Aim/Purpose: Medical images are very sensitive data that can be transferred to medical laboratories, professionals, and specialist for referral cases or consultation. Strict security measures must be utilized to keep these data secured in computer networks when transferred to another party. On a daily basis, unauthorized users derive ways to gain access to sensitive patient medical information. Background: One of the best ways to which medical image could be kept secured is through the use of quantum cryptography Methodology : Applying the principles of quantum mechanics to cryptography has led to a remarkable new dimension in secured network communication infrastructure. This enables two legitimate users to produce a shared secret random bit string, which can be used as a key in cryptographic applications, such as message encryption and authentication. Contribution: This paper can make it possible for the healthcare and medical professions to construct cryptographic communication systems to keep patients’ transferred data safe and secured. Findings: This work has been able to provide a way for two authorized users who are in different locations to securely establish a secret network key and to detect if eavesdropping (a fraudulent or disruption in the network) has occurred Recommendations for Practitioners: This security mechanism is recommended for healthcare providers and practitioners to ensure the privacy of patients’ medical information. Recommendation for Researchers: This paper opens a new chapter in secured medical records Impact on Society Quantum key distribution promises network security based on the fundamental laws of quantum mechanics by solving the problems of secret-key cryptography . Future Research: The use of post-quantum cryptography can be further researched.

Aim/Purpose. This study examined the self-perception of adolescents and young people aged 17-21 – how they perceived their personal characteristics, self-image, vitality, belonging to a local and global (glocal) society, happiness index and activity, media usage habits in general and smartphones in particular – in other words, it sought to produce a sketch of their character. Background. Different age groups are influenced by various factors that shape them, including living environment, technological developments, experiences, common issues, events of glocal significance, and more. People belonging to Gen Z were born at the end of the previous century and the beginning of the 21st century (up to 2010). This generation was born into the digital technological age and is the first one born into the environment defined by smartphones, and social media. Its members are referred to as “digital natives” because they were born after the widespread adoption of digital technology in the Western world. They entered an environment characterized by the widespread daily use of smartphones, the Internet, and technology in general. Methodology. This was a quantitative study based on a sample of 418 Israeli adolescents and young people aged 17-21. The following questionnaires were administered anonymously and disseminated online to an audience of youths aged 17-21 across Israel: A demographic questionnaire; Self-esteem; Vitality; Belonging vs. alienation; Social-emotional aspects; Usage habits in digital environments; Usage habits of learning on a smartphone; Open questions. Contribution. The current study tried to define clusters to characterize adolescents and youth aged 17-21. Findings Results show that study participants had high self-esteem and vitality, felt be-longing, happy, and satisfied with their life, and perceived themselves as active and enterprising at an average level or above. The study identified two clusters. Participants in Cluster 1 were characterized by higher parameter averages than those in Cluster 2 on the self-image, vitality, belonging, happiness, and activism scales. Participants in Cluster 1 felt that using a smartphone made life easier, helped them solve everyday problems, made everyday conduct easier, and allowed them to express themselves, keep up to date with what is happening with their friends, disseminate information conveniently, be involved in social life, and establish relationships with those around them. They thought that it was easy to collaborate with others and to plan activities and events. Recommendations for Practitioners. When examining cluster correlations with data in relation to other variables, it is apparent that participants in Cluster 1 had more options to reach out for help, report more weekly hours spent talking and meeting with friends and feel that using a smartphone makes everyday life easier and facilitates their day-to-day conduct than did participants in Cluster 2. The smartphone allows them to express themselves, keep updated regarding what is happening with their friends and disseminate information easily, helps them be involved in social life and establish connections with those around them. They find it easy to communicate and cooperate with others and to plan activities and events. By contrast, participants in Cluster 2 felt that the smartphone complicates things for them and creates problems in their daily lives. They feel that the use of social networks burdens them and that the smartphone prevents them from being more involved in their social life, and from establishing relationships with those around them. They felt that communication by smartphone creates more problems in understanding messages. Recommendations for Researchers. One of the challenges of this generation is forming an independent identity and self-regulation in a digital, global, across-the-border era that offers a variety of possibilities and communities. They must examine the connection between the digital and personal spaces, to be able to enjoy virtual communities and a sense of togetherness, and at the same time maintain privacy, autonomy, and individuality. Many studies point to the blurring of boundaries between the private-personal and the public, at numerous problems in social networks, including social problems, shaming, and exclusion from various groups and activities. The fear of shaming and the desire to keep up with everything that is happening create a state of mental stress, and adolescents often feel that they urgently need to check their smartphones. Sharing with others can help them deal with negative content and experiences and avoid the dangers lurking in their web surfing. Yet sharing, especially with friends, often causes intimate content to become public and leads to shaming and invasion of privacy. Impact on Society. Gen Z was born into an environment where smartphones, the Internet, and technology in general, are widely used in everyday routine, and they make extensive use of technological means in all areas of life. One of the characteristics of this generation is “globalization.” The present study showed that about 84% of participants felt to a moderate degree or higher that they were citizens of the world. Future Research. The findings of this study revealed a significant difference in self-image between males and females. An attempt was made to explain the findings in light of previous studies, but the need arose for studies on the self-image of young people of Gen Z that would shed light on the subject.

Breast cancer is leading cause of mortality among women compared to other types of cancers. Hence, early breast cancer diagnosis is crucial to the success of treatment. Various pathological and imaging tests are available for the diagnosis of breast cancer. However, it may introduce errors during detection and interpretation, leading to false-negative and false-positive results due to lack of pre-processing of it. To overcome this issue, we proposed a effective image pre-processing technique-based on Otsu's thresholding and single-seeded region growing (SSRG) to remove artefacts and segment the pectoral muscle from breast mammograms. To validate the proposed method, a publicly available MIAS dataset was utilised. The experimental finding showed that proposed technique improved 18% breast cancer detection accuracy compared to existing methods. The proposed methodology works efficiently for artefact removal and pectoral segmentation at different shapes and nonlinear patterns.

Aim/Purpose: In this paper, we address the theoretical challenges today’s scientific community faces to precisely draw lines between true and false pictures. In particular, we focus on problems related to the hidden wonders of science and the shiny images produced for scientific papers or to appeal to wider audiences. Background: As rumors (hoaxes) and false news (fake news) explode across society and the current network, several initiatives using current technology have been launched to study this phenomena and limit the social impact. Over the last two decades, inappropriate scientific behavior has raised more questions about whether some scientific images are valid. Methodology: This work is not about analyzing whether today’s images are objective. Instead, we advocate for a general approach that makes it easier to truly believe in all kinds of knowledge, scientific or otherwise (Goldman, 1967; Goldman, & Olson, 2009). This need to believe is closely related to social order (Shapin, 1994). Contribution: We conclude that we must ultimately move away from older ideas about truth and objectivity in research to broadly approach how science and knowledge are represented and move forward with this theoretical approach when communicating science to the public. Findings: Contemporary visual culture suggests that our world is expressed through images, which are all around us. Therefore, we need to promote the reliability of scientific pictures, which visually represent knowledge, to add meaning in a world of complex high-tech science (Allamel-Raffin, 2011; Greenberg, 2004; Rosenberger, 2009). Since the time of Galileo, and today more than ever, scientific activity should be understood as knowledge produced to reveal, and therefore inform us of, (Wise, 2006) all that remains unexplained in our world, as well as everything beyond our senses. Recommendation for Researchers: In journalism, published scientific images must be properly explained. Journalists should tell people the truth, not fake objectivity. Today we must understand that scientific knowledge is mapped, simulated, and accessed through interfaces, and is uncertain. The scientific community needs to approach and explain how knowledge is represented, while paying attention to detail. Future Research: In today’s expanding world, scientific research takes a more visual approach. It is important for both the scientific community and the public to understand how the technologies used to visually represent knowledge can account for why, for example, we know more about electrons than we did a century ago (Arabatzis, 1996), or why we are beginning to carefully understand the complexities and ethical problems related to images used to promote knowledge through the media (see, i.e., López-Cantos, 2017).

This work demonstrates a hybrid deep learning (DL) model for lung cancer (LC) detection using CT images. Firstly, the input image is passed to the pre-processing stage, where the input image is filtered using a BF and the obtained filtered image is subjected to lung lobe segmentation, where segmentation is done using squeeze U-SegNet. Feature extraction is performed, where features including entropy with fuzzy local binary patterns (EFLBP), local optimal oriented pattern (LOOP), and grey level co-occurrence matrix (GLCM) features are mined. After completing the extracting of features, LC is detected utilising the hybrid efficient-ShuffleNet (HES-Net) method, wherein the HES-Net is established by the incorporation of EfficientNet and ShuffleNet. The presented HES-Net for LC detection is investigated for its performance concerning TNR, and TPR, and accuracy is established to have acquired values of 92.1%, 93.1%, and 91.3%.

Lihan TONG,Weijia LI,Qingxia YANG,Liyuan CHEN,Peng CHEN, Vol.E107-D, No.11, pp.1472-1475
We present Ksformer, utilizing Multi-scale Key-select Routing Attention (MKRA) for intelligent selection of key areas through multi-channel, multi-scale windows with a top-k operator, and Lightweight Frequency Processing Module (LFPM) to enhance high-frequency features, outperforming other dehazing methods in tests.
Publication Date: 2024/11/01

Qinghua WU,Weitong LI, Vol.E107-D, No.11, pp.1422-1432
Multi-focus image fusion involves combining partially focused images of the same scene to create an all-in-focus image. Aiming at the problems of existing multi-focus image fusion algorithms that the benchmark image is difficult to obtain and the convolutional neural network focuses too much on the local region, a fusion algorithm that combines local and global feature encoding is proposed. Initially, we devise two self-supervised image reconstruction tasks and train an encoder-decoder network through multi-task learning. Subsequently, within the encoder, we merge the dense connection module with the PS-ViT module, enabling the network to utilize local and global information during feature extraction. Finally, to enhance the overall efficiency of the model, distinct loss functions are applied to each task. To preserve the more robust features from the original images, spatial frequency is employed during the fusion stage to obtain the feature map of the fused image. Experimental results demonstrate that, in comparison to twelve other prominent algorithms, our method exhibits good fusion performance in objective evaluation. Ten of the selected twelve evaluation metrics show an improvement of more than 0.28%. Additionally, it presents superior visual effects subjectively.
Publication Date: 2024/11/01

Zhigang WU,Yaohui ZHU, Vol.E107-D, No.11, pp.1385-1395
This article focuses on improving the BiSeNet v2 bilateral branch image segmentation network structure, enhancing its learning ability for spatial details and overall image segmentation accuracy. A modified network called “BiconvNet” is proposed. Firstly, to extract shallow spatial details more effectively, a parallel concatenated strip and dilated (PCSD) convolution module is proposed and used to extract local features and surrounding contextual features in the detail branch. Continuing on, the semantic branch is reconstructed using the lightweight capability of depth separable convolution and high performance of ConvNet, in order to enable more efficient learning of deep advanced semantic features. Finally, fine-tuning is performed on the bilateral guidance aggregation layer of BiSeNet v2, enabling better fusion of the feature maps output by the detail branch and semantic branch. The experimental part discusses the contribution of stripe convolution and different sizes of empty convolution to image segmentation accuracy, and compares them with common convolutions such as Conv2d convolution, CG convolution and CCA convolution. The experiment proves that the PCSD convolution module proposed in this paper has the highest segmentation accuracy in all categories of the Cityscapes dataset compared with common convolutions. BiConvNet achieved a 9.39% accuracy improvement over the BiSeNet v2 network, with only a slight increase of 1.18M in model parameters. A mIoU accuracy of 68.75% was achieved on the validation set. Furthermore, through comparative experiments with commonly used autonomous driving image segmentation algorithms in recent years, BiConvNet demonstrates strong competitive advantages in segmentation accuracy on the Cityscapes and BDD100K datasets.
Publication Date: 2024/11/01

Background and Objective: In response to the challenges of poor mapping outcomes and susceptibility to obstacles encountered by indoor mobile vehicles relying solely on pure cameras or pure LiDAR during their movements, this paper proposes an obstacle avoidance method for indoor mobile vehicles that integrates image and LiDAR data, thus achieving obstacle avoidance for mobile vehicles. Materials and Methods: This method combines data from a depth camera and LiDAR, employing the Gmapping SLAM algorithm for environmental mapping, along with the A* algorithm and TEB algorithm for local path planning. In addition, this approach incorporates gesture functionality, which can be used to control the vehicle in certain special scenarios where “pseudo-obstacles” exist. The method utilizes the YOLO V3 algorithm for gesture recognition. Results: This paper merges the maps generated by the depth camera and LiDAR, resulting in a three-dimensional map that is more enriched and better aligned with real-world conditions. Combined with the A* algorithm and TEB algorithm, an optimal route is planned, enabling the mobile vehicles to effectively obtain obstacle information and thus achieve obstacle avoidance. Additionally, the introduced gesture recognition feature, which has been validated, also effectively controls the forward and backward movements of the mobile vehicles, facilitating obstacle avoidance. Conclusion: The experimental platform for the mobile vehicles, which integrates depth camera and LiDAR, built in this study has been validated for real-time obstacle avoidance through path planning in indoor environments. The introduced gesture recognition also effectively enables obstacle avoidance for the mobile vehicles.

Improving equity in data science, edited by Colby Tofel-Grehl and Emmanuel Schanzer, is a thought-provoking exploration of how data science education can be transformed to foster equity, especially within K-16 classrooms. The editors advocate for redefining

[…] Update vom 10.2.2017, Karen Blakeman’s Blog: New Creative Commons image search – back to the drawing board I’m afraid […]

Locating images that can be re-used, modified and incorporated into commercial or non-commercial projects is always a hot topic on my search workshops.  As soon as we start looking at tools that identify Creative Commons and public domain images the delegates start scribbling. Yes, Google and Bing both have tools that allow you to specify … Continue reading New Creative Commons image search – back to the drawing board I’m afraid →

This tutorial will show you how to wrap text around the image in WordPress.

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This video tutorial shows how to get the image (attachment) ID to use it in the shortcode for WordPress templates.

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In our new tutorial we will teach you how to change predefined images dimensions in your Shopify store.

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I Can Only Imagine is part of our Christian Music For Kids Library.

A new EU BON derived paper, publsihed recently in the journal Remote Sensing, introduces eHabitat+, a habitat modelling service supporting the European Commission’s Digital Observatory for Protected Areas.

Abstract:

Protected areas (PAs) need to be assessed systematically according to biodiversity values and threats in order to support decision-making processes. For this, PAs can be characterized according to their species, ecosystems and threats, but such information is often difficult to access and usually not comparable across regions. There are currently over 200,000 PAs in the world, and assessing these systematically according to their ecological values remains a huge challenge. However, linking remote sensing with ecological modelling can help to overcome some limitations of conservation studies, such as the sampling bias of biodiversity inventories. The aim of this paper is to introduce eHabitat+, a habitat modelling service supporting the European Commission’s Digital Observatory for Protected Areas, and specifically to discuss a component that systematically stratifies PAs into different habitat functional types based on remote sensing data. eHabitat+ uses an optimized procedure of automatic image segmentation based on several environmental variables to identify the main biophysical gradients in each PA. This allows a systematic production of key indicators on PAs that can be compared globally. Results from a few case studies are illustrated to show the benefits and limitations of this open-source tool.

Original Source: 

Martínez-López, J.; Bertzky, B.; Bonet-García, F.J.; Bastin, L.; Dubois, G. Biophysical Characterization of Protected Areas Globally through Optimized Image Segmentation and Classification. Remote Sens. 2016, 8, 780. DOI: 0.3390/rs8090780

The discipline of taxonomy is highly reliant on previously published photographs, drawings and other images as biodiversity data. Inspired by the uncertainty among taxonomists, a team, representing both taxonomists and experts in rights and copyright law, has traced the role and relevance of copyright when it comes to images with scientific value. Their discussion and conclusions are published in the latest paper added in the EU BON Collection in the open science journal Research Ideas and Outcomes (RIO).

Taxonomic papers, by definition, cite a large number of previous publications, for instance, when comparing a new species to closely related ones that have already been described. Often it is necessary to use images to demonstrate characteristic traits and morphological differences or similarities. In this role, the images are best seen as biodiversity data rather than artwork. According to the authors, this puts them outside the scope, purposes and principles of Copyright. Moreover, such images are most useful when they are presented in a standardized fashion, and lack the artistic creativity that would otherwise make them 'copyrightable works'.

"It follows that most images found in taxonomic literature can be re-used for research or many other purposes without seeking permission, regardless of any copyright declaration," says Prof. David J. Patterson, affiliated with both Plazi and the University of Sydney.

Nonetheless, the authors point out that, "in observance of ethical and scholarly standards, re-users are expected to cite the author and original source of any image that they use." Such practice is "demanded by the conventions of scholarship, not by legal obligation," they add.

However, the authors underline that there are actual copyrightable visuals, which might also make their way to a scientific paper. These include wildlife photographs, drawings and artwork produced in a distinctive individual form and intended for other than comparative purposes, as well as collections of images, qualifiable as databases in the sense of the European Protection of Databases directive.

In their paper, the scientists also provide an updated version of the Blue List, originally compiled in 2014 and comprising the copyright exemptions applicable to taxonomic works. In their Extended Blue List, the authors expand the list to include five extra items relating specifically to images.

"Egloff, Agosti, et al. make the compelling argument that taxonomic images, as highly standardized 'references for identification of known biodiversity,' by necessity, lack sufficient creativity to qualify for copyright. Their contention that 'parameters of lighting, optical and specimen orientation' in biological imaging must be consistent for comparative purposes underscores the relevance of the merger doctrine for photographic works created specifically as scientific data," comments on the publication Ms. Gail Clement, Head of Research Services at the Caltech Library.

"In these cases, the idea and expression are the same and the creator exercises no discretion in complying with an established convention. This paper is an important contribution to the literature on property interests in scientific research data - an essential framing question for legal interoperability of research data," she adds.

###

Original source:

Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502

Rotten returns with a curious mixture of rage and nostalgia.

Leica Geosystems, part of Hexagon, announced on Sept. 12 the launch of the new Leica iCON trades solution, which pairs the Leica iCON iCS20 and Leica iCON iCS50 sensors with industry-tailored construction layout workflows. The new solution complements the industry-leading Leica iCON build portfolio.

Strategic communications is by no means a ‘silver bullet’, but it is a vital part of addressing the challenges we face

It was just a few years ago when I first heard the word “proptech,” and for a while it looked like it would become a common buzzword in the industry.

AXIS Image Health Analytics notifies users of any issues with image quality and ensures that the cameras being used are capturing the right images at all times.

As a writer I’m loath to admit it, but sometimes words just can’t paint as clear of a picture as, well, a picture.

West Lafayette, IN — Using newly developed algorithms, researchers from Purdue University have designed an image- and video-based application to detect combustible dust concentrations suspended in the air.

Lansing, MI — If you rely on caffeine to provide a brain boost after a poor night of sleep, findings of a recent study from researchers at Michigan State University may give you a jolt.

Thirsty Buddha™ Soda joins Buddha Brands™ portfolio of healthy, plant-based products including popular Thirsty Buddha® Coconut Water and Hungry Buddha® Bars. 

So currently (excuse the terrible schematic graphics) this is what I have: FIOS Router -----[WIRED via Ethernet] ----> Netgear Orbi Mesh ---------> Apple TV box wifi'ed to Netgear Orbi FIOS's new "cable box" wifi'ed to Netgear Orbi (or maybe...

Children's Geographies; 08/01/2021
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Children's Geographies; 08/01/2024
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The Contextual House, by LO Design, stands as both a tribute to Philadelphia's architectural heritage and a bold statement of contemporary design.

What would it take to build a world where every pregnant person in this country had the rights, resources, and respect they needed to decide what to do with their pregnancy, whether to continue it or not? That world that we want to build is what’s possible with this election and the organizing that must […]

The post Imagining a World Where Reproductive Justice is For Everyone was curated by information for practice.

About the Role
As an Imaging R&D Graduate, you will be joining the ISP team within Arm, which develops and designs image processing technology that is used in a range of applications including automobiles, security cameras, and drones. The algorithm development team is tasked with solving a variety of image processing problems, from denoise to demosaic, auto-exposure to motion compensation. Our algorithms must satisfy the competing demands of high image quality, and efficient, low-power hardware implementation.

This is an opportunity to contribute towards the next generation of imaging systems, for both human viewing and autonomous driving applications.

Why should you apply?

• You want to work in leading digital imaging technology.
• You have a keen interest in imaging or image processing, which you would like to develop into a career.
• You want to see tangible results from your work.
• You want to have the opportunity to learn from the best engineers and start a career in a leading imaging and vision technology group.

What will I be accountable for?

• Working with image quality experts to determine requirements for processing.
• Developing new image processing algorithms, often from early concept phase and typically in a mathematical modelling environment.
• Implementing novel algorithms, starting from a floating-point model
• Testing and benchmarking of the results, working closely with our image quality experts.
• Collaborating with the wider engineering team to arrive at an architecture and fixed-point model of your algorithm, optimized for hardware or software implementation

Abstract Objectives Higher education students experience elevated levels of suicidal ideation, but often face barriers in accessing support. The Mental Imagery for Suicidality in Students Trial (MISST; ISRCTN13621293; NCT05296538) tested the feasibility and acceptability of a six-session imagery-based approach called Broad-Minded Affective Coping (BMAC). This qualitative evaluation explored the experiences of MISST participants and staff. […]

The post A qualitative study exploring participants experiences of the Mental Imagery for Suicidality in Students Trial was curated by information for practice.

Space is around us transforms the Kyano apartment in Athens into a sleek, multifunctional space that blends history with contemporary design.

The singer-songwriter's latest album, "Black Cowboys," chronicles the role played by African-Americans in settling the West after the Civil War. The album has been nominated for a Grammy.