visibility increased with the increasing height in winter (especially at night), and decreased with height in summer (especially at the daytime). PM concentration exhibited opposite vertical variation to visibility, reflecting that visibility degrades with the increase of aerosol concentration in the air. The radiosonde meteorological data showed that weak turbulence in the planetary boundary layer (PBL) in winter favored aerosols’ accumulation near the surface. Whereas in summer, unstable atmospheric conditions, upper-level moister environment, and regional transport of air pollutants resulted in the deterioration of upper-level visibility. Inter-annual variation in the two-level visibility indicated that the upper-level visibility improved more significantly than low-level visibility, much likely due to the reduction in emission of elevated point sources in Shenyang. Our study suggested that strengthening the control of surface non-point emissions is a promising control strategy to improve Shenyang air quality.

Self-selection–based division of labor has gained visibility through its role in varied organizational contexts such as nonhierarchical firms, agile teams, and project-based organizations. Yet, we know relatively little about the precise conditions under which it can outperform the traditional allocation of work to workers by managers. We develop a computational agent-based model that conceives of division of labor as a matching process between workers’ skills and tasks. This allows us to examine in detail when and why different approaches to division of labor may enjoy a relative advantage. We find a specific confluence of conditions under which self-selection has an advantage over traditional staffing practices arising from matching: when employees are very skilled but at only a narrow range of tasks, the task structure is decomposable, and employee availability is unforeseeable. Absent these conditions, self-selection must rely on the benefits of enhanced motivation or better matching based on worker’s private information about skills, to dominate more traditional allocation processes. These boundary conditions are noteworthy both for those who study as well as for those who wish to implement forms of organizing based on self-selection.

A key goal of consciousness science is identifying neural signatures of being aware vs. unaware of simple stimuli. This is often investigated in the context of near-threshold detection, with reports of stimulus awareness being linked to heightened activation in a frontoparietal network. However, due to reports of stimulus presence typically being associated with higher confidence than reports of stimulus absence, these results could be explained by frontoparietal regions encoding stimulus visibility, decision confidence or both. In an exploratory analysis, we leverage fMRI data from 35 human participants (20 females) to disentangle these possibilities. We first show that, whereas stimulus identity was best decoded from the visual cortex, stimulus visibility (presence vs. absence) was best decoded from prefrontal regions. To control for effects of confidence, we then selectively sampled trials prior to decoding to equalize confidence distributions between absence and presence responses. This analysis revealed striking differences in the neural correlates of subjective visibility in prefrontal cortex regions of interest, depending on whether or not differences in confidence were controlled for. We interpret our findings as highlighting the importance of controlling for metacognitive aspects of the decision process in the search for neural correlates of visual awareness.Significance statementWhile much has been learned over the past two decades about the neural basis of visual awareness, the role of the prefrontal cortex remains a topic of debate. By applying decoding analyses to functional brain imaging data, we show that prefrontal representations of subjective visibility are contaminated by neural correlates of decision confidence. We propose a new analysis method to control for these metacognitive aspects of awareness reports, and use it to reveal confidence-independent correlates of perceptual judgments in a subset of prefrontal areas.

In this article, the image-based visual servoing (IBVS) problem for mobile robots with visibility constraints is studied by using a policy-based deep reinforcement learning (DRL) approach. First, the classical IBVS (C-IBVS) method and its feature-loss problem are introduced. Then, a DRL-based IBVS method is presented to solve the feature-loss problem and improve the servo efficiency.Specifically, the formulation of the C-IBVS controller is inherited by the designed controller to ensure the analytical stability, and a policy-based DRL algorithm is proposed to design an adaptive law for tuning the controller gain in the continuous space, which can maintain the feature in the field of the view of the camera as well as improving the servo efficiency. Finally, the effectiveness of the proposed method is demonstrated by various comparative experiments.

With the widespread diffusion of Massive Online Open Courses (MOOCs), educational recommender systems have become central tools to support students in their learning process. While most of the literature has focused on students and the learning opportunities that are offered to them, the teachers behind the recommended courses get a certain exposure when they appear in the final ranking. Underexposed teachers might have reduced opportunities to offer their services, so accounting for this perspective is of central importance to generate equity in the recommendation process. In this paper, we consider groups of teachers based on their geographic provenience and assess provider (un)fairness based on the continent they belong to. We consider measures of visibility and exposure, to account ( i ) in how many recommendations and ( i i ) wherein the ranking of the teachers belonging to different groups appear. We observe disparities that favor the most represented groups, and we overcome these phenomena with a re-ranking approach that provides each group with the expected visibility and exposure, thus controlling fairness of providers coming from different continents (cross-continent provider fairness). Experiments performed on data coming from a real-world MOOC platform show that our approach can provide fairness without affecting recommendation effectiveness.

Due to the complexity of real environment and potential defects of current simulation datasets, either prior-based or deep learning-based single image dehazing methods may not work well in certain scenarios. In this work, we propose an efficient joint contrast enhancement and exposure fusion (CEEF) framework to formulate image dehazing task as a local visibility and global contrast enhancement problem in lieu of solving time consuming minimization or training massive data. In the contrast enhancement stage, several intermediate images are generated through two pre-processing steps. Specifically, gamma correction (GC) is used to adjust local visibility of an input hazy image. To address the issue of applying adaptive histogram equalization (AHE) to each color channel independently, we explore the correlation among color channels and propose color-preserving AHE (CP-AHE) to improve global contrast of the input hazy image. In the fusion stage, we develop a fast structural patch decomposition-based fusion strategy with an adaptive kernel size to fuse the inputs obtained by GC and CP-AHE. Extensive experiments on the real-world datasets demonstrate the superiority of the proposed method against state-of-the-art methods in terms of visual and quantitative evaluation. Particularly for nighttime hazy scenes, our approach is capable of retaining fine details and reducing color artifacts against three latest nighttime defogging methods. Moreover, we discuss the potential application of our CP-AHE in low-light enhancement and image editing.

In practice, an increased interest into end-to-end visibility as a future-oriented driver and capability of resilient supply chains can be observed. However, the research in this area is in its infancy. Even less is understood about resilience and the potentials of a digital supply chain in pandemic settings. Based on an analysis of the relevant literature supplemented with the multiple case studies constructed with the use of primary data, we build a framework that could be instructive for supply chain managers seeking to manage resilience during pandemic disruptions and using digital technology. Our main methodological contributions are unlocking the value and potentials of end-to-end supply chain visibility for resilience management in the face of pandemic disruptions. We propose an associated design and implementation framework containing multiple dimensions—management, organizational, and technological. The outcomes of the article offer a conceptual guideline concerning the potentials and implementation of end-to-end visibility in the management of supply chain resilience.

Traffic visibility detection plays a vital role in intelligent transportation, autonomous driving, safe driving, etc. Convolutional neural networks (CNNs) based regression and classification algorithms have been shown competitive performance in many applications, but little attention has been paid to traffic visibility identification. In this paper, we propose a trainable end-to-end system called traffic visibility regression network (TVRNet). TVRNet takes a road image as input and outputs its visibility value. TVRNet adopts CNNs based deep architecture, uses appropriate filters to extract fog density-related features, and exploits the parallel convolution for multi-scale mapping. Later, a new type of non-linear activation function called Modified_sigmoid function is used. We synthesize labeled visibility datasets comprised of multi-scene and single-scene based on the actual road sense to train the visibility regression network. Extensive experiments and comparisons with other popular algorithms are performed to verify our method in road visibility estimation.

Achieving high rendering quality in the visualization of large particle data, for example from large-scale molecular dynamics simulations, requires a significant amount of sub-pixel super-sampling, due to very high numbers of particles per pixel. Although it is impossible to super-sample all particles of large-scale data at interactive rates, efficient occlusion culling can decouple the overall data size from a high effective sampling rate of visible particles. However, while the latter is essential for domain scientists to be able to see important data features, performing occlusion culling by sampling or sorting the data is usually slow or error-prone due to visibility estimates of insufficient quality. We present a novel probabilistic culling architecture for super-sampled high-quality rendering of large particle data. Occlusion is dynamically determined at the sub-pixel level, without explicit visibility sorting or data simplification. We introduce confidence maps to probabilistically estimate confidence in the visibility data gathered so far. This enables progressive, confidence-based culling, helping to avoid wrong visibility decisions. In this way, we determine particle visibility with high accuracy, although only a small part of the data set is sampled. This enables extensive super-sampling of (partially) visible particles for high rendering quality, at a fraction of the cost of sampling all particles. For real-time performance with millions of particles, we exploit novel features of recent GPU architectures to group particles into two hierarchy levels, combining fine-grained culling with high frame rates.

Interactions of group-living primates range from cooperation to competition. Many corresponding real-world decisions critically depend on observing partner9s actions. In classical game theory studies, however, agents act without knowing the partner9s choices. To overcome these limitations, we developed a setup where two agents engage face-to-face in cooperative or competitive tasks on a shared transparent touchscreen display ("transparent games"), ensuring mutual action visibility. We compared human and macaque pairs in a transparent version of the coordination game "Bach-or-Stravinsky", which entails the conflict about which of the two individually-preferred coordinated options to choose. Most human pairs developed coordinated behavior and adopted dynamic turn-taking to equalize the payoffs. All macaque pairs also converged on coordination, but in simpler, static ways. Remarkably, two animals that underwent training with a human confederate learned to coordinate dynamically, exhibiting turn-taking driven by temporal competition. The observed choices were captured by modeling the probability to see the other9s action before one9s own movement. Such competitive turn-taking is unlike the prosocial turn-taking in humans, who equally often initiated switches to and from their preferred option. Our results show that dynamic coordination is not restricted to humans, but it can be subserved by different social attitudes, and emphasize the importance of action visibility in studies of the emergence and maintenance of coordinated behavior.

This paper summarises two different approaches using technology to support young children's collaborative interaction in a classroom setting. KidPad, a 2 1/2D drawing package with zooming capabilities, was adapted for use with multiple mice and tangible interfaces. The first section of the paper focuses on a study carried out to evaluate the effect of multiple mice on children's collaborative behaviour at a desktop computer. Positive effects of the use of two mice included symmetry of mouse use amongst pairs and a greater degree of engagement in the task. However a number of usability issues were identified when children attempted to collaborate, particular problems were faced when the shared control was taken away, and one of the users took control, for example, when navigating. Different types of working styles were also evident between the one mouse and two mice conditions. The second section of the paper describes a move away from the desktop computer towards room-based technologies. Tangible interfaces to KidPad were developed in order to facilitate shared control over actions such as navigation where difficulties had been identified in a desktop situation. The visibility of action is highlighted as a fundamental element in the support of collaboration on a larger scale. Finally, future work and the potential of these technologies in encouraging shareable co-present interaction in a real school context are briefly discussed.

Publisher Summary With image enhancement, the visibility of selected features in an image can be improved, but the inherent information content cannot be increased. The design of a good image enhancement algorithm should consider the specific features of interest in the microscopic image and the imaging process itself. The image enhancement algorithms can be classified into two categories: spatial domain methods and transform domain methods. The spatial domain methods include operations carried out on a whole image or on a local region selected on the basis of image statistics. Techniques that belong to this category include histogram equalization, image averaging, sharpening of important features such as edges or contours, and nonlinear filtering. The transform domain enhancement methods manipulate image information in transform domains, such as Fourier and wavelet transforms. Often, interesting image information cannot be separated out in the spatial domain but can be isolated in the transform domain. For example, one can amplify certain coefficients in the Fourier domain and then recover the image in the spatial domain to highlight interesting image content. The wavelet transform is another powerful tool that has been developed in recent years and used for image enhancement.

This article examines the interplay between the European Union's (EU) interventions fostering LGBT+ rights in Georgia, and the visibility-raising strategies of local queer activists. The growing antagonism between the EU and Russia over their "shared neighborhood" crystallizes the idea of a value-based divide between the West/EUrope and the East/Russia on LGBT+ issues-with Georgia occupying a liminal position therein. The paper puts forward the concept of geopoliticization to unpack how the discursive construction of LGBT+ equality as a geopolitical issue shapes Georgian queer activists' visibility strategies, and to interrogate the outcomes these processes produce.

Recently, firms in supply chains have begun to deploy popular mobile apps (e.g., WeChat) into their supply chain practices to improve demand visibility. These efforts rely on consumers to scan the products they purchase using these apps, which we refer to as consumer scanning technology (CST). CST can be an alternative to the conventional interorganizational information technology (IOIT) that relies on collaboration between supply chain firms. This paper develops a theoretical model to examine the value of CST to learn supply chain (demand) information and the impact of CST on IOIT. Using an extensive simulation analysis based on real-world data from a manufacturer that has implemented a CST program, we show that the value of CST to a manufacturer can be substantial and provide insights into how market conditions affect the value.

In the present paper, an efficient mesh-free approach is established to determine the stress intensity factors in the vicinity of the crack tip. This efficient mesh-free approach is based on the Weighted Least Squares method (WLS) combined with the stresses extrapolation method and with the visibility criterion to evaluate the Stress Intensity Factors (SIFs). This approach is applied on a strong formulation to avoid the technique of numerical integration and this permits us to compute the stresses with accuracy with the help of the collocation method. The accuracy and the robustness of the proposed approach are tested on several benchmarks in Linear Elastic Fracture Mechanics (LEFM). The obtained results have demonstrated that this approach is very accurate and stable even for complex problems and it can be an alternative way for the computation of SIFs.

This article presents a fixed-time leader–follower formation control protocol for a swarm of unicycle-type mobile robots with visibility and performance constraints. Under a vision-based formation control framework, mobile robots calculate their control signals with only the local relative distance and bearing angle provided by onboard stereo or RGB-D cameras. Since the sensing capability of the fixed onboard cameras is subject to limited range and angle of view, the field-of-view constraints are considered to ensure that each follower can always detect its leader and meanwhile avoid collision with the leader. The time-varying and asymmetric performance constraints on formation tracking errors are applied to guarantee the transient and stead-state performance. Furthermore, the proposed control protocol can be extended to address the control design problem without constraint requirements. Based on the fixed-time control design and Lyapunov analysis, formation tracking errors are shown to converge to a small neighborhood of zero in fixed settling time. Simulation and experiment studies are performed to illustrate the effectiveness of the formation control protocol.

Objectives Virtual-assisted lung mapping (VAL-MAP) is a bronchoscopic marking method of dye application on the surface of the lungs before resecting nonpalpable nodules. However, in some cases, it can be difficult to identify the markings of VAL-MAP on computed tomography and intraoperative thoracoscopy. We developed and assessed the feasibility of indocyanine green VAL-MAP (ICG-VAL-MAP). Methods A historical control trial was conducted to investigate the effectiveness of ICG-VAL-MAP for marking visualization compared with that of VAL-MAP. In ICG-VAL-MAP, instead of indigo carmine, ICG and computed tomography contrast agents were used for dye marking, and near-infrared fluorescence endoscopy was employed to visualize the ICG markings. The other processes in VAL-MAP were carried out. The marking visibility was assessed in 3 grades of easy, faint, or not identifiable. We compared the visibility of the markings on computed tomography images and during thoracoscopic operations between VAL-MAP (567 markings in 147 cases) and ICG-VAL-MAP (142 markings in 63 cases). Results On the preoperative computed tomography images, ICG-VAL-MAP provided significantly better marking visualization than VAL-MAP (easy/faint/not identifiable = 142/0/0 vs 427/100/30; P, Graphical abstract Comparison of marking visibility between VAL-MAP and ICG-VAL-MAP. ICG-VAL-MAP showed significantly better marking visualization on preoperative CT and during thoracoscopic surgery than VAL-MAP.

Visibility is a key factor influencing animal behavior in forest ecosystems. Fine-scale visibility in forested areas has been measured by ground-based approaches at the plot level, using site-specific methods that have limited spatial coverage. Here we examine airborne laser scanning (ALS) as a novel tool to quantify fine-scale visibility in the temperate forests of Germany at a landscape scale. We validate the (vertically-derived) ALS-derived visibility measures using proven (horizontally-derived) terrestrial laser scanning (TLS) estimates of true visibility. Our results indicate that there is a good agreement between the visibility resulting from ALS and TLS with an R2 ranging from 0.53 to 0.84 and a normalized RMSE varying from 15.92% to 11.81% at various plot sizes, with the highest accuracy achieved using a plot size of 35 × 35 m. Our study demonstrates for the first time that ALS can be successfully applied to quantify fine-scale visibility in temperate forests at a landscape level. This approach holds potential for studying the spatial behavior of animals (e.g., habitat selection and predator–prey relationships) in forest ecosystems.

Recently, Low Earth orbit (LEO) satellite-based systems have attracted tremendous attention and various technologies have been developed for payload miniaturization and optical communications. In addition, mega constellation architectures are expected to be deployed with LEO satellites for global broadband networks. In this paper, we present a thorough analysis of mega constellation architecture in terms of a change in the number of visible satellites and antenna steering capability to investigate the impact of increase in the constellation size and adoption of optical inter-satellite links (ISLs). The network architecture is evaluated with respect to satellite antenna steering capability and the satellite visibility considering the very narrow beam divergence of optical communications. We analyze the impact of a change in relative positions among the satellites due to continuous satellite movement in the constellation. The results offer guidelines for designing a novel visibility matrix using a time-varying satellite topology. This could defuse the problem of conventional studies using fixed visibility matrices. The proposed time-varying visibility matrix achieves better performance than previous pre-assigned links in terms of end-to-end link distance and hop count of LEO satellite networks.

Como forma de ampliar a visibilidade e divulgação das produções acadêmicas e científicas, algumas instituições de ensino passaram a fazer uso de Repositórios Institucionais (RI), ferramentas tecnológicas que surgiram a partir do movimento mundial de acesso aberto à informação científica. Este trabalho apresenta como objeto de estudo o cenário de implantação de Repositórios nos Institutos Federais de Educação, Ciência e Tecnologia (IF) com marco temporal até maio de 2020. Trata-se de uma pesquisa bibliográfica de caráter qualitativo. Foi realizado o mapeamento para identificar quais IF possuíam Repositório Institucional. A coleta de dados aconteceu por meio de consulta em sites institucionais, envio de e-mails ao grupo de bibliotecários da Rede brasileira de Institutos Federais e coleta de informações por meio do Sistema Eletrônico do Serviço de Informação ao Cidadão (e-SIC). Identificou-se que das 38 instituições pesquisadas 15 já possuem Repositório Institucional e outras 15 estão em fase de implantação. Acredita-se que a implantação de repositórios nos IF ainda precisa avançar significativamente para proporcionar maior visibilidade às suas produções acadêmicas, técnicas e científicas.

The paper examines communication and visibility (C&V) aspect in the operations of the EU Delegation in Saudi Arabia and the GFA Consulting Group. The author assumes that properly designed communication using adequate contents may significantly affect the EU external relations. To verify this statement, the twofold approach was used. First, through the lens of Soft Power and EU actorness, it looks into the theoretical dimension of the international relations and its possible links with communication process. Second, drawing on existing internal EU documents (Communication and Visibility in EU-financed External Actions – Requirements for Implementing Partners 2018 by the EU Delegation in Saudi Arabia, and Information and Communication Handbook for EU Delegations in the Third Countries and International Organizations, published in 20122) the paper offers analytical framework to explore the qualitative and quantitative nature of the online communication undertaken in social media platform both by the EU Delegation in Saudi Arabia and the GFA.

20 years after the issue of Ordonnance 92/2000 which was establishing the need to provide services for the social reintegration of offenders and supervision for non-custodial sanctions, called from 2006 probation services, a national study was carried out on the visibility of probation system among citizens. The respondents were all the probation services Chiefs in the country and their opinion confirmed the hypothesis that the National Probation System, ignoring the recommendations of the Committee of Ministers of European Council, don't have a promoting strategy nither the concern for creating a recognizable image among the other actors involved in the justice act. Consequently, the field has so far failed to gain full consideration within the Romanian Criminal Justice System and visibility among citizens, although after 2014 when the New Criminal Code started to be applied, the number of offenders attended by probation services was tripled and the staff's attributions war extended. The article is structured in two parallel planes, first showing the social and economic benefits of alternative detention measures supervised by probation services in the light of the costs of incarceration and the second showing the unfair lack of visibility of these benefits and the unknown activity carried out by probation counselors for the social reintegration of offenders.

International audience; 5G technology enables end-to-end connectivity in real time at a highly granular level along with the associated end-to-end visibility through the Internet-of-Everything. While some potential benefits of 5G for digital supply chain and operations management have been declared, literature is still silent about theoretical underpinning and structured conceptualisation of application areas, underlying implementation challenges, and the role of 5G in future transformations of value creation. This paper aims to offer some directions of how to close this research gap. We organise the discussion around five major capabilities of the digital supply chain and smart operations which can be enhanced by 5G, i.e. intelligence, visibility, transparency, dynamic networking, and connectivity. We delineate possible future research topics related to 5G in different areas of Industry 4.0-driven, digital supply chain and operations management which can be useful for researchers and practitioners alike when seeking to understand the impact of 5G on both short-term and long-term time scales. Our analysis encompasses both operational processes (e.g. transformations of manufacturing and warehouse operations by end-to-end connectivity of devices) and strategic perspectives (e.g. transformations of business models and supply network structures through end-to-end real-time visibility and connectivity of industry, public infrastructure, and consumers). Finally, cost-benefits trade-offs are discussed.

During the first part of the millennium some of the most visible media images of large Black women in American media were of Black actors wearing fat suits playing fat Black women in comedic roles ...

Asian American women’s beauty practices have been doubly pathologized – not only being stereotyped as passive, dull, unattractive, and foreign, but also stigmatized as non-normative, uneducated, se...

Due to the attenuation of light passes through water, the captured underwater images suffer from low-contrast, halo artifacts, etc. To address this issue, the hybrid network with a weighted filter is proposed to improve the visibility of the obscured (turbid) images. In the captured image, the brighter pixels (near-to-source) are called foreground regions and the darker pixels (far-from-source) are called background regions. In order to ensure the adaptability of the proposed algorithm, the considered datasets are collected on different atmospheric light such as pond, lake, and fisheries tank. The foreground area of an image can be enhanced using the thresholding and masking technique. The background hazy region can be recovered by a hybrid Dehazenet called Generative Adversarial Network and Convolutional Neural Network. With this, the transmission map with high accuracy and color deviation can be addressed. Then both the regions are blended and the Amended Unsharp Mask filter is used to toughen the distorted edges. Finally, the blended restored image is weighted with a contrast factor to obtain the visibility improved image. The subjective and objective evaluation is done on considering the standard non-reference metric called Underwater Image Quality Measure comprises measures of color, sharpness, and contrast for a variety of water types with different atmospheric light. It is observed that the proposed technique showed a metric improvement of 57% compared to other existing techniques in an average manner. Overall, it is inferred that the proposed technique produces better results in both subjective and objective evaluation, thus it outperforms other state-of-the-art techniques.

In future years, airline companies will be leaning more and more towards cryptocurrencies to implement their digital marketing strategies as leaders seek to gain an understanding of the factors affecting airlines’ visibility parameters. Cryptocurrency investment websites are currently experiencing rising demand, making them an appropriate site for paid advertisements. The above factors suggest the need for airlines to harvest cryptocurrency investment and platform users in their favour. To this end, it can be beneficial for airlines’ web promotions to link certain web analytics metrics to cryptocurrency trading site metrics. For research purposes, web analytics data were monitored and gathered for 2 consecutive years from 10 globally leading cryptocurrency trading companies and 10 airline websites. A three-stage model was adopted by the authors. In the first stage, statistical analysis was implemented using cryptocurrency and airline metrics, followed by fuzzy cognitive mapping and agent-based modelling stages. The findings of the study indicate that engagement with cryptocurrency trading websites has a positive impact on airline websites’ global ranking and visibility parameters. The outcomes of this research provide noteworthy digital marketing strategies which can be addressed by airline companies to increase their website visitors and optimise visibility parameters with the assistance of cryptocurrency trading websites.

Distinguishing high-performing employees imposes choices on managers: Is recognition most effectively delivered publicly or privately? If delivered publicly, what setting is best? This paper broadens the accounting literature on the implications of these decisions. Via experiment, I examine how the social bond between recognized employees and those observing the recognition influences the effect of recognition visibility on employee behavior. I find that with weak social bonds, public recognition (versus private) does not result in more beneficial employee behavior. However, when social bonds are strong, employees provide greater pre-recognition effort and respond more positively to public recognition than to private recognition. Overall, my study supports the extensive use of public recognition in practice and helps clarify the collective results from prior accounting studies. My findings also have implications for implementing recognition programs—suggesting managers should consider employee relationships when deciding how and where to recognize their employees.

Background: Radiographic visibility of the root pulp in lower third molars is one of the reliable methodologies for chronological age estimation. Objective: To evaluate the radiographic visibility of the lower third molar root pulp using digital panoramic radiographs of the Thai population, and determine the appropriation of this technique in age assessment, especially at the age of 18 years. Methods: A total of 746 digital panoramic radiographs of the Thai population aged from 16 to 26 years were recruited for the present study. The visibility of root pulp of lower third molars with completed root formation was recorded in the four stages. Descriptive statistics were performed for each stage in both males and females. Results: The first appearance of stage 0 is 16.71 years in males and 17.00 years in females. The minimum age of stage 1 was found at 17.08 years in males and 17.18 years in females. The beginning of stage 2 was 18.33 years in males and 18.17 years in females. For stage 3, the earliest presence was started at 18.58 years in males and 18.83 years in females. Conclusion: The occurrence of stages 2 or 3 in both males and females indicated that the subject is over 18 years of age. Further study on the Thai population should be conducted to confirm the results of the present study.

Waterfalls are documented among Indigenous peoples as settings for the intergenerational transfer of knowledge and locations sacred to life transitions. Eastern Woodlands ethnographic literature identifies waterfalls as places where life emerges in the presence of danger, requiring the acknowledgement of those who travel near them. In the Virginia Blue Ridge Mountains, ceramic-bearing Middle and Late Woodland sites near named waterfalls are associated with small sites located outside the topographic parameters of modeled site locations and containing non-local or unique objects. Sound mapping with calibrated decibel meters, survey-grade GPS, and inverse distance weighted interpolation demonstrate a correspondence between the location of the small sites and natural sound magnification. The small sites and the deposited objects may represent the offerings of travelers made aware of the sacred/dangerous place by the sound of the waterfall. Acoustic archaeology is introduced as a practice that takes into consideration sensory experience as central to place identity.

This study estimated the levels of atmospheric turbidity in Ile-Ife, a tropical location in the Southwest of Nigeria, from November, 2017 to March, 2019. This was with the aim to quantify the degree of atmospheric cleanliness of the study location. The methods of estimation used are: the Angstrom turbidity parameters (α and β), Linke turbidity factor (TL) and horizontal visibility (VH). The values of α and β range between 0.6 and 1.4; 0.10 and 0.91 respectively. The values obtained for TL varied between 1 and 7 while visibility values ranged between 2 and 14 km. Maximum values of β and TL (corresponding to low values of VH) were obtained in the dry season (particularly in the months of January and February) while the lowest values of the same methods of estimation (corresponding to high values of VH) were recorded in the wet season (specifically in August and September). The elevated turbidity observed in the dry season was linked to episodes of Harmattan dust storms usually experienced at the study location. The study concluded that a polluted atmosphere dominates the study location especially in the dry season as indicated by the different atmospheric turbidity parameters.

In the current context generated by the ubiquity of digital technologies in all aspects of socio-economic life, the NGOs that succeed in integrating smart tools into their development strategies are those that have a high chance of adapting, transforming and being resilient to digital transformation. The digital strategy is an integral part of the NGO's strategic development plan, continuously adapting and developing with the changes brought by new technologies in society. The article explains how NGOs, with a cohesive plan for adapting and integrating smart technologies into development strategies, can successfully achieve their cause. In the elaboration of the digital strategy, the management will have as a starting point the finding of answers to the questions: Why is this wanted? and How will this vision be achieved? The author believes that the paper can serve as a guide for the adoption of digital technology by other NGOs at the beginning of the road in order to promote the cause for which it advocates, but also to reduce costs

Code-modulated interferometry (CMI) enables a lens-less approach to imaging in which incoming signals are code modulated, combined, and processed through a shared hardware path; visibility functions are demodulated from an aggregate power-detected response; and an image is obtained using an inverse Fourier transform of the visibility samples. CMI allows the imager to be constructed using low-cost conventional beamforming hardware. This article presents the theory of operation of a code-modulated interferometer array intended for active imaging. This includes the selection of codes, the use of phase shifters for modulation, the demodulation of visibility functions, the necessary calibration, and the image processing. The architecture and design of an active imaging prototype is then presented, where it is created using a commercially available 16-element 8–16 GHz beamforming receiver along with a sparse antenna array that generates 169 distinct visibility samples. The imaging capabilities are demonstrated through the detection of multiple point sources at 10 GHz. Finally, the feasibility of creating a larger 64-element imager with 961 visibility samples is demonstrated through construction and measurements of a single row within that array.

Ultrasound-guided, lymph node, fine-needle aspiration cytology is important in diagnosing axillary lymph node metastasis in breast cancer. However, poor needle visibility can render the procedure difficult. We describe a case in which state-of-the-art enhancement techniques using matrix linear probes can provide better needle visibility and improve the certainty and efficiency of the examination.

Contribution: This article confirms the continued marginalization of undergraduate LGBTQ+ electrical and computer engineering (ECE) students and describes how they navigate their (non)visibility in engineering. Best practices to increase diversity and inclusion are discussed. Background: LGBTQ+ ECE undergraduate students experience a chilly, sometimes hostile climate in engineering. As a result, they experience lower sense of belonging, worse academic outcomes, and greater mental and emotional stress in their daily lives. Research Questions: How are LGBTQ+ ECE undergraduate students’ perceptions of ECE culture, sense of belonging, perceptions of discrimination, and (non)visibility affected by their identities? How do they navigate their (non)visibility in engineering contexts? How do LGBTQ+ ECE undergraduate students perceive and navigate engineering culture and their (non)visibility in engineering spaces, potentially integrating LGBTQ+, race, ethnicity, gender, and other identities into their perceptions? Methodology: A mixed-methods study with a survey and focus groups was conducted at a large southern public university in the United States. Survey participants included 854 undergraduate ECE students, of which 9% were strongly LGBTQ+. Focus group participants included 9 self-selected LGBTQ+ ECE students from the survey sample. Findings: LGBTQ+ ECE undergraduate students face noninclusive environments, marginalizing experiences, and cis-heteronormativity in engineering as a result of their multiple marginalized identities that intersect with their LGBTQ+ identity.

It is established numerically that an area of small delay distances limited by the value Ldel-gr, where the spatialenergy profile of the recorded signal has the shape of a convex asymmetric curve with a maximum shifted toward the beginning of the visibility zone, can be selected when an active-pulse vision system registers signals from a diffusely reflecting underlying surface along inclined lines of sight. The value of Ldel-gr depends on the duration of the illumination and strobe pulses. The value of Ldel-gr for a cooperative object (equipped with retroreflectors) coincides with the value previously set for horizontal observation lines. The widths of the visibility zones for cooperative and diffuse objects increase with an increase in the delay distance, tending toward a certain limiting value depending on the duration of the illumination and strobe pulses. The visibility angle in the vertical plane is determined by the duration of the illumination and strobe pulses and the delay distance and height of the vision system installation when observing on inclined lines of sight.

In recent years, transgender people have both grown in numbers and visibility in the united states. However, the issue of discrimination against transgender people has been a serious and widespread phenomenon in today's society. This paper discusses the transgender issues at large and how the issues negatively affect transgender students' college experiences in a variety of ways, including but not limited to institutions' failure to include "gender identity" in their nondiscrimination policies. The evidence from scholarly sources also suggests that religiously affiliated, single-sex and two-year colleges typically offer few protections for transgender students. Finally, the paper will examine institutions' past initiatives on the subject matter and provide recommendations for institutions to create a more gender-friendly environmnent.

Intelligent transportation systems (ITS) have become a popular method for enhancing transportation safety and efficiency. As essential participants of ITS, autonomous vehicles need to detect pedestrians accurately. In this paper, we propose a one-stage anchor-free pedestrian detection model named Bi-Center Network (BCNet), which is aided by the semantic features of pedestrians’ visible parts. We perform an ablation study to discover how visibility features could benefit the detector’s performance, including introducing two hyper-parameters and adopting three different attention mechanisms, respectively. The experimental results indicate that the performance of pedestrian detection could be significantly improved, since the visibility semantic could prompt stronger responses on the heatmap. We compare our BCNet variants with state-of-the-art models on the CityPersons dataset and ETH dataset; results indicate that our detector is effective and achieves a promising performance.

We present a new approach for redirected walking in static and dynamic scenes that uses techniques from robot motion planning to compute the redirection gains that steer the user on collision-free paths in the physical space. Our first contribution is a mathematical framework for redirected walking using concepts from motion planning and configuration spaces. This framework highlights various geometric and perceptual constraints that tend to make collision-free redirected walking difficult. We use our framework to propose an efficient solution to the redirection problem that uses the notion of visibility polygons to compute the free spaces in the physical environment and the virtual environment. The visibility polygon provides a concise representation of the entire space that is visible, and therefore walkable, to the user from their position within an environment. Using this representation of walkable space, we apply redirected walking to steer the user to regions of the visibility polygon in the physical environment that closely match the region that the user occupies in the visibility polygon in the virtual environment. We show that our algorithm is able to steer the user along paths that result in significantly fewer resets than existing state-of-the-art algorithms in both static and dynamic scenes. Our project website is available at https://ganuna.umd.edu/vis.poly/ .

Certificate Transparency is a maturing system to provide visibility into the certificates that are issued as part of the web’s public key infrastructure. In this article, we survey the history of Certificate Transparency deployment so far and discuss ongoing engineering and research challenges.