Search results for: image processing

Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

Abstract:

The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

Procedia PDF Downloads 68

Authors: Oktay Celenk, Ugur Karanfil, Iskender Demir, Samir Lamrini, Jorg Neumann, Arif Demir

Abstract:

Due to its favourable material characteristics, fiber reinforced plastics are amongst the main topics of all actual lightweight construction megatrends. Especially in transportation trends ranging from aeronautics over the automotive industry to naval transportation (yachts, cruise liners) the expected economic and environmental impact is huge. In naval transportation components like yacht bodies, antenna masts, decorative structures like deck lamps, light houses and pool areas represent cheap and robust solutions. Commercially available laser tools like carbon dioxide gas lasers (CO₂), frequency tripled solid state UV lasers, and Neodymium-YAG (Nd:YAG) lasers can be used. These tools have emission wavelengths of 10 µm, 0.355 µm, and 1.064 µm, respectively. The scientific goal is first of all the generation of a parameter matrix for laser processing of each used material for a Tm-fiber laser system (wavelength 2 µm). These parameters are the heat affected zone, process gas pressure, work piece feed velocity, intensity, irradiation time etc. The results are compared with results obtained with well-known material processing lasers, such as a Yb-fiber lasers (wavelength 1 µm). Compared to the CO₂-laser, the Tm-laser offers essential advantages for future laser processes like cutting, welding, ablating for repair and drilling in composite part manufacturing (components of cruise liners, marine pipelines). Some of these are the possibility of beam delivery in a standard fused silica fiber which enables hand guided processing, eye safety which results from the wavelength, excellent beam quality and brilliance due to the fiber nature. There is one more feature that is economically absolutely important for boat, automotive and military projects manufacturing that the wavelength of 2 µm is highly absorbed by the plastic matrix and thus enables selective removal of it for repair procedures.

Keywords: Thulium (Tm) fiber laser, laser processing of fiber-reinforced plastics (FRP), composite, heat affected zone

Procedia PDF Downloads 193

Authors: Muhammad Umar Kiani, Muhammad Shahbaz, Hassan Akbar

Abstract:

Simulation of a high speed inviscid steady ideal air flow around a 2D/axial-symmetry body was carried out by the use of mb_cns code. mb_cns is a program for the time-integration of the Navier-Stokes equations for two-dimensional compressible flows on a multiple-block structured mesh. The flow geometry may be either planar or axisymmetric and multiply-connected domains can be modeled by patching together several blocks. The main simulation code is accompanied by a set of pre and post-processing programs. The pre-processing programs scriptit and mb_prep start with a short script describing the geometry, initial flow state and boundary conditions and produce a discretized version of the initial flow state. The main flow simulation program (or solver as it is sometimes called) is mb_cns. It takes the files prepared by scriptit and mb_prep, integrates the discrete form of the gas flow equations in time and writes the evolved flow data to a set of output files. This output data may consist of the flow state (over the whole domain) at a number of instants in time. After integration in time, the post-processing programs mb_post and mb_cont can be used to reformat the flow state data and produce GIF or postscript plots of flow quantities such as pressure, temperature and Mach number. The current problem is an example of supersonic inviscid flow. The flow domain for the current problem (strake configuration wing) is discretized by a structured grid and a finite-volume approach is used to discretize the conservation equations. The flow field is recorded as cell-average values at cell centers and explicit time stepping is used to update conserved quantities. MUSCL-type interpolation and one of three flux calculation methods (Riemann solver, AUSMDV flux splitting and the Equilibrium Flux Method, EFM) are used to calculate inviscid fluxes across cell faces.

Keywords: steady flow simulation, processing programs, simulation code, inviscid flux

Procedia PDF Downloads 429

Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

Abstract:

Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

Procedia PDF Downloads 111

Authors: Ouafa Amira, Jiangshe Zhang

Abstract:

Clustering is an unsupervised machine learning technique; its aim is to extract the data structures, in which similar data objects are grouped in the same cluster, whereas dissimilar objects are grouped in different clusters. Clustering methods are widely utilized in different fields, such as: image processing, computer vision , and pattern recognition, etc. Fuzzy c-means clustering (fcm) is one of the most well known fuzzy clustering methods. It is based on solving an optimization problem, in which a minimization of a given cost function has been studied. This minimization aims to decrease the dissimilarity inside clusters, where the dissimilarity here is measured by the distances between data objects and cluster centers. The degree of belonging of a data point in a cluster is measured by a membership function which is included in the interval [0, 1]. In fcm clustering, the membership degree is constrained with the condition that the sum of a data object’s memberships in all clusters must be equal to one. This constraint can cause several problems, specially when our data objects are included in a noisy space. Regularization approach took a part in fuzzy c-means clustering technique. This process introduces an additional information in order to solve an ill-posed optimization problem. In this study, we focus on regularization by relative entropy approach, where in our optimization problem we aim to minimize the dissimilarity inside clusters. Finding an appropriate membership degree to each data object is our objective, because an appropriate membership degree leads to an accurate clustering result. Our clustering results in synthetic data sets, gaussian based data sets, and real world data sets show that our proposed model achieves a good accuracy.

Keywords: clustering, fuzzy c-means, regularization, relative entropy

Procedia PDF Downloads 259

Authors: Pallavi Malhotra

Abstract:

This paper examines the importance of ethics in cloud computing. In the modern society, cloud computing is offering individuals and businesses an unlimited space for storing and processing data or information. Most of the data and information stored in the cloud by various users such as banks, doctors, architects, engineers, lawyers, consulting firms, and financial institutions among others require a high level of confidentiality and safeguard. Cloud computing offers centralized storage and processing of data, and this has immensely contributed to the growth of businesses and improved sharing of information over the internet. However, the accessibility and management of data and servers by a third party raise concerns regarding the privacy of clients’ information and the possible manipulations of the data by third parties. This document suggests the approaches various stakeholders should take to address various ethical issues involving cloud-computing services. Ethical education and training is key to all stakeholders involved in the handling of data and information stored or being processed in the cloud.

Keywords: IT ethics, cloud computing technology, cloud privacy and security, ethical education

Procedia PDF Downloads 325

Authors: Sungho Kim, Dae Shik Kim, Jong Min Lee

Abstract:

Fluid catalytic cracking (FCC) process is one of the most important process in modern refinery industry. This paper focuses on the fluid catalytic cracking (FCC) process. As the FCC process is difficult to model well, due to its non linearities and various interactions between its process variables, rigorous process modeling of whole FCC plant is demanded for control and plant-wide optimization of the plant. In this study, a process design for the FCC plant includes riser reactor, main fractionator, and gas processing unit was developed. A reactor model was described based on four-lumped kinetic scheme. Main fractionator, gas processing unit and other process units are designed to simulate real plant data, using a process flow sheet simulator, Aspen PLUS. The custom reactor model was integrated with the process flow sheet simulator to develop an integrated process model.

Keywords: fluid catalytic cracking, simulation, plant data, process design

Procedia PDF Downloads 529

Authors: Ariangelo Hauer Dias Filho, Gustavo Antoniácomi de Carvalho, Benjamim de Melo Carvalho

Abstract:

The work´s purpose was to evaluate the possibility of manufacturing casting tools utilizing Fused Filament Fabrication, a 3D printing technique, without any post-processing on the printed part. Taguchi Orthogonal array was used to evaluate the influence of extrusion temperature, bed temperature, layer height, and infill on the dimensional accuracy of a 3D-Printed Polymer Model. A Zeiss T-SCAN CS 3D Scanner was used for dimensional evaluation of the printed parts within the limit of ±0,2 mm. The mold capabilities were tested with the printed model to check how it would interact with the green sand. With little adjustments in the 3D model, it was possible to produce rapid tools without the need for post-processing for iron casting. The results are important for reducing time and cost in the development of such tools.

Keywords: additive manufacturing, Taguchi method, rapid tooling, fused filament fabrication, casting mold

Procedia PDF Downloads 142

Authors: David Muyise

Abstract:

Mixed Integer Programming (MIP) is an approach that involves the optimization of a range of decision variables in order to minimize or maximize a particular objective function. The main objective of this study was to apply the MIP approach to optimize the deployment of waste plastic to fuel oil processing plants in Uganda. The processing plants are meant to reduce plastic pollution by pyrolyzing the waste plastic into a cleaner fuel that can be used to power diesel/paraffin engines, so as (1) to reduce the negative environmental impacts associated with plastic pollution and also (2) to curb down the energy gap by utilizing the fuel oil. A programming model was established and tested in two case study applications that are, small-scale applications in rural towns and large-scale deployment across major cities in the country. In order to design the supply chain, optimal decisions on the types of waste plastic to be processed, size, location and number of plants, and downstream fuel applications were concurrently made based on the payback period, investor requirements for capital cost and production cost of fuel and electricity. The model comprises qualitative data gathered from waste plastic pickers at landfills and potential investors, and quantitative data obtained from primary research. It was found out from the study that a distributed system is suitable for small rural towns, whereas a decentralized system is only suitable for big cities. Small towns of Kalagi, Mukono, Ishaka, and Jinja were found to be the ideal locations for the deployment of distributed processing systems, whereas Kampala, Mbarara, and Gulu cities were found to be the ideal locations initially utilize the decentralized pyrolysis technology system. We conclude that the model findings will be most important to investors, engineers, plant developers, and municipalities interested in waste plastic to fuel processing in Uganda and elsewhere in developing economy.

Keywords: mixed integer programming, fuel oil plants, optimisation of waste plastics, plastic pollution, pyrolyzing

Procedia PDF Downloads 129

Authors: Nabila Mohamed, Santiago Aparicio, Bahman Tohidi, Mert Atilhan

Abstract:

Qatar's one of the biggest problem in processing its natural resource, which is natural gas, is the often occurring blockage in the pipelines caused due to uncontrolled gas hydrate formation in the pipelines. Several millions of dollars are being spent at the process site to dehydrate the blockage safely by using chemical inhibitors. We aim to establish national database, which addresses the physical conditions that promotes Qatari natural gas to form gas hydrates in the pipelines. Moreover, we aim to design and test novel hydrate inhibitors that are suitable for Qatari natural gas and its processing facilities. From these perspectives we are aiming to provide more effective and sustainable reservoir utilization and processing of Qatari natural gas. In this work, we present the initial findings of a QNRF funded project, which deals with the natural gas hydrate formation characteristics of Qatari type gas in both experimental (PVTx) and computational (molecular simulations) methods. We present the data from the two fully automated apparatus: a gas hydrate autoclave and a rocking cell. Hydrate equilibrium curves including growth/dissociation conditions for multi-component systems for several gas mixtures that represent Qatari type natural gas with and without the presence of well known kinetic and thermodynamic hydrate inhibitors. Ionic liquids were designed and used for testing their inhibition performance and their DFT and molecular modeling simulation results were also obtained and compared with the experimental results. Results showed significant performance of ionic liquids with up to 0.5 % in volume with up to 2 to 4 0C inhibition at high pressures.

Keywords: gas hydrates, natural gas, ionic liquids, inhibition, thermodynamic inhibitors, kinetic inhibitors

Procedia PDF Downloads 1320

Authors: Charlotte Entwistle, Ryan Boyd

Abstract:

Recent developments in information retrieval techniques and natural language processing have allowed for greater exploration of psychological and social processes. Linguistic analysis methods for understanding behaviour have provided useful insights within the field of mental health. One area within mental health that has received little attention though, is borderline personality disorder (BPD). BPD is a common mental health disorder characterised by instability of interpersonal relationships, self-image and affect. It also manifests through maladaptive behaviours, such as impulsivity and self-harm. Examination of language patterns associated with BPD could allow for a greater understanding of the disorder and its links to maladaptive thoughts and behaviours. Language analysis methods could also be used in a predictive way, such as by identifying indicators of BPD or predicting maladaptive thoughts, emotions and behaviours. Additionally, associations that are uncovered between language and maladaptive thoughts and behaviours could then be applied at a more general level. This study explores linguistic characteristics of BPD, and their links to maladaptive thoughts and behaviours, through the analysis of social media data. Data were collected from a large corpus of posts from the publicly available social media platform Reddit, namely, from the ‘r/BPD’ subreddit whereby people identify as having BPD. Data were collected using the Python Reddit API Wrapper and included all users which had posted within the BPD subreddit. All posts were manually inspected to ensure that they were not posted by someone who clearly did not have BPD, such as people posting about a loved one with BPD. These users were then tracked across all other subreddits of which they had posted in and data from these subreddits were also collected. Additionally, data were collected from a random control group of Reddit users. Disorder-relevant behaviours, such as self-harming or aggression-related behaviours, outlined within Reddit posts were coded to by expert raters. All posts and comments were aggregated by user and split by subreddit. Language data were then analysed using the Linguistic Inquiry and Word Count (LIWC) 2015 software. LIWC is a text analysis program that identifies and categorises words based on linguistic and paralinguistic dimensions, psychological constructs and personal concern categories. Statistical analyses of linguistic features could then be conducted. Findings revealed distinct linguistic features associated with BPD, based on Reddit posts, which differentiated these users from a control group. Language patterns were also found to be associated with the occurrence of maladaptive thoughts and behaviours. Thus, this study demonstrates that there are indeed linguistic markers of BPD present on social media. It also implies that language could be predictive of maladaptive thoughts and behaviours associated with BPD. These findings are of importance as they suggest potential for clinical interventions to be provided based on the language of people with BPD to try to reduce the likelihood of maladaptive thoughts and behaviours occurring. For example, by social media tracking or engaging people with BPD in expressive writing therapy. Overall, this study has provided a greater understanding of the disorder and how it manifests through language and behaviour.

Keywords: behaviour analysis, borderline personality disorder, natural language processing, social media data

Procedia PDF Downloads 349

Authors: Mohamed K. Metwally, Sherif H. El-Gohary, Kyung Min Byun, Seung Moo Han, Soo Yeol Lee, Min Hyoung Cho, Gon Khang, Jinsung Cho, Tae-Seong Kim

Abstract:

Photoacoustic imaging (PAI) is a non-invasive and non-ionizing imaging modality that combines the absorption contrast of light with ultrasound resolution. Laser is used to deposit optical energy into a target (i.e., optical fluence). Consequently, the target temperature rises, and then thermal expansion occurs that leads to generating a PA signal. In general, most image reconstruction algorithms for PAI assume uniform fluence within an imaging object. However, it is known that optical fluence distribution within the object is non-uniform. This could affect the reconstruction of PA images. In this study, we have investigated the influence of optical fluence distribution on PA back-propagation imaging using finite element method. The uniform fluence was simulated as a triangular waveform within the object of interest. The non-uniform fluence distribution was estimated by solving light propagation within a tissue model via Monte Carlo method. The results show that the PA signal in the case of non-uniform fluence is wider than the uniform case by 23%. The frequency spectrum of the PA signal due to the non-uniform fluence has missed some high frequency components in comparison to the uniform case. Consequently, the reconstructed image with the non-uniform fluence exhibits a strong smoothing effect.

Keywords: finite element method, fluence distribution, Monte Carlo method, photoacoustic imaging

Procedia PDF Downloads 378

Authors: Madushani Rodrigo, Banuka Athuraliya

Abstract:

In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

Procedia PDF Downloads 120

Authors: Anum Javed

Abstract:

This study identifies the dynamical image of human body that continues its metamorphosis in the virtual field of reality. It calls attention to the ways where humans start co-evolving with other life forms; technology in particular and are striving to establish a realm outside the physical framework of matter. The problem exceeds the area of technological ethics by explicably and explanatorily entering the space of literary texts and criticism. Textual analysis of Geek Love (1989) by Katherine Dunn is adjoined with posthumanist perspectives of Pramod K. Nayar to beget psycho-somatic changes in man’s nature of being. It uncovers the meaning people give to their experiences in this budding social and cultural phenomena of material representation tied up with personal practices and technological innovations. It also observes an ethical, physical and psychological reassessment of man within the context of technological evolutions. The study indicates the elements that have rendered morphological freedom and new materialism in man’s consciousness. Moreover this work is inquisitive of what it means to be a human in this time of accelerating change where surgeries, implants, extensions, cloning and robotics have shaped a new sense of being. It attempts to go beyond individual’s body image and explores how objectifying media and culture have influenced people’s judgement of others on new material grounds. It further argues a decentring of the glorified image of man as an independent entity because of his energetic partnership with intelligent machines and external agents. The history of the future progress of technology is also mentioned. The methodology adopted is posthumanist techno-ethical textual analysis. This work necessitates a negotiating relationship between man and technology in order to achieve harmonic and balanced interconnected existence. The study concludes by recommending a call for an ethical set of codes to be cultivated for the techno-human habituation. Posthumanism ushers a strong need of adopting new ethics within the terminology of neo-materialist humanism.

Keywords: corporeality, dematerialism, human ethos, posthumanism

Procedia PDF Downloads 147

Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

Abstract:

The modeling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high-resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve denser and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high-resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D models, environment, matching, pleiades

Procedia PDF Downloads 330

Authors: Alexandra-Monica Toma

Abstract:

As the internet became a ruling force of society, computer-mediated communication has enriched its methods to convey meaning by combining linguistic means to visual means of expressivity. One of the elements of cyberspace is what we call a meme, a succinct, visually engaging tool used to communicate ideas or emotions, usually in a funny or ironic manner. Coined by Richard Dawkings in the late 1970s to refer to cultural genes, this term now denominates a special type of vernacular language used to share content on the internet. This research aims to analyse the basic mechanism that stands at the basis of meme creation as a blend of innovation and imitation and will approach some of the most widely used image macros remixed to generate new content while also pointing out success strategies. Moreover, this paper discusses whether memes can transcend the light-hearted and playful mood they mirror and become biting and sharp cultural comments. The study also uses the concept of multimodality and stresses how the text interacts with image, discussing three types of relations between the two: symmetry, amplification, and contradiction. We will furthermore show that memes are cultural artifacts and virtual tropes highly dependent on context and societal issues by using a corpus of memes created related to the COVID-19 pandemic.

Keywords: context, computer-mediated communication, memes, multimodality

Procedia PDF Downloads 184

Authors: Yufen Qin

Abstract:

Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

Procedia PDF Downloads 236

Authors: Shriya Shukla, Lachin Fernando

Abstract:

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

Procedia PDF Downloads 125

Authors: Sh. Khoshemehry, M. E. Bahram, M. J. Pourvaghar

Abstract:

Sport has found a special place as an effective phenomenon in all societies of the contemporary world. The relationship between physical activity and exercise with different sciences has provided new fields for human study. The range of issues related to exercise and physical education is such that it requires specialized sciences and special studies. In this article, the psychological and social sections of exercise have been investigated for children and adults. It can be used for anyone in different age groups. Exercise and regular physical movements have a great impact on the mental and social health of the individual in addition to body health. It affects the individual's adaptability in society and his/her personality. Exercise affects the treatment of diseases such as depression, anxiety, stress, body image, and memory. Exercise is a safe haven for young people to achieve the optimum human development in its shelter. The effects of sensorimotor skills on mental actions and mental development are such a way that many psychologists and sports science experts believe these activities should be included in training programs in the first place. Familiarity of students and scholars with different programs and methods of sensorimotor activities not only causes their mental actions; but also increases mental health and vitality, enhances self-confidence and, therefore, mental health.

Keywords: anxiety, mental health, physical activity, serotonin

Procedia PDF Downloads 207

Authors: Magali Mari, Fabrice Clement

Abstract:

The present study investigated the influence of implicit stereotypes on adults’ visual information processing, using an eye-tracking device. Implicit stereotyping is an automatic and implicit process; it happens relatively quickly, outside of awareness. In the presence of a member of a social group, a set of expectations about the characteristics of this social group appears automatically in people’s minds. The study aimed to shed light on the cognitive processes involved in stereotyping and to further investigate the use of eye movements to measure implicit stereotypes. With an eye-tracking device, the eye movements of participants were analyzed, while they viewed everyday scenes depicting women and men in congruent or incongruent gender role activities (e.g., a woman ironing or a man ironing). The settings of these scenes had to be analyzed to infer the character’s role. Also, participants completed an implicit association test that combined the concept of gender with attributes of occupation (home/work), while measuring reaction times to assess participants’ implicit stereotypes about gender. The results showed that implicit stereotypes do influence people’s visual attention; within a fraction of a second, the number of returns, between stereotypical and counter-stereotypical scenes, differed significantly, meaning that participants interpreted the scene itself as a whole before identifying the character. They predicted that, in such a situation, the character was supposed to be a woman or a man. Also, the study showed that eye movements could be used as a fast and reliable supplement for traditional implicit association tests to measure implicit stereotypes. Altogether, this research provides further understanding of implicit stereotypes processing as well as a natural method to study implicit stereotypes.

Keywords: eye-tracking, implicit stereotypes, social cognition, visual attention

Procedia PDF Downloads 159

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 359

Authors: Andrey V. Timofeev, Dmitry Egorov

Abstract:

This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the suggested approach allows to control super-extended objects with very limited operational costs. So-called C-OTDR (Coherent Optical Time Domain Reflectometer) systems are used to monitor the seismoacoustic field. Far-CCTV systems are used to monitor the optical/infrared field. A simultaneous data processing provided by both systems allows effectively detecting and classifying target activities, which appear in the monitored objects vicinity. The results of practical usage had shown high effectiveness of the suggested approach.

Keywords: C-OTDR monitoring system, bimodal processing, LPboost, SVM

Procedia PDF Downloads 470

Authors: Chao Wang

Abstract:

Under rapid innovation of information technology, the media plays a very important role in the dissemination of information, and it has a totally different analogy generations face. However, the involvement of narrative images provides more possibilities of narrative text. "Images" through the process of aperture, a camera shutter and developable photosensitive processes are manufactured, recorded and stamped on paper, displayed on a computer screen-concretely saved. They exist in different forms of files, data, or evidence as the ultimate looks of events. By the interface of media and network platforms and special visual field of the viewer, class body space exists and extends out as thin as sebum layer, extremely soft and delicate with real full tension. The physical space of sebum layer of confuses the fact that physical objects exist, needs to be established under a perceived consensus. As at the scene, the existing concepts and boundaries of physical perceptions are blurred. Sebum layer physical simulation shapes the “Topical-Similarity" immersing, leading the contemporary social practice communities, groups, network users with a kind of illusion without the presence, i.e. a non-real illusion. From the investigation and discussion of literatures, digital movies editing manufacture and produce the variability characteristics of time (for example, slices, rupture, set, and reset) are analyzed. Interactive eBook has an unique interaction in "Waiting-Greeting" and "Expectation-Response" that makes the operation of image narrative structure more interpretations functionally. The works of digital editing and interactive technology are combined and further analyze concept and results. After digitization of Interventional Imaging and interactive technology, real events exist linked and the media handing cannot be cut relationship through movies, interactive art, practical case discussion and analysis. Audience needs more rational thinking about images carried by the authenticity of the text.

Keywords: sebum layer, topical and similarity, interactive technology, image narrative

Procedia PDF Downloads 389

Authors: Narin Salehiyan, Ramin Ghasemi Shayan

Abstract:

In order to investigate coronavirus RNA replication, transcription, recombination, protein processing and transport, virion assembly, the identification of coronavirus-specific cell receptors, and polymerase processing, the manipulation of coronavirus clones and complementary DNAs (cDNAs) of defective-interfering (DI) RNAs is the subject of this chapter. The idea of the Covid genome is nonsegmented, single-abandoned, and positive-sense RNA. When compared to other RNA viruses, its size is significantly greater, ranging from 27 to 32 kb. The quality encoding the enormous surface glycoprotein depends on 4.4 kb, encoding a forcing trimeric, profoundly glycosylated protein. This takes off exactly 20 nm over the virion envelope, giving the infection the appearance-with a little creative mind of a crown or coronet. Covid research has added to the comprehension of numerous parts of atomic science as a general rule, like the component of RNA union, translational control, and protein transport and handling. It stays a fortune equipped for creating startling experiences.

Keywords: covid-19, corona, virus, genome, genetic

Procedia PDF Downloads 72

Authors: Igor Faulmann, Arnaud Saj, Roland Maurer

Abstract:

Spatial cognition consists in a plethora of high level cognitive abilities: among them, the ability to learn and to navigate in large scale environments is probably one of the most complex skills. Navigation is thought to rely on the ability to read a cognitive map, defined as an allocentric representation of ones environment. Those representations are of course intimately related to the two geometrical primitives of the environment: distance and direction. Also, many recent studies point to a predominant hippocampal and para-hippocampal role in spatial cognition, as well as in the more specific cluster of navigational skills. In a previous study in humans, we used a newly validated test assessing cognitive map processing by evaluating the ability to judge relative distances and directions: the CMRT (Cognitive Map Recall Test). This study identified in topographically disorientated patients (1) behavioral differences between the evaluation of distances and of directions, and (2) distinct causality patterns assessed via VLSM (i.e., distinct cerebral lesions cause distinct response patterns depending on the modality (distance vs direction questions). Thus, we hypothesized that: (1) if the CMRT really taps into the same resources as real navigation, there would be hippocampal, parahippocampal, and parietal activation, and (2) there exists underlying neuroanatomical and functional differences between the processing of this two modalities. Aiming toward a better understanding of the neuroanatomical correlates of the CMRT in humans, and more generally toward a better understanding of how the brain processes the cognitive map, we adapted the CMRT as an fMRI procedure. 23 healthy subjects (11 women, 12 men), all living in Geneva for at least 2 years, underwent the CMRT in fMRI. Results show, for distance and direction taken together, than the most active brain regions are the parietal, frontal and cerebellar parts. Additionally, and as expected, patterns of brain activation differ when comparing the two modalities. Furthermore, distance processing seems to rely more on parietal regions (compared to other brain regions in the same modality and also to direction). It is interesting to notice that no significant activity was observed in the hippocampal or parahippocampal areas. Direction processing seems to tap more into frontal and cerebellar brain regions (compared to other brain regions in the same modality and also to distance). Significant hippocampal and parahippocampal activity has been shown only in this modality. This results demonstrated a complex interaction of structures which are compatible with response patterns observed in other navigational tasks, thus showing that the CMRT taps at least partially into the same brain resources as real navigation. Additionally, differences between the processing of distances and directions leads to the conclusion that the human brain processes each modality distinctly. Further research should focus on the dynamics of this processing, allowing a clearer understanding between the two sub-processes.

Keywords: cognitive map, navigation, fMRI, spatial cognition

Procedia PDF Downloads 294

Authors: Fatemeh Noori

Abstract:

The fashion industry is a dynamic and ever-evolving realm that continuously shapes societal perceptions of beauty and style. Within this industry, fashion modeling plays a crucial role, acting as the visual representation of brands and designers. However, behind the glamorous façade lies a complex web of legal considerations that govern the rights, responsibilities, and ethical practices within the field. This paper aims to explore the legal landscape surrounding fashion modeling, shedding light on key issues such as contract law, intellectual property, labor rights, and the increasing importance of ethical considerations in the industry. Fashion modeling involves the collaboration of various stakeholders, including models, designers, agencies, and photographers. To ensure a fair and transparent working environment, it is imperative to establish a comprehensive legal framework that addresses the rights and obligations of each party involved. One of the primary legal considerations in fashion modeling is the contractual relationship between models and agencies. Contracts define the terms of engagement, including payment, working conditions, and the scope of services. This section will delve into the essential elements of modeling contracts, the negotiation process, and the importance of clarity to avoid disputes. Models are not just individuals showcasing clothing; they are integral to the creation and dissemination of artistic and commercial content. Intellectual property rights, including image rights and the use of a model's likeness, are critical aspects of the legal landscape. This section will explore the protection of models' image rights, the use of their likeness in advertising, and the potential for unauthorized use. Models, like any other professionals, are entitled to fair and ethical treatment. This section will address issues such as working conditions, hours, and the responsibility of agencies and designers to prioritize the well-being of models. Additionally, it will explore the global movement toward inclusivity, diversity, and the promotion of positive body image within the industry. The fashion industry has faced scrutiny for perpetuating harmful standards of beauty and fostering a culture of exploitation. This section will discuss the ethical responsibilities of all stakeholders, including the promotion of diversity, the prevention of exploitation, and the role of models as influencers for positive change. In conclusion, the legal considerations in fashion modeling are multifaceted, requiring a comprehensive approach to protect the rights of models and ensure ethical practices within the industry. By understanding and addressing these legal aspects, the fashion industry can create a more transparent, fair, and inclusive environment for all stakeholders involved in the art of modeling.

Keywords: fashion modeling contracts, image rights in modeling, labor rights for models, ethical practices in fashion, diversity and inclusivity in modeling

Procedia PDF Downloads 77

Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum

Abstract:

Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.

Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value

Procedia PDF Downloads 412

Authors: Yongqin Zhang, John Lett

Abstract:

Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.

Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements

Procedia PDF Downloads 75

Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

Abstract:

Indonesia as an archipelagic nation have very long coastline which have large potential marine resources, one of that is the mangrove ecosystems. Lapindo mudflow disaster in Sidoarjo, East Java requires mudflow flowed into the sea through the river Brantas and Porong. Mud material that transported by river flow is feared dangerous because they contain harmful substances such as heavy metals. This study aims to map the mangrove ecosystem seen from its density and knowing how big the impact of a disaster on the Lapindo mud to mangrove ecosystem and accompanied by efforts to address the mangrove ecosystem that maintained continuity. Mapping coastal mangrove conditions of Sidoarjo was done using remote sensing products that Landsat 7 ETM + images with dry months of recording time in 2002, 2006, 2009, and 2014. The density of mangrove detected using NDVI that uses the band 3 that is the red channel and band 4 that is near IR channel. Image processing was used to produce NDVI using ENVI 5.1 software. NDVI results were used for the detection of mangrove density is 0-1. The development of mangrove ecosystems of both area and density from year to year experienced has a significant increase. Mangrove ecosystems growths are affected by material deposition area of Lapindo mud on Porong and Brantas river estuary, where the silt is growing medium suitable mangrove ecosystem and increasingly growing. Increasing the density caused support by public awareness to prevent heavy metals in the material so that the Lapindo mud mangrove breeding done around the farm.

Keywords: archipelagic nation, mangrove, Lapindo mudflow disaster, NDVI

Procedia PDF Downloads 438

Authors: Mulugeta K. Tefera, Xiaolong Yang, Jian Liu

Abstract:

Detection and tracking of moving objects are very important in many application contexts such as detection and recognition of people, visual surveillance and automatic generation of video effect and so on. However, the task of detecting a real shape of an object in motion becomes tricky due to various challenges like dynamic scene changes, presence of shadow, and illumination variations due to light switch. For such systems, once the moving object is detected, tracking is also a crucial step for those applications that used in military defense, video surveillance, human computer interaction, and medical diagnostics as well as in commercial fields such as video games. In this paper, an object presents in dynamic background is detected using adaptive mixture of Gaussian based analysis of the video sequences. Then the detected moving object is tracked using the region based moving object tracking and inter-frame differential mechanisms to address the partial overlapping and occlusion problems. Firstly, the detection algorithm effectively detects and extracts the moving object target by enhancing and post processing morphological operations. Secondly, the extracted object uses region based moving object tracking and inter-frame difference to improve the tracking speed of real-time moving objects in different video frames. Finally, the plotting method was applied to detect the moving objects effectively and describes the object’s motion being tracked. The experiment has been performed on image sequences acquired both indoor and outdoor environments and one stationary and web camera has been used.

Keywords: background modeling, Gaussian mixture model, inter-frame difference, object detection and tracking, video surveillance

Procedia PDF Downloads 477