Search results for: image manipulation
1103 Factors Affecting Sense of Community in Residential Communities Case Study: Residential Communities in Tehran, Iran
Authors: Parvin Foroughifar
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The concept of sense of community refers to residents’ sense of attachment and commitment to the other residents in a residential community. It is implicitly indicative of the mental image of a physical environment in which the residents enjoy strong social ties. Sense of community, a crucial factor in improving quality of life and social welfare, leads to life satisfaction in a residential community. Despite the important functions of such a notion, few empirical studies, to the best of the authors' knowledge, have been so far carried out in Iran to investigate the effective factors in sharpening the sense of community in residential communities. This survey research examined sense of community in 360 above 20-year old residents of three residential communities in Tehran, Iran using cluster sampling and questionnaire. The study yielded the result that variables of local social ties, social control and trust, sense of security, length of residence, use of public spaces, and mixed land use have a significant relationship with sense of community.Keywords: sense of community, local social ties, sense of security, public space, residential community, Tehran
Procedia PDF Downloads 1911102 Efficient Layout-Aware Pretraining for Multimodal Form Understanding
Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose
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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention
Procedia PDF Downloads 1511101 Automatic Method for Exudates and Hemorrhages Detection from Fundus Retinal Images
Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar
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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages
Procedia PDF Downloads 2731100 Digital Watermarking Using Fractional Transform and (k,n) Halftone Visual Cryptography (HVC)
Authors: R. Rama Kishore, Sunesh Malik
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Development in the usage of internet for different purposes in recent times creates great threat for the copy right protection of the digital images. Digital watermarking is the best way to rescue from the said problem. This paper presents detailed review of the different watermarking techniques, latest trends in the field and categorized like spatial and transform domain, blind and non-blind methods, visible and non visible techniques etc. It also discusses the different optimization techniques used in the field of watermarking in order to improve the robustness and imperceptibility of the method. Different measures are discussed to evaluate the performance of the watermarking algorithm. At the end, this paper proposes a watermarking algorithm using (k.n) shares of halftone visual cryptography (HVC) instead of (2, 2) share cryptography. (k,n) shares visual cryptography improves the security of the watermark. As halftone is a method of reprographic, it helps in improving the visual quality of watermark image. The proposed method uses fractional transformation to improve the robustness of the copyright protection of the method.Keywords: digital watermarking, fractional transform, halftone, visual cryptography
Procedia PDF Downloads 3571099 Monocular 3D Person Tracking AIA Demographic Classification and Projective Image Processing
Authors: McClain Thiel
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Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.Keywords: monocular distancing, computer vision, facial analysis, 3D localization
Procedia PDF Downloads 1421098 Ambivalence in Embracing Artificial Intelligence in the Units of a Public Hospital in South Africa
Authors: Sanele E. Nene L., Lia M. Hewitt
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Background: Artificial intelligence (AI) has a high value in healthcare, various applications have been developed for the efficiency of clinical operations, such as appointment/surgery scheduling, diagnostic image analysis, prognosis, prediction and management of specific ailments. Purpose: The purpose of this study was to explore, describe, contrast, evaluate, and develop the various leadership strategies as a conceptual framework, applied by public health Operational Managers (OMs) to embrace AI benefits, with the aim to improve the healthcare system in a public hospital. Design and Method: A qualitative, exploratory, descriptive and contextual research design was followed and a descriptive phenomenological approach. Five phases were followed to conduct this study. Phenomenological individual interviews and focus groups were used to collect data and a phenomenological thematic data analysis method was used. Findings and conclusion: Three themes surfaced as the experiences of AI by the OMs; Positive experiences related to AI, Management and leadership processes in AI facilitation, and Challenges related to AI.Keywords: ambivalence, embracing, Artificial intelligence, public hospital
Procedia PDF Downloads 801097 Early Detection of Lymphedema in Post-Surgery Oncology Patients
Authors: Sneha Noble, Rahul Krishnan, Uma G., D. K. Vijaykumar
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Breast-Cancer related Lymphedema is a major problem that affects many women. Lymphedema is the swelling that generally occurs in the arms or legs caused by the removal of or damage to lymph nodes as a part of cancer treatment. Treating it at the earliest possible stage is the best way to manage the condition and prevent it from leading to pain, recurrent infection, reduced mobility, and impaired function. So, this project aims to focus on the multi-modal approaches to identify the risks of Lymphedema in post-surgical oncology patients and prevent it at the earliest. The Kinect IR Sensor is utilized to capture the images of the body and after image processing techniques, the region of interest is obtained. Then, performing the voxelization method will provide volume measurements in pre-operative and post-operative periods in patients. The formation of a mathematical model will help in the comparison of values. Clinical pathological data of patients will be investigated to assess the factors responsible for the development of lymphedema and its risks.Keywords: Kinect IR sensor, Lymphedema, voxelization, lymph nodes
Procedia PDF Downloads 1381096 Nanostructural Analysis of the Polylactic Acid (PLA) Fibers Functionalized by RF Plasma Treatment
Authors: J. H. O. Nascimento, F. R. Oliveira, K. K. O. S. Silva, J. Neves, V. Teixeira, J. Carneiro
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These the aliphatic polyesters such as Polylactic Acid (PLA) in the form of fibers, nanofibers or plastic films, generally possess chemically inert surfaces, free porosity, and surface free energy (ΔG) lesser than 32 mN/m. It is therefore considered a low surface energy material, consequently has a low work of adhesion. For this reason, the products manufactured using these polymers are often subjected to surface treatments in order to change its physic-chemical surface, improving their wettability and the Work of Adhesion (WA). Plasma Radio Frequency low pressure (RF) treatment was performed in order to improve the Work of Adhesion (WA) on PLA fibers. Different parameters, such as, power, ratio of working gas (Argon/Oxygen) and treatment time were used to optimize the plasma conditions to modify the PLA surface properties. With plasma treatment, a significant increase in the work of adhesion on PLA fiber surface was observed. The analysis performed by XPS showed an increase in polar functional groups and the SEM and AFM image revealed a considerable increase in roughness.Keywords: RF plasma, surface modification, PLA fabric, atomic force macroscopic, Nanotechnology
Procedia PDF Downloads 5391095 Land Use Change Detection Using Remote Sensing and GIS
Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi
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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.Keywords: Haraz basin, change detection, land-use, satellite data
Procedia PDF Downloads 4151094 Authenticity and Performance in Political Leadership: Social Media’s Role in Shaping Public Perceptions
Authors: Simbarashe Nzvere
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In an era dominated by digital communication, social media has become a powerful tool for political leaders to connect with the public, shape their narratives, and influence perceptions. With this much performance from political leaders, this paper will explore the dichotomy between authenticity and performance in the digital personas of political leaders. By examining how leaders craft their image on platforms such as X (Formerly Twitter), Facebook, Instagram, and Linked In, this study investigates whether these portrayals align with their true character or represent a strategic facade designed to resonate with target audiences. Utilizing case studies and content analysis, the research delves into the methods leaders employ to construct their online identities, the role of digital marketing teams in shaping these images, and the implications for public trust and political engagement. The findings highlight the complex interplay between genuine representation and strategic branding, offering insights into how social media reshapes political leadership in the 21st century.Keywords: political leadership, social media, authenticity, public perceptions, digital persona
Procedia PDF Downloads 81093 A Generalized Sparse Bayesian Learning Algorithm for Near-Field Synthetic Aperture Radar Imaging: By Exploiting Impropriety and Noncircularity
Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle
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The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.Keywords: complex-valued signal processing, synthetic aperture radar, 2-D radar imaging, compressive sensing, sparse Bayesian learning
Procedia PDF Downloads 1331092 Lean Comic GAN (LC-GAN): a Light-Weight GAN Architecture Leveraging Factorized Convolution and Teacher Forcing Distillation Style Loss Aimed to Capture Two Dimensional Animated Filtered Still Shots Using Mobile Phone Camera and Edge Devices
Authors: Kaustav Mukherjee
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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parametersKeywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss
Procedia PDF Downloads 1331091 Modelling and Simulation of Milk Fouling
Authors: Harche Rima, Laoufi Nadia Aicha
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This work focuses on the study and modeling of the fouling phenomenon in a vertical pipe. In the first step, milk is one of the fluids obeying the phenomenon of fouling because of the denaturation of these proteins, especially lactoglobulin, which is the active element of milk, and to facilitate its use, we chose to study milk as a fouling fluid. In another step, we consider the test section of our installation as a tubular-type heat exchanger that works against the current and in a closed circuit. A simple mathematical model of Kern & Seaton, based on the kinetics of the fouling resistance, was used to evaluate the influence of the operating parameters (fluid flow velocity and exchange wall temperature) on the fouling resistance. The influence of the variation of the fouling resistance with the operating conditions on the efficiency of the heat exchanger and the importance of the dirty state exchange coefficient as an exchange quality control parameter were discussed and examined. On the other hand, an electronic scanning microscope analysis was performed on the milk deposit in order to obtain its actual image and composition, which allowed us to calculate the thickness of this deposit.Keywords: fouling, milk, tubular heat exchanger, fouling resistance
Procedia PDF Downloads 591090 The National Idea and Selthindentification of Nation is the Foundation of the Society’s Development
Authors: K. Aisultanova, O. Abdimanuly
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The article is told about the factors influencing the formation of the national idea and national identity. Paying attention to the idea and purpose of 'Eternal county', historical dates and examples are given. The structure of the idea 'The eternal country' by ancient Turks is discussed and the history of the legend prevalent among the Kazakh people, the image of the mythical historical figures are analyzed. Al-Farabi’s philosophical work 'Honest city', Zhysip Balasagun’s poem 'Happy Knowledge' are told, the opinions of scholars researching the nation's history, literature, and culture are given. As international experience shows, the idea of a new stage in the development of the country's great national society and the state for the purpose of political, social, economic, cultural, spiritual, and the other efforts are consolidated. The idea of the national, ethnic, religious, cultural and other communities united by a group of people sharing a collective memory, goals, ideas and dreams and , world view, a complex set of beliefs and values are expressed.Keywords: independence, historical process, national idea, the national ideology, society, state
Procedia PDF Downloads 3051089 Identification of High Stress Regions in Proximal Femur During Single-Leg Stance and Sideways Fall Using QCT-Based Finite Element Model
Authors: Hossein Kheirollahi, Yunhua Luo
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Studying stress and strain trends in the femur and recognizing femur failure mechanism is very important for preventing hip fracture in the elderly. The aim of this study was to identify high stress and strain regions in the femur during normal walking and falling to find the mechanical behavior and failure mechanism of the femur. We developed a finite element model of the femur from the subject’s quantitative computed tomography (QCT) image and used it to identify potentially high stress and strain regions during the single-leg stance and the sideways fall. It was found that fracture may initiate from the superior region of femoral neck and propagate to the inferior region during a high impact force such as sideways fall. The results of this study showed that the femur bone is more sensitive to strain than stress which indicates the effect of strain, in addition to effect of stress, should be considered for failure analysis.Keywords: finite element analysis, hip fracture, strain, stress
Procedia PDF Downloads 5041088 Digital Musical Organology: The Audio Games: The Question of “A-Musicological” Interfaces
Authors: Hervé Zénouda
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This article seeks to shed light on an emerging creative field: "Audio games," at the crossroads between video games and computer music. Indeed, many applications, which propose entertaining audio-visual experiences with the objective of musical creation, are available today for different supports (game consoles, computers, cell phones). The originality of this field is the use of the gameplay of video games applied to music composition. Thus, composing music using interfaces but also cognitive logics that we qualify as "a-musicological" seem to us particularly interesting from the perspective of musical digital organology. This field raises questions about the representation of sound and musical structures and develops new instrumental gestures and strategies of musical composition. We will try in this article to define the characteristics of this field by highlighting some historical milestones (abstract cinema, game theory in music, actions, and graphic scores) as well as the novelties brought by digital technologies.Keywords: audio-games, video games, computer generated music, gameplay, interactivity, synesthesia, sound interfaces, relationships image/sound, audiovisual music
Procedia PDF Downloads 1131087 A Simple and Easy-To-Use Tool for Detecting Outer Contour of Leukocytes Based on Image Processing Techniques
Authors: Retno Supriyanti, Best Leader Nababan, Yogi Ramadhani, Wahyu Siswandari
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Blood cell morphology is an important parameter in a hematology test. Currently, in developing countries, a lot of hematology is done manually, either by physicians or laboratory staff. According to the limitation of the human eye, examination based on manual method will result in a lower precision and accuracy. In addition, the hematology test by manual will further complicate the diagnosis in some areas that do not have competent medical personnel. This research aims to develop a simple tool in the detection of blood cell morphology-based computer. In this paper, we focus on the detection of the outer contour of leukocytes. The results show that the system that we developed is promising for detecting blood cell morphology automatically. It is expected, by implementing this method, the problem of accuracy, precision and limitations of the medical staff can be solved.Keywords: morphology operation, developing countries, hematology test, limitation of medical personnel
Procedia PDF Downloads 3391086 Shaabi in the City: On Modernizing Sounds and Exclusion in Egyptian Cities
Authors: Mariam Aref Mahmoud
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After centuries of historical development, Egypt is no stranger to national identity frustrations. What may or may not be counted as this “national identity” becomes a source of contention. Today, after decades of neoliberal reform, Cairo has become the center of Egypt’s cultural debacle. At its heart, the Egyptian capital serves as Egypt’s extension into global capitalism, its flailing hope to become part of the modernized, cosmopolitan world. Yet, to converge into this image of cosmopolitanism, Cairo must silence the perceived un-modernized sounds, cultures, and spaces that arise from within its alleyways. Currently, the agitation surrounding shaabi music, particularly, that of mahraganat, places these contentions to the center of the modernization debates. This paper will discuss the process through which the conversations between modernization, space, and culture have taken place through a historical analysis of national identity formation under Egypt’s neoliberal regimes. Through this, the paper concludes that music becomes a spatial force through which public space, identity, and globalization must be contested. From these findings researchers can then analyze Cairo through not only its physical landscapes, but also its metaphysical features – such as the soundscape.Keywords: music, space, globalization, Cairo
Procedia PDF Downloads 1141085 Studying Relationship between Local Geometry of Decision Boundary with Network Complexity for Robustness Analysis with Adversarial Perturbations
Authors: Tushar K. Routh
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If inputs are engineered in certain manners, they can influence deep neural networks’ (DNN) performances by facilitating misclassifications, a phenomenon well-known as adversarial attacks that question networks’ vulnerability. Recent studies have unfolded the relationship between vulnerability of such networks with their complexity. In this paper, the distinctive influence of additional convolutional layers at the decision boundaries of several DNN architectures was investigated. Here, to engineer inputs from widely known image datasets like MNIST, Fashion MNIST, and Cifar 10, we have exercised One Step Spectral Attack (OSSA) and Fast Gradient Method (FGM) techniques. The aftermaths of adding layers to the robustness of the architectures have been analyzed. For reasoning, separation width from linear class partitions and local geometry (curvature) near the decision boundary have been examined. The result reveals that model complexity has significant roles in adjusting relative distances from margins, as well as the local features of decision boundaries, which impact robustness.Keywords: DNN robustness, decision boundary, local curvature, network complexity
Procedia PDF Downloads 761084 Experimental Approach for Determining Hemi-Anechoic Characteristics of Engineering Acoustical Test Chambers
Authors: Santiago Montoya-Ospina, Raúl E. Jiménez-Mejía, Rosa Elvira Correa Gutiérrez
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An experimental methodology is proposed for determining hemi-anechoic characteristics of an engineering acoustic room built at the facilities of Universidad Nacional de Colombia to evaluate the free-field conditions inside the chamber. Experimental results were compared with theoretical ones in both, the source and the sound propagation inside the chamber. Acoustic source was modeled by using monopole radiation pattern from punctual sources and the image method was considered for dealing with the reflective plane of the room, that means, the floor without insulation. Finite-difference time-domain (FDTD) method was implemented to calculate the sound pressure value at every spatial point of the chamber. Comparison between theoretical and experimental data yields to minimum error, giving satisfactory results for the hemi-anechoic characterization of the chamber.Keywords: acoustic impedance, finite-difference time-domain, hemi-anechoic characterization
Procedia PDF Downloads 1631083 Graphene Metamaterials Supported Tunable Terahertz Fano Resonance
Authors: Xiaoyong He
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The manipulation of THz waves is still a challenging task due to lack of natural materials interacted with it strongly. Designed by tailoring the characters of unit cells (meta-molecules), the advance of metamaterials (MMs) may solve this problem. However, because of Ohmic and radiation losses, the performance of MMs devices is subjected to the dissipation and low quality factor (Q-factor). This dilemma may be circumvented by Fano resonance, which arises from the destructive interference between a bright continuum mode and dark discrete mode (or a narrow resonance). Different from symmetric Lorentz spectral curve, Fano resonance indicates a distinct asymmetric line-shape, ultrahigh quality factor, steep variations in spectrum curves. Fano resonance is usually realized through symmetry breaking. However, if concentric double rings (DR) are placed closely to each other, the near-field coupling between them gives rise to two hybridized modes (bright and narrowband dark modes) because of the local asymmetry, resulting into the characteristic Fano line shape. Furthermore, from the practical viewpoint, it is highly desirable requirement that to achieve the modulation of Fano spectral curves conveniently, which is an important and interesting research topics. For current Fano systems, the tunable spectral curves can be realized by adjusting the geometrical structural parameters or magnetic fields biased the ferrite-based structure. But due to limited dispersion properties of active materials, it is still a tough work to tailor Fano resonance conveniently with the fixed structural parameters. With the favorable properties of extreme confinement and high tunability, graphene is a strong candidate to achieve this goal. The DR-structure possesses the excitation of so-called “trapped modes,” with the merits of simple structure and high quality of resonances in thin structures. By depositing graphene circular DR on the SiO2/Si/ polymer substrate, the tunable Fano resonance has been theoretically investigated in the terahertz regime, including the effects of graphene Fermi level, structural parameters and operation frequency. The results manifest that the obvious Fano peak can be efficiently modulated because of the strong coupling between incident waves and graphene ribbons. As Fermi level increases, the peak amplitude of Fano curve increases, and the resonant peak position shifts to high frequency. The amplitude modulation depth of Fano curves is about 30% if Fermi level changes in the scope of 0.1-1.0 eV. The optimum gap distance between DR is about 8-12 μm, where the value of figure of merit shows a peak. As the graphene ribbon width increases, the Fano spectral curves become broad, and the resonant peak denotes blue shift. The results are very helpful to develop novel graphene plasmonic devices, e.g. sensors and modulators.Keywords: graphene, metamaterials, terahertz, tunable
Procedia PDF Downloads 3451082 Distangling Biological Noise in Cellular Images with a Focus on Explainability
Authors: Manik Sharma, Ganapathy Krishnamurthi
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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.Keywords: cellular images, genetic perturbations, deep-learning, explainability
Procedia PDF Downloads 1131081 Delusional Parasitosis (A Rare Primary Psychiatric Diagnosis)
Authors: Jaspinder Kaur, Jatinder Pal Singh
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Introduction- Delusional parasitosis is a rare psychotic illness characterized by a fixed belief of manifesting a parasite in a body when in reality, it was not. Also known as Ekbom syndrome or delusional infestations, or acarophobia. Although the patient has no primary skin pathology, but all skin findings were secondary to skin manipulation by the patient itself, which is why up to 90% of patients first seek consultation from a dermatologist. Most commonly, it was seen in older people with female to male ratio is 2:1. For treatment, the patient first need to be investigated to rule all other possible causes, as Delusional parasitosis can be caused by Vitamin B12 deficiency, pellagra, hepatic and renal disease, diabetes mellitus, multiple sclerosis, and leprosy. When all possible causes ruled out, psychiatric referral to be done. Rule out other psychiatric comorbidities, and treatment should be done accordingly. Patient with delusional parasitosis responds well to second generation antipsychotics and need to continuous medication over years, and relapse is likely if treatment is stopped. Case Presentation- A 79-year-old female, belonging to lower socio-economic status, presented with complaints of itching sensation with erythematous patches over the scalp and multiple scratch excoriations lesion over the scalp, face and neck from the past 7-8 months. She had a feeling of small insect crawling under her skin and scalp area. To reduce the itching and kill the insect, she would scratch and squeeze her skin repeatedly. When the family tried to give her explanation that there was no insect in her body, she would not get convinced, rather got angry and abuse family members for not believing her. Gradually, her sleep would remain disturbed, she would be seen awake at night, seen to be scratching her skin, pull her scalp hair, even squeeze out her healed lesions. She collected her skin debris, scalp hairs and look out for insect. Because of her continuous illness, the patient started to remain sad and had crying spells. Her appetite decreased. She became socially isolated and stopped doing her activities of daily living. Family member’s first consulted dermatologist, investigated thoroughly with routine investigations, autoimmune and malignancy workup. As all investigations were normal, following which patient was referred for psychiatric evaluation. The patient was started on Tablet Olanzapine 2.5 mg, gradually increased to 7.5 mg. Over 1 month, there was reduction in itching, skin pricking. Lesions were gradually healed, and the patient continued to take other dermatological medications and ointment and was in regular follow up with psychiatric liaison from past 2 months with 70-80 % improvement in her symptoms. Conclusion- Delusional parasitosis is a psychiatric disorder of insidious onset, seen commonly in middle and old age people. Both psychiatric and dermatology consultation liaison will help the patient for an early diagnosis and adequate treatment. If a primary psychiatric diagnosis, the patient respond well to second generation antipsychotics but always require a further evaluation and treatment management if it is secondary to some physical or other psychiatric comorbidity.Keywords: delusional parasitosis, delusional infestations, rare, primary psychiatric diagnosis, antipsychotic agents
Procedia PDF Downloads 831080 Hierarchical Piecewise Linear Representation of Time Series Data
Authors: Vineetha Bettaiah, Heggere S. Ranganath
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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation
Procedia PDF Downloads 2761079 Practical Guidelines for Utilizing WipFrag Software to Assess Oversize Blast Material Using Both Orthomosaic and Digital Images
Authors: Blessing Olamide Taiwo, Andrew Palangio, Chirag Savaliya, Jenil Patel
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Oversized material resulting from blasting presents a notable drawback in the transportation of run-off-mine material due to increased expenses associated with handling, decreased efficiency in loading, and greater wear on digging equipment. Its irregular size and weight demand additional resources and time for secondary breakage, impacting overall productivity and profitability. This paper addresses the limitations of interpreting image analysis software results and applying them to the assessment of blast-generated oversized materials. This comprehensive guide utilizes both ortho mosaic and digital photos to provide critical approaches for optimizing fragmentation analysis and improving decision-making in mining operations. It briefly covers post-blast assessment, blast block heat map interpretation, and material loading decision-making recommendations.Keywords: blast result assessment, WipFrag, oversize identification, orthomosaic images, production optimization
Procedia PDF Downloads 411078 Towards Integrating Statistical Color Features for Human Skin Detection
Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani
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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.Keywords: color space, neural network, random forest, skin detection, statistical feature
Procedia PDF Downloads 4621077 Effects of Upstream Wall Roughness on Separated Turbulent Flow over a Forward Facing Step in an Open Channel
Authors: S. M. Rifat, André L. Marchildon, Mark F. Tachie
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The effect of upstream surface roughness over a smooth forward facing step in an open channel was investigated using a particle image velocimetry technique. Three different upstream surface topographies consisting of hydraulically smooth wall, sandpaper 36 grit and sand grains were examined. Besides the wall roughness conditions, all other upstream flow characteristics were kept constant. It was also observed that upstream roughness decreased the approach velocity by 2% and 10% but increased the turbulence intensity by 14% and 35% at the wall-normal distance corresponding to the top plane of the step compared to smooth upstream. The results showed that roughness decreased the reattachment lengths by 14% and 30% compared to smooth upstream. Although the magnitudes of maximum positive and negative Reynolds shear stress in separated and reattached region were 0.02Ue for all the cases, the physical size of both the maximum and minimum contour levels were decreased by increasing upstream roughness.Keywords: forward facing step, open channel, separated and reattached turbulent flows, wall roughness
Procedia PDF Downloads 3551076 Multilabel Classification with Neural Network Ensemble Method
Authors: Sezin Ekşioğlu
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Multilabel classification has a huge importance for several applications, it is also a challenging research topic. It is a kind of supervised learning that contains binary targets. The distance between multilabel and binary classification is having more than one class in multilabel classification problems. Features can belong to one class or many classes. There exists a wide range of applications for multi label prediction such as image labeling, text categorization, gene functionality. Even though features are classified in many classes, they may not always be properly classified. There are many ensemble methods for the classification. However, most of the researchers have been concerned about better multilabel methods. Especially little ones focus on both efficiency of classifiers and pairwise relationships at the same time in order to implement better multilabel classification. In this paper, we worked on modified ensemble methods by getting benefit from k-Nearest Neighbors and neural network structure to address issues within a beneficial way and to get better impacts from the multilabel classification. Publicly available datasets (yeast, emotion, scene and birds) are performed to demonstrate the developed algorithm efficiency and the technique is measured by accuracy, F1 score and hamming loss metrics. Our algorithm boosts benchmarks for each datasets with different metrics.Keywords: multilabel, classification, neural network, KNN
Procedia PDF Downloads 1551075 Consumers’ Attitude towards Marketing Recreational Marijuana
Authors: Nizar Souiden, Riadh Ladhari
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Like tobacco and alcohol, recreational marijuana falls under the umbrella of ‘sin’ industries’. Notwithstanding this general negative image surrounding marijuana use, some scholars argue that most of the widely believed claims made about recreational marijuana users are irrelevant and that marijuana use can even improve individuals’ decision-making. This study intends to shed light on this particular product category (i.e., marijuana) often overlooked or portrayed as taboo from a business view. More specifically, it investigates whether legalizing the consumption of recreational marijuana would be perceived as ethical and whether companies/organizations involved in the commercialization of this particular product would be held socially responsible. Based on primary data collected in Canada, this study aims to answer the following questions: 1) What moral thoughts do individuals hold with regard to the consumption of recreational marijuana? 2) How do these moral thoughts determine consumers’ attitude toward the consumption of recreational marijuana? Regardless of the legalization of recreational marijuana in some countries such as Canada, probing people’s opinions, and investigating their attitudes toward the consumption of recreational marijuana is of important interest to different stakeholders such as consumers, public organizations, private businesses, and trade associations.Keywords: recreational marijuana, moral thoughts, ethics, attitude
Procedia PDF Downloads 1471074 Efficient Motion Estimation by Fast Three Step Search Algorithm
Authors: S. M. Kulkarni, D. S. Bormane, S. L. Nalbalwar
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The rapid development in the technology have dramatic impact on the medical health care field. Medical data base obtained with latest machines like CT Machine, MRI scanner requires large amount of memory storage and also it requires large bandwidth for transmission of data in telemedicine applications. Thus, there is need for video compression. As the database of medical images contain number of frames (slices), hence while coding of these images there is need of motion estimation. Motion estimation finds out movement of objects in an image sequence and gets motion vectors which represents estimated motion of object in the frame. In order to reduce temporal redundancy between successive frames of video sequence, motion compensation is preformed. In this paper three step search (TSS) block matching algorithm is implemented on different types of video sequences. It is shown that three step search algorithm produces better quality performance and less computational time compared with exhaustive full search algorithm.Keywords: block matching, exhaustive search motion estimation, three step search, video compression
Procedia PDF Downloads 491