Search results for: digital images

Authors: Dominic Sagar

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Manchester ‘King Cotton’, the first truly industrial city of the nineteenth century, passing on the baton to Detroit ‘Motor City’, is the first truly modern city. We are exploring the tales of the two cities, their rise and fall and subsequent post-industrial decline, their transitions and transformations, whilst alongside paralleling their corresponding, commercial, cultural, industrial and even agricultural, artistic and musical transactions and connections. The paper will briefly contextualize how technologies of the industrial age and modern age have been instrumental in the development of these cities and other similar cities including New York. However, the main focus of the study will be the present and more importantly the future, how globalisation and the advancements of digital technologies and industries have shaped the cities developments from AlanTuring and the making of the first programmable computer to the effect of digitalisation and digital initiatives. Manchester now has a thriving creative digital infrastructure of Digilabs, FabLabs, MadLabs and hubs, the study will reference the Smart Project and the Manchester Digital Development Association whilst paralleling similar digital and creative industrial initiatives now starting to happen in Detroit. The paper will explore other topics including the need to allow for zones of experimentation, areas to play, think and create in order develop and instigate new initiatives and ideas of production, carrying on the tradition of influential inventions throughout the history of these key cities. Other topics will be briefly touched on, such as urban farming, citing the Biospheric foundation in Manchester and other similar projects in Detroit. However, the main thread will focus on the music industries and how they are contributing to the regeneration of cities. Musically and artistically, Manchester and Detroit have been closely connected by the flow and transmission of information and transfer of ideas via ‘cars and trains and boats and planes’ through to the new ‘super highway’. From Detroit to Manchester often via New York and Liverpool and back again, these musical and artistic connections and flows have greatly affected and influenced both cities and the advancement of technology are still connecting the cities. In summary two hugely important industrial cities, subsequently both experienced massive decline in fortunes, having had their large industrial hearts ripped out, ravaged leaving dying industrial carcasses and car crashes of despair, dereliction, desolation and post-industrial wastelands vacated by a massive exodus of the cities’ inhabitants. To examine the affinity, similarity and differences between Manchester & Detroit, from their industrial importance to their post-industrial decline and their current transmutations, transformations, transient transgressions, cities in transition; contrasting how they have dealt with these problems and how they can learn from each other. With a view to framing these topics with regard to how various communities have shaped these cities and the creative industries and design [the new cotton/car manufacturing industries] are reinventing post-industrial cities, to speculate on future development of these themes in relation to Globalisation, digitalisation and how cities can function to develop solutions to communal living in cities of the future.

Keywords: cultural capital, digital developments, musical initiatives, zones of experimentation

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Authors: Karthiyayini Nagarajan, P. V. RamaKrishna

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Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar(SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System(lab bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Benoit Landi, Hervé Pingaud, Jean-Benoit Culie, Michel Galaup

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Serious games have been widely disseminated in the field of digital learning. They have proved their utility in improving skills through virtual environments that simulate the field where new competencies have to be improved and assessed. This paper describes how we created CLONE, a serious game whose purpose is to help nurses create an efficient work plan in a hospital care unit. In CLONE, the number of patients to take care of is similar to the reality of their job, going far beyond what is currently practiced in nurse school classrooms. This similarity with the operational field increases proportionally the number of activities to be scheduled. Moreover, very often, the team of nurses is composed of regular nurses and nurse assistants that must share the work with respect to the regulatory obligations. Therefore, on the one hand, building a short-term planning is a complex task with a large amount of data to deal with, and on the other, good clinical practices have to be systematically applied. We present how reference planning has been defined by addressing an optimization problem formulation using the expertise of teachers. This formulation ensures the gameplay feasibility for the scenario that has been produced and enhanced throughout the game design process. It was also crucial to steer a player toward a specific gaming strategy. As one of our most important learning outcomes is a clear understanding of the workload concept, its factual calculation for each caregiver along time and its inclusion in the nurse reasoning during planning elaboration are focal points. We will demonstrate how to modify the game scenario to create a digital environment in which these somewhat abstract principles can be understood and applied. Finally, we give input on an experience we had on a pilot of a thousand undergraduate nursing students.

Keywords: care planning, workload, game design, hospital nurse, organizational skills, digital learning, serious game

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Authors: Rika Uchida

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Claude Debussy's piano works can be divided into three categories in terms of style characteristics. The first category includes works which are strongly impressionistic, evoking a mood or an atmosphere, rather than making a direct, clear statement. These works often depict nature, and they are descriptive and sensitive in their character. Harmonic vocabulary is often complex, and the sense of tonality is often ambiguous in those works. Examples which belong to this category are ‘Clair de lune’ from Suite Bergamasque, Deux Arabesques, and ‘Reflets dans l'eau’ from Images Book 2. The second category shows little or no trace of impressionism. Works are not descriptive; rather, they are classical or absolute. Examples which belong to this category are Pour le Piano, ‘Hommage à Rameau’ and ‘Movement’ from Images Book 1 and Etudes. The third category can be called exotic. Debussy had a great interest in foreign lands such as the Far and Near East, and Spain. He employs pentatonic and quartal harmonies to describe the Orient, occasionally using the effect of the Javanese gamelan, which impressed him at the Paris Exhibition. His compositions in the Spanish style evoke the atmosphere of Spain. Though he borrowed some techniques from Spanish composers whom he knew, the tonal experimentation which occurs in these works sets them apart. Examples which belong to this category are ‘Pagodes’ and ‘la Soiree dans Grenade’ from Estampes, ‘la Puerta del Vino’ from Preludes Book 2.

Keywords: music, piano, Debussy, style

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Authors: Tommi Mahlamaki, Mika Ojala

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Digitalization is changing our lives in many ways. As consumers, we are accustomed using different online interactive sales systems. However, while many online selling sites offer systems that have evolved from simple selling functions, the change has not been as rapid in business-to-business (B2B) markets. This is because many B2B companies rely on personal sales and personal communication. The main objective of this research is to clarify perceptions towards digital interactive sales systems and, more specifically, sales configurators. It also aims to identify trends towards the use of sales configurators. To reach these objectives, an online questionnaire was created that targets Finnish B2B distributors who are, by definition, part of B2B markets. The questionnaire was sent to 340 distributors, and it was returned by 150 respondents. The results showed that 82% of respondents had heard about sales configurators, and 64% had used them. The results also showed that 48% of respondents felt that the use of sales configurators would increase in the future, while only 2% felt they would be used less. The future use of sales configurators was not seen as affecting the level of personal sales. In light of the results, we recommend that B2B companies create marketing strategies that integrate and complement traditional sales processes with digital interactive systems.

Keywords: digitalization, interactive systems, marketing, sales process

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Authors: Fatema-Tuz-Zohra Khanam, Ali Al-Naji, Asanka G. Perera, Kim Gibson, Javaan Chahl

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Conventional contact-based vital signs monitoring sensors such as pulse oximeters or electrocardiogram (ECG) may cause discomfort, skin damage, and infections, particularly in neonates with fragile, sensitive skin. Therefore, remote monitoring of the vital sign is desired in both clinical and non-clinical settings to overcome these issues. Camera-based vital signs monitoring is a recent technology for these applications with many positive attributes. However, there are still limited camera-based studies on neonates in a clinical setting. In this study, the heart rate (HR) and respiratory rate (RR) of eight infants at the Neonatal Intensive Care Unit (NICU) in Flinders Medical Centre were remotely monitored using a digital camera applying color and motion-based computational methods. The region-of-interest (ROI) was efficiently selected by incorporating an image decomposition method. Furthermore, spatial averaging, spectral analysis, band-pass filtering, and peak detection were also used to extract both HR and RR. The experimental results were validated with the ground truth data obtained from an ECG monitor and showed a strong correlation using the Pearson correlation coefficient (PCC) 0.9794 and 0.9412 for HR and RR, respectively. The RMSE between camera-based data and ECG data for HR and RR were 2.84 beats/min and 2.91 breaths/min, respectively. A Bland Altman analysis of the data also showed a close correlation between both data sets with a mean bias of 0.60 beats/min and 1 breath/min, and the lower and upper limit of agreement -4.9 to + 6.1 beats/min and -4.4 to +6.4 breaths/min for both HR and RR, respectively. Therefore, video camera imaging may replace conventional contact-based monitoring in NICU and has potential applications in other contexts such as home health monitoring.

Keywords: neonates, NICU, digital camera, heart rate, respiratory rate, image decomposition

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Authors: Jandot Aurélia

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In France, in the main media, the concern about nuclear safety and security has not really appeared before the beginning of the 1970s. The gradual changes in its perception are studied here through the arguments given in the main French news magazines, linked with several parameters. As this represents a considerable amount of copies and thus of information, are selected here the main articles as well as the main “mental images” aiming to persuade the readers and which have led the public awareness to evolve. Indeed, in the 1970s, in France, these evolutions were not made in one day. Indeed, over the period, many articles were still in favor of nuclear power plants and promoted the technological advances that were made in this field. They had to be taken into account. But, gradually, grew up arguments and mental images discrediting the perception of nuclear technology. Among these were the environmental impacts of this industry, as the question of pollution progressively appeared. So, between 1970 and 1979, the language has changed, as the perceptible objectives of the communication, allowing to discern the deepest intentions of the editorial staffs of the French news magazines. This is all these changes that are emphasized here, over a period when the safety and security concern linked to the nuclear technology, to there a field for specialists, has become progressively a social issue seemingly open to all.

Keywords: environmental impacts, media discourse, nuclear security, public awareness

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Authors: Bangaly Kaba

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In the global information society, the importance of the Internet cannot be overemphasized. Africa needs access to the powerful information and communication tools of the Internet in order to obtain the resources and efficiency essential for sustainable development. Unfortunately, in 2013, the data from Internetworldstats showed only 15% of African populations have access to Internet. This relative low Internet penetration rate signals a problem that may threaten the economic development, governmental efficiency, and ultimately the global competitiveness of African countries. Many initiatives were undertaken to bring the benefits of the global information revolution to the people of Africa, through connection to the Internet and other Global Information Infrastructure technologies. The purpose is to understand differences between socio-economically advantaged and disadvantaged internet users. From that, we will determine what prevents disadvantaged groups from benefiting from Internet usage. Data were collected through a survey from Internet users in Ivory Coast. The results reveal that Personal network exposure, Self-efficacy and Availability are the key drivers of continued use intention for the socio-economically disadvantaged group. The theoretical and practical implications are also described.

Keywords: digital inequality, internet, integrative model, socio-economically advantaged and disadvantaged, use continuance, Africa

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Kakhaber Djakeli

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For market leadership, iconic brands already start to establish their unique digital avatars into Metaverse and offer Non Fungible Tokens to their fans. Metaverse can be defined as an evolutionary step of Internet development. So if companies and brands use the internet, logically, they can find new solutions for them and their customers in Metaverse. Marketing and Management today must learn how to combine physical world activities with those either entitled as digital, virtual, and immersive. A “Phygital” Solution uniting physical and digital competitive activities of the company covering the questions about how to use virtual worlds for Brand Development and Non Fungible Tokens for more attractiveness soon will be most relevant question for Branding. Thinking comprehensively, we can entitle this type of branding as an Immersive one. As we see, the Immersive Brands give customers more mesmerizing feelings than traditional ones. Accordingly, the Branding can be divided by the company in its own understanding into two models: traditional and immersive. Immersive Branding being more directed to Sensorial challenges of Humans will be big job for International Universities in near future because they target the Generation - Z. To try to help those International Universities opening the door to the mesmerizing, immersive branding, the Marketing Research have been undertaken. The main goal of the study was to establish the model for Immersive Branding at International Universities and answer on many questions what logically arises in university life. The type of Delphi Surveys entitled as an Expert Studies was undertaken for one great mission, to help International Universities to open the opportunities to Phygital activities with reliable knowledge with Model of Immersive Branding. The Questionnaire sent to Experts of Education were covering professional type of questions from education to segmentation of customers, branding, attitude to students, and knowledge to Immersive Marketing. The research results being very interesting and encouraging enough to make author to establish the New Model of Immersive Experiential Branding for International Universities.

Keywords: branding, immersive marketing, students, university

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Authors: Deonie Botha

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Digital transformation and the digitization of occupational health and safety training have grown exponentially due to a variety of contributing factors. The literature suggests that digitalization has numerous benefits but also has associated challenges. The aim of the paper is to develop an understanding of both the perceived benefits and challenges of digitalization in an occupational health and safety context in an effort to design and develop e-learning interventions that will optimize the benefits of digitalization and address the associated challenges. The paper proposes, deliberate and tests the design principles of an e-learning intervention to ensure alignment with the requirements of a digitally transformed environment. The results of the research are based on a literature review regarding the requirements and effect of the Fourth Industrial Revolution on learning and e-learning in particular. The findings of the literature review are enhanced with empirical research in the form of a case study conducted in an organization that designs and develops e-learning content in the occupational health and safety industry. The primary findings of the research indicated that: (i) The requirements of learners and organizations in respect of e-learning are different than previously (i.e., a pre-Fourth Industrial Revolution related work setting). (ii) The design principles of an e-learning intervention need to be aligned with the entire value chain of the organization. (iii) Digital twins support and enhance the design and development of e-learning. (iv)Learning should incorporate a multitude of sensory experiences and should not only be based on visual stimulation. (v) Data that are generated as a result of e-learning interventions should be incorporated into big data streams to be analyzed and to become actionable. It is therefore concluded that there is general consensus on the requirements that e-learning interventions need to adhere to in a digitally transformed occupational health and safety work environment. The challenge remains for organizations to incorporate data generated as a result of e-learning interventions into the digital ecosystem of the organization.

Keywords: digitalization, training, fourth industrial revolution, big data

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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Authors: Mansilla, Juan Camilo

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According to many studies, public space in the cities of Global South is constantly morcellated and captured by a multiplicity of actors in a permanent struggle for power. This imposed public space restricts the access to services and political actions to many inhabitants. The author has conducted several focus group sessions using video in a reflective mode with low-income communities in Medellín, Colombia in order to study how people in this city are shift from a physical public space to a hybrid public space shaped by internet. Beyond the fragmented city and the violent urban context manifested by participants, these activities have highlighted how the access to the city is currently going through a dialectic movement between the physical and the digital space. The purpose of this article is to make explicit the link between this hybrid public space and the boundaries of exclusion in the city. Urban marginality is closely related with the idea of access and space. Low-income communities in Medellín assume the digital realm like a “not controlled space” of resistance, where alternative ways of expression like hip hop movement, graffiti, dance, video and virtual communities produce effective changes in the physical realm.

Keywords: access to the city, hybrid public space, low-income communities, Medellín, urban marginality

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Authors: Stefano Pelaggi

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The research is focused on youth labor and mobility in Berlin. Mobility has become a common denominator in our daily lives but it does not primarily move according to monetary incentives. Labor, knowledge and leisure overlap on this point as cities are trying to attract people who could participate in production of the innovations while the new migrants are experiencing the lifestyle of the host cities. The research will present the project of empirical study focused on Italian workers in the digital industry in Berlin, trying to underline the connection between pleasure, leisure with the choice of life abroad. Berlin has become the epicenter of the European Internet start-up scene, but people suitable to work for digital industries are not moving in Berlin to make a career, most of them are attracted to the city for different reasons. This point makes a clear exception to traditional migration flows, which are always originated from a specific search of employment opportunities or strong ties, usually families, in a place that could guarantee success in finding a job. Even the skilled migration has always been originated from a specific need, finding the right path for a successful professional life. In a society where the lack of free time in our calendar seems to be something to be ashamed, the actors of youth mobility incorporate some categories of experiential tourism within their own life path. Professional aspirations, lifestyle choices of the protagonists of youth mobility are geared towards meeting the desires and aspirations that define leisure. While most of creative work places, in particular digital industries, uses the category of fun as a primary element of corporate policy, virtually extending the time to work for the whole day; more and more people around the world are deciding their path in life, career choices on the basis of indicators linked to the realization of the self, which may include factors like a warm climate, cultural environment. All indicators that are usually eradicated from the hegemonic approach to labor. The interpretative framework commonly used seems to be mostly focused on a dualism between Florida's theories and those who highlight the absence of conflict in his studies. While the flexibility of the new creative industries is minimizing leisure, incorporating elements of leisure itself in work activities, more people choose their own path of life by placing great importance to basic needs, through a gaze on pleasure that is only partially driven by consumption. The multi localism is the co-existence of different identities and cultures that do not conflict because they reject the bind on territory. Local loses its strength of opposition to global, with an attenuation of the whole concept of citizenship, territory and even integration. A similar perspective could be useful to search a new approach to all the studies dedicated to the gentrification process, while studying the new migrations flow.

Keywords: brain drain, digital industry, leisure and gentrification, multi localism

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Authors: A. V. Sokolov, S. V. Vorobyev, A. Yu. Efimtcev, V. Yu. Lobzin, I. A. Lupanov, O. A. Cherdakov, V. A. Fokin

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Alzheimer’s disease (AD) is the most common form of dementia. Different brain regions are involved to the pathological process of AD. The purpose of this study was to evaluate brain activation by visual memory task in patients with Alzheimer's disease and determine correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. To investigate the organization of memory and localize cortical areas activated by visual memory task we used functional magnetic resonance imaging and to evaluate brain atrophy of patients with Alzheimer's disease we used voxel-based morphometry. FMRI was performed on 1.5 T MR-scanner Siemens Magnetom Symphony with BOLD (Blood Oxygenation Level Dependent) technique, based on distinctions of magnetic properties of hemoglobin. For test stimuli we used series of 12 not related images for "Baseline" and 12 images with 6 presented before for "Active". Stimuli were presented 3 times with reduction of repeated images to 4 and 2. Patients with Alzheimer's disease showed less activation in hippocampal formation (HF) region and parahippocampal gyrus then healthy persons of control group (p<0.05). The study also showed reduced activation in posterior cingulate cortex (p<0.001). Voxel-based morphometry showed significant atrophy of grey matter in Alzheimer’s disease patients, especially of both temporal lobes (fusiform and parahippocampal gyri); frontal lobes (posterior cingulate and superior frontal gyri). The study showed correlation between memory impairment and atrophy of memory specific brain regions of frontal and medial temporal lobes. Thus, reduced activation in hippocampal formation and parahippocampal gyri, in posterior cingulate gyrus in patients with Alzheimer's disease correlates to significant atrophy of these regions, detected by voxel-based morphometry, and to deterioration of specific cognitive functions.

Keywords: Alzheimer’s disease, functional MRI, voxel-based morphometry

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Authors: Rachel Cherner

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Introduction: The current study investigates several user characteristics that may predict the adoption of digital mental health supports. The extent to which individual characteristics predict preferences for functional elements of computer-mediated social support (CMSS) platforms and mental health (MH) apps is relatively unstudied. Aims: The present study seeks to illuminate the relationship between broad user characteristics and perceived attraction to CMSS platforms and MH apps. Methods: Participants (n=353) were recruited using convenience sampling methods (i.e., digital flyers, email distribution, and online survey forums). The sample was 68% male, and 32% female, with a mean age of 29. Participant racial and ethnic breakdown was 75% White, 7%, 5% Asian, and 5% Black or African American. Participants were asked to complete a 25-minute self-report questionnaire that included empirically validated measures assessing a battery of characteristics (i.e., subjective levels of anxiety/depression via PHQ-9 (Patient Health Questionnaire 9-item) and GAD-7 (Generalized Anxiety Disorder 7-item); attachment style via MAQ (Measure of Attachment Qualities); personality types via TIPI (The 10-Item Personality Inventory); growth mindset and mental health-seeking attitudes via GM (Growth Mindset Scale) and MHSAS (Mental Help Seeking Attitudes Scale)) and subsequent attitudes toward CMSS platforms and MH apps. Results: A stepwise linear regression was used to test if user characteristics significantly predicted attitudes towards key features of CMSS platforms and MH apps. The overall regression was statistically significant (R² =.20, F(1,344)=14.49, p<.000). Conclusion: This original study examines the clinical and sociocultural factors influencing decisions to use CMSS platforms and MH apps. Findings provide valuable insight for increasing adoption and engagement with digital mental health support. Fostering a growth mindset may be a method of increasing participant/patient engagement. In addition, CMSS platforms and MH apps may empower under-resourced and minority groups to gain basic access to mental health support. We do not assume this final model contains the best predictors of use; this is merely a preliminary step toward understanding the psychology and attitudes of CMSS platform/MH app users.

Keywords: computer-mediated social support platforms, digital mental health, growth mindset, health-seeking attitudes, mental health apps, user characteristics

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Authors: Greta Rizzi, Ashley Gallitto, Federica Vacca

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Looking at design artifacts as bearers and disseminators of material knowledge and intangible socio-cultural meanings, the significance of archival jewelry was investigated following digital cultural heritage research streams. The application of the reverse engineering concept guided the research path: starting with the study of Gianfranco Ferré's archival jewelry and analyzing its technical heritage and symbolic value, the digitalization, dematerialization, and rematerialization of the artifact were carried out. According to that, the proposed paper results from research conducted within the residency program between the Gianfranco Ferré Research Center (GFRC) and Massachusetts Institute of Technology (MIT), involving both the Design and Mechanical Engineering Departments of Politecnico di Milano. The paper will discuss the analysis of traditional design manufacturing techniques, re-imagined through 3D scanning, 3D modeling, and 3D printing technical knowledge while emphasizing the significance of the designer's role as an explorer of socio-cultural meanings and technological mediators in the analog-digital-analog transition.

Keywords: Archival jewelry, cultural heritage, rematerialization, reverse engineering.

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Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

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Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

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Authors: Aditya Karade, Sharada Falane, Dhananjay Deshmukh, Vijaykumar Mantri

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Brain tumors pose a significant challenge in healthcare due to their complex nature and impact on patient outcomes. The application of deep learning (DL) algorithms in medical imaging have shown promise in accurate and efficient brain tumour detection. This paper explores the performance of various pre-trained DL models ResNet50, Xception, InceptionV3, EfficientNetB0, DenseNet121, NASNetMobile, VGG19, VGG16, and MobileNet on a brain tumour dataset sourced from Figshare. The dataset consists of MRI scans categorizing different types of brain tumours, including meningioma, pituitary, glioma, and no tumour. The study involves a comprehensive evaluation of these models’ accuracy and effectiveness in classifying brain tumour images. Data preprocessing, augmentation, and finetuning techniques are employed to optimize model performance. Among the evaluated deep learning models for brain tumour detection, ResNet50 emerges as the top performer with an accuracy of 98.86%. Following closely is Xception, exhibiting a strong accuracy of 97.33%. These models showcase robust capabilities in accurately classifying brain tumour images. On the other end of the spectrum, VGG16 trails with the lowest accuracy at 89.02%.

Keywords: brain tumour, MRI image, detecting and classifying tumour, pre-trained models, transfer learning, image segmentation, data augmentation

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Authors: Olena Kavats, Dmitry Khramov, Kateryna Sergieieva, Vladimir Vasyliev, Iurii Kavats

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Geoinformation technologies of space agromonitoring are a means of operative decision making support in the tasks of managing the agricultural sector of the economy. Existing technologies use satellite images in the optical range of electromagnetic spectrum. Time series of optical images often contain gaps due to the presence of clouds and haze. A geoinformation technology is created. It allows to fill gaps in time series of optical images (Sentinel-2, Landsat-8, PROBA-V, MODIS) with radar survey data (Sentinel-1) and use information about agrometeorological conditions of the growing season for individual monitoring years. The technology allows to perform crop classification and mapping for spring-summer (winter and spring crops) and autumn-winter (winter crops) periods of vegetation, monitoring the dynamics of crop state seasonal changes, crop yield forecasting. Crop classification is based on supervised classification algorithms, takes into account the peculiarities of crop growth at different vegetation stages (dates of sowing, emergence, active vegetation, and harvesting) and agriculture land state characteristics (row spacing, seedling density, etc.). A catalog of samples of the main agricultural crops (Ukraine) is created and crop spectral signatures are calculated with the preliminary removal of row spacing, cloud cover, and cloud shadows in order to construct time series of crop growth characteristics. The obtained data is used in grain crop growth tracking and in timely detection of growth trends deviations from reference samples of a given crop for a selected date. Statistical models of crop yield forecast are created in the forms of linear and nonlinear interconnections between crop yield indicators and crop state characteristics (temperature, precipitation, vegetation indices, etc.). Predicted values of grain crop yield are evaluated with an accuracy up to 95%. The developed technology was used for agricultural areas monitoring in a number of Great Britain and Ukraine regions using EOS Crop Monitoring Platform (https://crop-monitoring.eos.com). The obtained results allow to conclude that joint use of Sentinel-1 and Sentinel-2 images improve separation of winter crops (rapeseed, wheat, barley) in the early stages of vegetation (October-December). It allows to separate successfully the soybean, corn, and sunflower sowing areas that are quite similar in their spectral characteristics.

Keywords: geoinformation technology, crop classification, crop yield prediction, agricultural monitoring, EOS Crop Monitoring Platform

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

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Authors: Krzysztof Malczewski

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PET is widely applied scanning procedure in medical imaging based research. It delivers measurements of functioning in distinct areas of the human brain while the patient is comfortable, conscious and alert. This article presents the new compression sensing based super-resolution algorithm for improving the image resolution in clinical Positron Emission Tomography (PET) scanners. The issue of motion artifacts is well known in Positron Emission Tomography (PET) studies as its side effect. The PET images are being acquired over a limited period of time. As the patients cannot hold breath during the PET data gathering, spatial blurring and motion artefacts are the usual result. These may lead to wrong diagnosis. It is shown that the presented approach improves PET spatial resolution in cases when Compressed Sensing (CS) sequences are used. Compressed Sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. The application of CS to PET has the potential for significant scan time reductions, with visible benefits for patients and health care economics. In this study the goal is to combine super-resolution image enhancement algorithm with CS framework to achieve high resolution PET output. Both methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity.

Keywords: PET, super-resolution, image reconstruction, pattern recognition

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Authors: Murat Demir Aydin, Elanur Celebi

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Adhesively bonded joints are used as an alternative to traditional joining methods due to the important advantages they provide. The most important consideration in the use of adhesively bonded joints is that these joints have appropriate requirements for their use in terms of safety. In order to ensure control of this condition, damage analysis of the adhesively bonded joints should be performed by determining the mechanical properties of the adhesives. When the literature is investigated; it is generally seen that the mechanical properties of adhesives are determined by traditional measurement methods. In this study, to determine the mechanical properties of adhesives, the Digital Image Correlation (DIC) method, which can be an alternative to traditional measurement methods, has been used. The DIC method is a new optical measurement method which is used to determine the parameters of displacement and strain in an appropriate and correct way. In this study, tensile tests of Thick Adherent Shear Test (TAST) samples formed using DP410 liquid structural adhesive and steel materials and bulk tensile specimens formed using and DP410 liquid structural adhesive was performed. The displacement and strain values of the samples were determined by DIC method and the shear stress-strain curves of the adhesive for TAST specimens and the tensile strain curves of the bulk adhesive specimens were obtained. Various methods such as numerical methods are required as conventional measurement methods (strain gauge, mechanic extensometer, etc.) are not sufficient in determining the strain and displacement values of the very thin adhesive layer such as TAST samples. As a result, the DIC method removes these requirements and easily achieves displacement measurements with sufficient accuracy.

Keywords: structural adhesive, adhesively bonded joints, digital image correlation, thick adhered shear test (TAST)

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Authors: Daniel Schimmelpfennig

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This paper attempts to delineate the idea to curate the leveling up for whole-systems change. Curation is the act fo select, organize, look after, or present information from a professional point of view through expert knowledge. The trans-paradigmatic, trans-contextual, trans-disciplinary, trans-perspective of trans-media futures studies hopes to enable a move from a monochrome intellectual pursuit towards breathing a higher dimensionality. Progressing to the next level to equip actors for whole-systems change is in consideration of the commonly known symptoms of our time as well as in anticipation of future challenges, both a necessity and desirability. Systems of collective intelligence could potentially scale regenerative, adaptive, and anticipatory capacities. How could such a curation then be enacted and implemented, to initiate the process of leveling-up? The suggestion here is to focus on the metasystem transition, the bio-digital fusion, namely, by merging neurosciences, the ontological design of money as our operating system, and our understanding of the billions of years of time-proven permutations in nature, biomimicry, and biological metaphors like symbiogenesis. Evolutionary cybernetics accompanies the process of whole-systems change.

Keywords: bio-digital fusion, evolutionary cybernetics, metasystem transition, symbiogenesis, transmedia futures studies

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Authors: V. V. Fomin, A. P. Mikhailovich, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Ground-level landscape photos can be used as a source of objective data on woody vegetation and vegetation dynamics. We proposed a method for processing, analyzing, and presenting ground photographs, which has the following advantages: 1) researcher has to form holistic representation of the study area in form of a set of interlapping ground-level landscape photographs; 2) it is necessary to define or obtain characteristics of the landscape, objects, and phenomena present on the photographs; 3) it is necessary to create new or supplement existing textual descriptions and annotations for the ground-level landscape photographs; 4) single or multiple ground-level landscape photographs can be used to develop specialized geoinformation layers, schematic maps or thematic maps; 5) it is necessary to determine quantitative data that describes both images as a whole, and displayed objects and phenomena, using algorithms for automated image analysis. It is suggested to match each photo with a polygonal geoinformation layer, which is a sector consisting of areas corresponding with parts of the landscape visible in the photos. Calculation of visibility areas is performed in a geoinformation system within a sector using a digital model of a study area relief and visibility analysis functions. Superposition of the visibility sectors corresponding with various camera viewpoints allows matching landscape photos with each other to create a complete and wholesome representation of the space in question. It is suggested to user-defined data or phenomenons on the images with the following superposition over the visibility sector in the form of map symbols. The technology of geoinformation layers’ spatial superposition over the visibility sector creates opportunities for image geotagging using quantitative data obtained from raster or vector layers within the sector with the ability to generate annotations in natural language. The proposed method has proven itself well for relatively open and clearly visible areas with well-defined relief, for example, in mountainous areas in the treeline ecotone. When the polygonal layers of visibility sectors for a large number of different points of photography are topologically superimposed, a layer of visibility of sections of the entire study area is formed, which is displayed in the photographs. Also, as a result of this overlapping of sectors, areas that did not appear in the photo will be assessed as gaps. According to the results of this procedure, it becomes possible to obtain information about the photos that display a specific area and from which points of photography it is visible. This information may be obtained either as a query on the map or as a query for the attribute table of the layer. The method was tested using repeated photos taken from forty camera viewpoints located on Ray-Iz mountain massif (Polar Urals, Russia) from 1960 until 2023. It has been successfully used in combination with other ground-based and remote sensing methods of studying the climate-driven dynamics of woody vegetation in the Polar Urals. Acknowledgment: This research was collaboratively funded by the Russian Ministry for Science and Education project No. FEUG-2023-0002 (image representation) and Russian Science Foundation project No. 24-24-00235 (automated textual description).

Keywords: woody, vegetation, repeated, photographs

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Authors: Usman Ahmed Adam, Umar Ibrahim, Ezra S. Gbaje

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This study is posed to explore the practice of Public Access Computers (PACs) in academic libraries in Kaduna State, Nigeria. The study aimed to determine the computers and other tools available, their services and challenges of the practices. Three questions were framed to identify number of public computers and tools available, their services and problems faced during the practice. The study used qualitative research design along with semi-constructed interview and observation as tools for data collection. Descriptive analysis was employed to analyze the data. The sample size of the study comprises 52 librarian and IT staff from the seven academic institutions in Kaduna State. The findings revealed that, PACs were provided for access to the Internet, digital resources, library catalogue and training services. The study further explored that, despite the limit number of the computers, users were not allowed to enjoy many services. The study recommends that libraries in Kaduna state should provide more public computers to be able to cover the population of their users; libraries should allow users to use the computers without limitations and restrictions.

Keywords: academic libraries, computers in library, digital libraries, public computers

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Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Darsh N. Patel, Eric Olson

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Fractals can be found everywhere, whether it be the shape of a leaf or a system of blood vessels. Fractals are used to help study and understand different physical and mathematical processes; however, their artistic nature is also beautiful to simply explore. This project explores fractals generated by a cubically convergent extension to Newton's method. With this iteration as a starting point, a complex plane spanning from -2 to 2 is created with a color wheel mapped onto it. Next, the polynomial whose roots the fractal will generate from is established. From the Fundamental Theorem of Algebra, it is known that any polynomial has as many roots (counted by multiplicity) as its degree. When generating the fractals, each root will receive its own color. The complex plane can then be colored to indicate the basins of attraction that converge to each root. From a computational point of view, this project’s code identifies which points converge to which roots and then obtains fractal images. A zoom path into the fractal was implemented to easily visualize the self-similar structure. This path was obtained by selecting keyframes at different magnifications through which a path is then interpolated. Using parallel processing, many images were generated and condensed into a video. This project illustrates how practical techniques used for scientific visualization can also have an artistic side.

Keywords: fractals, cubic method, Julia programming language, basin of attraction

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Authors: Thu Nhi Tran Caliste

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X-ray Bragg diffraction imaging (“topography”)entered into practical use when Lang designed an “easy” technical setup to characterise the defects / distortions in the high perfection crystals produced for the microelectronics industry. The use of this technique extended to all kind of high quality crystals, and deposited layers, and a series of publications explained, starting from the dynamical theory of diffraction, the contrast of the images of the defects. A quantitative version of “monochromatic topography” known as“Rocking Curve Imaging” (RCI) was implemented, by using synchrotron light and taking advantage of the dramatic improvement of the 2D-detectors and computerised image processing. The rough data is constituted by a number (~300) of images recorded along the diffraction (“rocking”) curve. If the quality of the crystal is such that a one-to-onerelation between a pixel of the detector and a voxel within the crystal can be established (this approximation is very well fulfilled if the local mosaic spread of the voxel is < 1 mradian), a software we developped provides, from the each rocking curve recorded on each of the pixels of the detector, not only the “voxel” integrated intensity (the only data provided by the previous techniques) but also its “mosaic spread” (FWHM) and peak position. We will show, based on many examples, that this new data, never recorded before, open the field to a highly enhanced characterization of the crystal and deposited layers. These examples include the characterization of dislocations and twins occurring during silicon growth, various growth features in Al203, GaNand CdTe (where the diffraction displays the Borrmannanomalous absorption, which leads to a new type of images), and the characterisation of the defects within deposited layers, or their effect on the substrate. We could also observe (due to the very high sensitivity of the setup installed on BM05, which allows revealing these faint effects) that, when dealing with very perfect crystals, the Kato’s interference fringes predicted by dynamical theory are also associated with very small modifications of the local FWHM and peak position (of the order of the µradian). This rather unexpected (at least for us) result appears to be in keeping with preliminary dynamical theory calculations.

Keywords: rocking curve imaging, X-ray diffraction, defect, distortion

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