Search results for: MR image of brain

Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid, Kashaf Gul

Abstract:

Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.

Keywords: landcover classification, artificial neural network, remote sensing, SPOT 5

Procedia PDF Downloads 534

Authors: Ibraheem Husain, Abul Kalam Najmi, Karishma Chester

Abstract:

First-in-human (FIH) studies are a critical step in clinical development of any molecule that has shown therapeutic promise in preclinical evaluations, since preclinical research and safety studies into clinical development is a crucial step for successful development of monoclonal antibodies for guidance in pharmaceutical industry for the treatment of human diseases. Therefore, comparison between USFDA and nine pharmacologically guided approaches (PGA) (simple allometry, maximum life span potential, brain weight, rule of exponent (ROE), two species methods and one species methods) were made to determine maximum recommended starting dose (MRSD) for first in human clinical trials using four drugs namely Denosumab, Bevacizumab, Anakinra and Omalizumab. In our study, the predicted pharmacokinetic (pk) parameters and the estimated first-in-human dose of antibodies were compared with the observed human values. The study indicated that the clearance and volume of distribution of antibodies can be predicted with reasonable accuracy in human and a good estimate of first human dose can be obtained from the predicted human clearance and volume of distribution. A pictorial method evaluation chart was also developed based on fold errors for simultaneous evaluation of various methods.

Keywords: clinical pharmacology (CPH), clinical research (CRE), clinical trials (CTR), maximum recommended starting dose (MRSD), clearance and volume of distribution

Procedia PDF Downloads 368

Authors: Oğuzhan Urhan

Abstract:

In this paper, an improved motion estimation (ME) approach based on weighted constrained one-bit transform is proposed for block-based ME employed in video encoders. Binary ME approaches utilize low bit-depth representation of the original image frames with a Boolean exclusive-OR based hardware efficient matching criterion to decrease computational burden of the ME stage. Weighted constrained one-bit transform (WC‑1BT) based approach improves the performance of conventional C-1BT based ME employing 2-bit depth constraint mask instead of a 1-bit depth mask. In this work, the range of constraint mask is further extended to increase ME performance of WC-1BT approach. Experiments reveal that the proposed method provides better ME accuracy compared existing similar ME methods in the literature.

Keywords: fast motion estimation; low-complexity motion estimation, video coding

Procedia PDF Downloads 311

Authors: Sanjeeb Sutradhar, Archita Patnaik

Abstract:

Histidine is one of the twenty-two naturally occurring essential amino acids exhibiting two conformations, L-histidine and D-histidine. D-Histidine is biologically inert, while L-histidine is bioactive because of its conversion to neurotransmitter or neuromodulator histamine in both brain as well as central nervous system. The deficiency of L-histidine causes serious diseases like Parkinson’s disease, epilepsy and the failure of normal erythropoiesis development. Gold nanocomposites are attractive materials due to their excellent biocompatibility and are easy to adsorb on the electrode surface. In the present investigation, hydrophobic fullerene-C60 was functionalized with homocysteine via nucleophilic addition reaction to make it hydrophilic and to successively make the nanocomposite with in-situ prepared gold nanoparticles with ascorbic acid as reducing agent. The electronic structure calculations of the AuNPs@Hcys-C60 nanocomposite showed a drastic reduction of HOMO-LUMO gap compared to the corresponding molecules of interest, indicating enhanced electron transportability to the electrode surface. In addition, the electrostatic potential map of the nanocomposite showed the charge was distributed over either end of the nanocomposite, evidencing faster direct electron transfer from nanocomposite to the electrode surface. This nanocomposite showed catalytic activity; the nanocomposite modified glassy carbon electrode showed a tenfold higher kₑt, the electron transfer rate constant than the bare glassy carbon electrode. Significant improvement in its sensing behavior by square wave voltammetry was noted.

Keywords: fullerene-C60, gold nanocomposites, L-Histidine, square wave voltammetry

Procedia PDF Downloads 245

Authors: Nareenad Panbun

Abstract:

The objective is to study the knowledge utilization from the participants of the announcer training program by National Broadcasting and Telecommunications Commission (NBTC). This study is a quantitative research based on surveys and self-answering questionnaires. The population of this study is 100 participants randomly chosen by non-probability sampling method. The results have shown that most of the participants were satisfied with the topics of general knowledge about the broadcasting and television business for 37 people representing 37%, followed by the topics of broadcasting techniques. The legal issues, consumer rights, television business ethics, and credibility of the media are, in addition to the media's role and responsibilities in society, the use of language for successful communication. Therefore, the communication language skills are the most important for all of the trainees and will also build up the image of the broadcasting center.

Keywords: announcer training program, participant, requirements announced, theory of utilization

Procedia PDF Downloads 218

Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

Abstract:

Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

Procedia PDF Downloads 128

Authors: Ayalew Yimam Ali

Abstract:

The T-shaped microchannel is used to mix both miscible or immiscible fluids with different viscosities. However, mixing at the entrance of the T-junction microchannel can be difficult mixing phenomena due to micro-scale laminar flow aspects with the two miscible high-viscosity water-glycerol fluids. One of the most promising methods to improve mixing performance and diffusion mass transfer in laminar flow phenomena is acoustic streaming (AS), which is a time-averaged, second-order steady streaming that can produce rolling motion in the microchannel by oscillating a low-frequency range acoustic transducer and inducing an acoustic wave in the flow field. The newly developed 3D trapezoidal, triangular structure spine used in this study was created using sophisticated CNC machine cutting tools used to create microchannel mold with a 3D trapezoidal triangular structure spine alone the T-junction longitudinal mixing region. In order to create the molds for the 3D trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm trapezoidal, triangular sharp edge tip depth from PMMA glass (Polymethylmethacrylate) with advanced CNC machine and the channel manufactured using PDMS (Polydimethylsiloxane) which is grown up longitudinally on the top surface of the Y-junction microchannel using soft lithography nanofabrication strategies. Flow visualization of 3D rolling steady acoustic streaming and mixing enhancement with high-viscosity miscible fluids with different trapezoidal, triangular structure longitudinal length, channel width, high volume flow rate, oscillation frequency, and amplitude using micro-particle image velocimetry (μPIV) techniques were used to study the 3D acoustic streaming flow patterns and mixing enhancement. The streaming velocity fields and vorticity flow fields show 16 times more high vorticity maps than in the absence of acoustic streaming, and mixing performance has been evaluated at various amplitudes, flow rates, and frequencies using the grayscale value of pixel intensity with MATLAB software. Mixing experiments were performed using fluorescent green dye solution with de-ionized water in one inlet side of the channel, and the de-ionized water-glycerol mixture on the other inlet side of the T-channel and degree of mixing was found to have greatly improved from 67.42% without acoustic streaming to 0.96.83% with acoustic streaming. The results show that the creation of a new 3D steady streaming rolling motion with a high volume flowrate around the entrance was enhanced by the formation of a new, three-dimensional, intense streaming rolling motion with a high-volume flowrate around the entrance junction mixing zone with the two miscible high-viscous fluids which are influenced by laminar flow fluid transport phenomena.

Keywords: micro fabrication, 3d acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement.

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Authors: Arthur C. Tsai, Chii-Shyang Kuo, Vincent S. C. Chien, Michelle Liou, Philip E. Cheng

Abstract:

Meditation enhances mental abilities and it is an antidote to anxiety. However, very little is known about brain mechanisms and cortico-subcortical interactions underlying meditation-induced anxiety relief. In this study, the changes of phase-amplitude coupling (PAC) in which the amplitude of the beta frequency band were modulated in phase with delta rhythm were investigated after eight-week of meditation training. The study hypothesized that through a concentrate but relaxed mental training the delta-beta coupling in the frontal regions is attenuated. The delta-beta coupling analysis was applied to within and between maximally-independent component sources returned from the extended infomax independent components analysis (ICA) algorithm on the continuous EEG data during mediation. A unique meditative concentration task through relaxing body and mind was used with a constant level of moderate mental effort, so as to approach an ‘emptiness’ meditative state. A pre-test/post-test control group design was used in this study. To evaluate cross-frequency phase-amplitude coupling of component sources, the modulation index (MI) with statistics to calculate circular phase statistics were estimated. Our findings reveal that a significant delta-beta decoupling was observed in a set of frontal regions bilaterally. In addition, beta frequency band of prefrontal component were amplitude modulated in phase with the delta rhythm of medial frontal component.

Keywords: phase-amplitude coupling, ICA, meditation, EEG

Procedia PDF Downloads 419

Authors: Eman S. Soliman, Sana Hawamdeh, Najmus S. Mahfooz

Abstract:

Purpose: The purpose of this paper was to examine various components of applied emotional intelligence as demonstrated in the leadership style of Khadijah Bint Khuwaylid in pre and post-Islamic society. Methodology: The research used a qualitative research method, specifically historical and ethnographic techniques. Data collection included both primary and secondary sources. Data from sources were analyzed to document the use of emotional intelligent leadership behaviors throughout Khadijah Bint Khuwaylid leadership experience from 596 A.D. to 621 A.D. Findings: Demonstration of four cornerstones of emotional intelligence which are self-awareness, self-management, social awareness and relationship management. Apply them on khadejah Bint Khuwaylid leadership style reveal that she possess main behavioral competences in the form of emotionally self-aware, self-.confidence, adaptability, empathy and influence. Conclusions: Khadijah Bint Khuwaylid serves as a historical model of effective leadership that included the use of emotional intelligence in her leadership behavior. The inclusion of the effective portion of the brain created a successful leadership style that can be learned by present day and future leadership. The recommendations for future leaders are to include the use of emotionally self-aware and self-confidence, adaptability, empathy and influence as components of leadership. This will then demonstrate in a leadership a basic knowledge and understanding of feelings, the keenness to be emotionally open with others, the ability to prototype beliefs and values, and the use of emotions in future communications, vision and progress.

Keywords: emotional intelligence, leadership, Khadijah Bint Khuwaylid, women

Procedia PDF Downloads 270

Authors: Jamuna Rajeswaran

Abstract:

In the past two decades, with a population of more than a billion. India is passing through a major socio-demographic and epidemiological transition with consequent changes in health scenario. TBI constitute significant burden on health care resources in India The impact on a person and family can be devastating. Patients with TBI experience persistent cognitive deficits, emotional changes, which contribute to the disruption of life activities. The recovery of TBI would be maximized by appropriate rehabilitation. Neurofeedback is an emerging neuroscience-based clinical application. Sixty patients were recruited for this study after obtaining informed consent. Rivermead Head Injury Follow-up Questionnaire, Rivermead Post Concussion Symptoms Questionnaire and Visual Analog Scale were used to assess the behavioral and symptomotolgy associated with post TBI. Neuropsychological assessment was carried out using NIMHANS neuropsychological battery 2004. The Intervention group received neurofeedback training and the waitlist group did not receive any treatment during this phase. Patients were allocated to intervention and waitlist group at random. There were 30 patients in each group. Patients were given 20 sessions of NFT Patients were trained on the O1 and O2 channels for alpha theta training. Each session was of 40 minutes duration with 5-6 sessions per week. The post-training assessment was carried out for the intervention group after 20 sessions of NFT. The waitlist group underwent assessment after one month. Results showed neurofeedback training is effective in ameliorating deficits in cognitive functions and quality of life in patients with TBI. Improvements were corroborated by the clinical interview with patients and significant others post NFT.

Keywords: assessment, rehabilitation, cognition, EEG neurofeedback

Procedia PDF Downloads 258

Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

Abstract:

Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

Procedia PDF Downloads 223

Authors: Ilzira A. Minigalieva, Tatiana V. Bushueva, Eleonore Frohlich, Vladimir Panov, Ekaterina Shishkina, Boris A. Katsnelson

Abstract:

Background: The overwhelming majority of the experimental studies in the field of metal nanotoxicology have been performed on cultures of established cell lines, with very few researchers focusing on animal experiments, while a juxtaposition of conclusions inferred from these two types of research is blatantly lacking. The least studied aspect of this problem relates to characterizing and predicting the combined toxicity of metallic nanoparticles. Methods: Comparative and combined toxic effects of purposefully prepared spherical NiO and Mn₃O₄ nanoparticles (mean diameters 16.7 ± 8.2 nm and 18.4 ± 5.4 nm respectively) were estimated on cultures of human cell lines: MRC-5 fibroblasts, THP-1 monocytes, SY-SY5Y neuroblastoma cells, as well as on the latter two lines differentiated to macrophages and neurons, respectively. The combined cytotoxicity was mathematically modeled using the response surface methodology. Results: The comparative assessment of the studied NPs unspecific toxicity previously obtained in vivo was satisfactorily reproduced by the present in vitro tests. However, with respect to manganese-specific brain damage which had been demonstrated by us in animal experiment with the same NPs, the testing on neuronall cell culture showed only a certain enhancing effect of Mn₃O₄-NPs on the toxic action of NiO-NPs, while the role of the latter prevailed. Conclusion: From the point of view of the preventive toxicology, the experimental modeling of metallic NPs combined toxicity on cell cultures can give non-reliable predictions of the in vivo action’s effects.

Keywords: manganese oxide, nickel oxide, nanoparticles, in vitro toxicity

Procedia PDF Downloads 289

Authors: Revytia Tanera

Abstract:

This research is a pilot study to examine the rise of selfie trend in dealing with individual self representation and identity building in social media. The symbolic interactionism theory is used as the concept of the desired self image, and Cooley’s looking glass-self concept is used to analyze the mechanical reflection of ourselves; how do people perform their “digital self” in social media. In-depth interviews were conducted in the study with a non-random sample who owns a smartphone with a front camera feature and are active in social media. This research is trying to find out whether the selfie trend brings any influence on identity building on each individual. Through analysis of interview results, it can be concluded that people take selfie photos in order to express themselves and to boost their confidence. This study suggests a follow up and more in depth analysis on identity and self representation from various age groups.

Keywords: self representation, selfie, social media, symbolic interaction, looking glass-self

Procedia PDF Downloads 294

Authors: Lam Hong Lan

Abstract:

The textile industry is said to be the second-largest polluter, responsible for 92 million tonnes of waste annually. There is an urgent need to practice the circular economy to increase the use and reuse around the world. By its nature, the pre-owned fashion business is considered part of the circular economy as it helps to eliminate waste and circulate products. Second-hand clothes and accessories used to be associated with a ‘cheap image’ that carried ‘old energy’ in Vietnam. This perception has been shifted, especially amongst the younger generation. Vietnamese consumer is spending more on products and services that increase self-esteem. The same consumer is moving away from a collectivist social identity towards a ‘me, not we’ outlook as they look for a way to express their individual identity. And pre-owned fashion is one of their solutions as it values money, can create a unique personal style for the wearer and links with sustainability. The design of this study is based on the second-hand shopping motivation theory. A semi-structured online survey with 100 consumers from one pre-owned clothing community and one pre-owned e-commerce site in Vietnam. The findings show that in contrast with Vietnamese older consumers (55+yo) who, in the previous study, generally associated pre-owned fashion with ‘low-cost’, ‘cheap image’ that carried ‘old energy’, young customers (20-30 yo) were actively promoted their pre-owned fashion items to the public via outlet’s social platforms and their social media. This cultural shift comes from the impact of global and local discourse around sustainable fashion and the growth of digital platforms in the pre-owned fashion business in the last five years, which has generally supported wider interest in pre-owned fashion in Vietnam. It can be summarised in three areas: (1) global and local celebrity influencers. A number of celebrities have been photographed wearing vintage items in music videos, photoshoots or at red carpet events. (2) E-commerce and intermediaries. International e-commerce sites – e.g., Vinted, TheRealReal – and/or local apps – e.g., Re.Loved – can influence attitudes and behaviors towards pre-owned consumption. (3) Eco-awareness. The increased online coverage of climate change and environmental pollution has encouraged customers to adopt a more eco-friendly approach to their wardrobes. While sustainable biomaterials and designs are still navigating their way into sustainability, sustainable consumerism via pre-owned fashion seems to be an immediate solution to lengthen the clothes lifecycle. This study has found that young consumers are primarily seeking value for money and/or a unique personal style from pre-owned/vintage fashion while using these purchases to promote their own “eco-awareness” via their social media networks. This is a good indication for fashion designers to keep in mind in their design process and for fashion enterprises in their business model’s choice to not overproduce fashion items.

Keywords: cultural shift, pre-owned fashion, sustainable consumption, sustainable fashion.

Procedia PDF Downloads 77

Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

Abstract:

Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

Procedia PDF Downloads 154

Authors: Nidhi Chadha, A. K. Tiwari, Marilyn D. Milton, Anil K. Mishra

Abstract:

Translocator protein (18 kDa) TSPO is highly expressed during microglia activation in neuroinflammation. Although a number of PET ligands have been developed for the visualization of activated microglia, one of the advantageous approaches is to develop potential optical imaging (OI) probe. Our study involves computational screening, synthesis and evaluation of TSPO ligand through various imaging modalities namely PET/SPECT/Optical. The initial computational screening involves pharmacophore modeling from the library designing having oxo-benzooxazol-3-yl-N-phenyl-acetamide groups and synthesis for visualization of efficacy of these compounds as multimodal imaging probes. Structure modeling of monomer, Ala147Thr mutated, parallel and anti-parallel TSPO dimers was performed and docking analysis was performed for distinct binding sites. Computational analysis showed pattern of variable binding profile of known diagnostic ligands and NBMP via interactions with conserved residues along with TSPO’s natural polymorphism of Ala147→Thr, which showed alteration in the binding affinity due to considerable changes in tertiary structure. Preliminary in vitro binding studies shows binding affinity in the range of 1-5 nm and selectivity was also certified by blocking studies. In summary, this skeleton was found to be potential probe for TSPO imaging due to ease in synthesis, appropriate lipophilicity and reach to specific region of brain.

Keywords: TSPO, molecular modeling, imaging, docking

Procedia PDF Downloads 452

Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

Abstract:

In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

Procedia PDF Downloads 301

Authors: Rokeshia Renné Ashley

Abstract:

The purpose of this study is to understand the perception of historical figure Saartjie 'Sara/Sarah' Baartman from a cross cultural perspective of black women in the United States and black women in South Africa. Semi-structured interviews (n = 30) uncover that many women in both countries did not have an accurate representation, recollection, or have been exposed to the story of Baartman. Nonetheless, those who were familiar with Baartman’s story, those participants compared her to modern examples of black women who are showcased in a contemporary familiarity. The women are described by participants as women who reveal their bodies in a sexualized manner and have the curves that are similar to Baartman’s historic figure. This comparison emphasized a connection to popular images of black women who represent the curvaceous ideal. Findings contribute to social comparison theory by providing a lens for examining black women’s body image.

Keywords: black women, body modification, media, South Africa

Procedia PDF Downloads 310

Authors: Yasaman Mohammadi

Abstract:

Executive functions are a critical component of goal-directed behavior, encompassing a diverse set of cognitive processes such as working memory, cognitive flexibility, and inhibitory control. These functions are known to decline with age, but the precise mechanisms underlying this decline remain unclear. This paper provides an in-depth review of recent research investigating age-related changes in executive functions, drawing on insights from neuroimaging, genetics, and cognitive neuroscience. Through an interdisciplinary approach, this paper offers a nuanced understanding of the complex interplay between neural mechanisms, genetic factors, and cognitive processes that contribute to executive function decline in aging. Here, we investigate how different neuroimaging methods, like functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), have helped scientists better understand the brain bases for age-related declines in executive function. Additionally, we discuss the role of genetic factors in mediating individual differences in executive functions across the lifespan, as well as the potential for cognitive interventions to mitigate age-related decline. Overall, this paper presents a comprehensive and integrative view of the current state of knowledge regarding age-related changes in executive functions. It underscores the need for continued interdisciplinary research to fully understand the complex and dynamic nature of executive function decline in aging, with the ultimate goal of developing effective interventions to promote healthy cognitive aging.

Keywords: executive functions, aging, neuroimaging, cognitive neuroscience, working memory, cognitive training

Procedia PDF Downloads 60

Authors: Mahdi Bazarganigilani

Abstract:

Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

Procedia PDF Downloads 202

Authors: Shiyin He, Zheng Huang

Abstract:

In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

Procedia PDF Downloads 178

Authors: Ayalew Yimam Ali

Abstract:

The Y-shaped microchannel is used to mix both miscible or immiscible fluids with different viscosities. However, mixing at the entrance of the Y-junction microchannel can be a difficult mixing phenomena due to micro-scale laminar flow aspects with the two miscible high-viscosity water-glycerol fluids. One of the most promising methods to improve mixing performance and diffusion mass transfer in laminar flow phenomena is acoustic streaming (AS), which is a time-averaged, second-order steady streaming that can produce rolling motion in the microchannel by oscillating a low-frequency range acoustic transducer and inducing an acoustic wave in the flow field. The developed 3D trapezoidal, triangular structure spine used in this study was created using sophisticated CNC machine cutting tools used to create microchannel mold with a 3D trapezoidal triangular structure spine alone the Y-junction longitudinal mixing region. In order to create the molds for the 3D trapezoidal structure with the 3D sharp edge tip angles of 30° and 0.3mm trapezoidal triangular sharp edge tip depth from PMMA glass (Polymethylmethacrylate) with advanced CNC machine and the channel manufactured using PDMS (Polydimethylsiloxane) which is grown up longitudinally on top surface of the Y-junction microchannel using soft lithography nanofabrication strategies. Flow visualization of 3D rolling steady acoustic streaming and mixing enhancement with high-viscosity miscible fluids with different trapezoidal, triangular structure longitudinal length, channel width, high volume flow rate, oscillation frequency, and amplitude using micro-particle image velocimetry (μPIV) techniques were used to study the 3D acoustic streaming flow patterns and mixing enhancement. The streaming velocity fields and vorticity flow fields show 16 times more high vorticity maps than in the absence of acoustic streaming, and mixing performance has been evaluated at various amplitudes, flow rates, and frequencies using the grayscale value of pixel intensity with MATLAB software. Mixing experiments were performed using fluorescent green dye solution with de-ionized water in one inlet side of the channel, and the de-ionized water-glycerol mixture on the other inlet side of the Y-channel and degree of mixing was found to have greatly improved from 67.42% without acoustic streaming to 0.96.83% with acoustic streaming. The results show that the creation of a new 3D steady streaming rolling motion with a high volume flowrate around the entrance was enhanced by the formation of a new, three-dimensional, intense streaming rolling motion with a high-volume flowrate around the entrance junction mixing zone with the two miscible high-viscous fluids which are influenced by laminar flow fluid transport phenomena.

Keywords: micro fabrication, 3d acoustic streaming flow visualization, micro-particle image velocimetry, mixing enhancement

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Authors: Sello Mokwena, Monyepao Thabang

Abstract:

In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis on benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: camera network, convolutional neural network topology, person tracking, person re-identification, siamese

Procedia PDF Downloads 66

Authors: Shrikaant Kulkarni, Akshata Naik Nimbalkar

Abstract:

In this worki a method protocol has been developed for the synthesis of innovative Co3O4 material by using a method of chemical synthesis followed by calcination. The effect of calcination temperature on the morphology, structure and catalytic performance on material in question is investigated by using characterization tools like scanning electron microscopy (SEM), X-ray diffraction (XRD) spectroscopy and electrochemical techniques. The SEM images reveal that the morphology of the Co3O4 material undergoes a change from the rod to a beadlike shape on calcination at temperature of 700 °C. The XRD image shows that although the morphology of synthesized Co3O4 material exhibits a cubic phase but it differs in crystallinity depending upon morphology. Similarly spherical beadlike Co3O4 material has exhibited better activity than its rodlike counterpart which is reflected from electrochemical findings. Further, its performance in terms of bifunctional nature and hlods a lot much of promise as a excellent electrode material in the next generation batteries and fuel cells.

Keywords: bifunctional, next generation material, Co3O4, XRD

Procedia PDF Downloads 370

Authors: Asil Zureigat, Ayat Odat

Abstract:

Analyzing the old and bringing in the new is an ever ongoing process in driving innovations in architecture. This paper looks at the excessive use of stone in apartment buildings in Amman and speculates on the existing possibilities of changing the cladding material. By looking at architectural exceptions present in Amman the paper seeks to make the exception, the rule by adding new materials to the architectural library of Amman and in turn, project a series of possible new identities to the existing stone scape. Through distributing a survey, conducting a photographic study on exceptional buildings and shedding light on the historical narrative of stone, the paper highlights the ways in which new finishing materials such as plaster, paint and stone variations could be introduced in an attempt to project a new architectural identity to Amman.

Keywords: architectural city identity, cladding materials, façade architecture, image of the city

Procedia PDF Downloads 218

Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

Abstract:

The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Josef Uher, Jana Boháčová, Richard Kadeřábek

Abstract:

In this paper, we present a multi-robot imaging and irradiation research platform referred to as Irradion, with full capabilities of portable arbitrary path computed tomography (CT). Irradion is an imaging and irradiation unit entirely based on robotic arms for research on cancer treatment with ion beams on small animals (mice or rats). The platform comprises two subsystems that combine several imaging modalities, such as 2D X-ray imaging, CT, and particle tracking, with precise positioning of a small animal for imaging and irradiation. Computed Tomography: The CT subsystem of the Irradion platform is equipped with two 6-joint robotic arms that position a photon counting detector and an X-ray tube independently and freely around the scanned specimen and allow image acquisition utilizing computed tomography. Irradiation measures nearly all conventional 2D and 3D trajectories of X-ray imaging with precisely calibrated and repeatable geometrical accuracy leading to a spatial resolution of up to 50 µm. In addition, the photon counting detectors allow X-ray photon energy discrimination, which can suppress scattered radiation, thus improving image contrast. It can also measure absorption spectra and recognize different materials (tissue) types. X-ray video recording and real-time imaging options can be applied for studies of dynamic processes, including in vivo specimens. Moreover, Irradion opens the door to exploring new 2D and 3D X-ray imaging approaches. We demonstrate in this publication various novel scan trajectories and their benefits. Proton Imaging and Particle Tracking: The Irradion platform allows combining several imaging modules with any required number of robots. The proton tracking module comprises another two robots, each holding particle tracking detectors with position, energy, and time-sensitive sensors Timepix3. Timepix3 detectors can track particles entering and exiting the specimen and allow accurate guiding of photon/ion beams for irradiation. In addition, quantifying the energy losses before and after the specimen brings essential information for precise irradiation planning and verification. Work on the small animal research platform Irradion involved advanced software and hardware development that will offer researchers a novel way to investigate new approaches in (i) radiotherapy, (ii) spectral CT, (iii) arbitrary path CT, (iv) particle tracking. The robotic platform for imaging and radiation research developed for the project is an entirely new product on the market. Preclinical research systems with precision robotic irradiation with photon/ion beams combined with multimodality high-resolution imaging do not exist currently. The researched technology can potentially cause a significant leap forward compared to the current, first-generation primary devices.

Keywords: arbitrary path CT, robotic CT, modular, multi-robot, small animal imaging

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Authors: Zohra Aziz Ali Manjiyani, Renju Thomas Jacob, Keerthan Kumar

Abstract:

This project develops a hand movement monitoring system, which feeds the data into the computer and gives the 3D image rotation according to the direction of the tilt and hence monitoring the movement of the hand in context to its tilt. Advancement of MEMS Technology has enabled us to get very small and low-cost accelerometer ICs which is based on capacitive principle. Accelerometer based Tilt sensor ADXL335 is used in this paper, based on MEMS technology and the project emphasis on the development of the MEMS-based accelerometer to measure the tilt, interfacing the hardware with the LabVIEW and showing the 3D rotation to the user, which is in his understandable form and tilt data can be saved in the computer. It provides an experience of working on emerging technologies like MEMS and design software like LabVIEW.

Keywords: MEMS accelerometer, tilt sensor ADXL335, LabVIEW simulation, 3D animation

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

Abstract:

Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Ulysse Lecomte, Maryline Thenot

Abstract:

For a long time, disabled people lived in isolation within the family environment, with little interaction with the outside world and a high risk of social exclusion. However, in a number of countries, progress has been made thanks to changes in legislation on the social integration of disabled people, a significant change in attitudes, and the development of CSR. But the problem of their social, economic, and professional exclusion persists and has been further exacerbated by the COVID-19 pandemic. This societal phenomenon is sufficiently important to be the subject of management science research. We have therefore focused our work on society's current perception of people with disabilities and their possible integration. Our aim is to find out what levers could be put in place to bring about positive change in the situation. We have chosen to focus on the perception of young people in France, who are the new generation responsible for the future of our society and from whom tomorrow's decisionmakers, future employers, and stakeholders who can influence the living conditions of disabled people will be drawn. Our study sample corresponds to the 18-30 age group, which is the population of young adults likely to have sufficient experience and maturity. The aim of this study is not only to find out how this population currently perceives disability but also to identify the factors influencing this perception and the most effective levers for action to act positively on this phenomenon and thus promote better social integration of people with disabilities in the future. The methodology is based on theoretical and empirical research. The literature review includes a historical and etymological approach to disability, a definition of the different concepts of disability, an approach to disability as a vector of social exclusion, and the role of perception and representations in defining the social image of disability. This literature review is followed by an empirical part carried out by means of a questionnaire administered to 110 young people aged 18 to 30. Analysis of our results suggests that, despite a recent improvement, disabled people are still perceived as vulnerable and socially marginalised. The following factors stand out as having a significant influence (positive or negative) on the perception of disability: the individual's familiarity with the 'world of disability', cultural factors, the degree of 'visibility' of the disability and the empathy level of the disabled person him/herself. Others, on the other hand, such as socio-political and economic factors, have little impact on this perception. In addition, it is possible to classify the various levers of action likely to improve the social perception of disability according to their degree of effectiveness. Our study population prioritised training initiatives for the various players and stakeholders (teachers, students, disabled people themselves, companies, sports clubs, etc.). This was followed by communication, ecommunication and media campaigns in favour of disability. Lastly, the sample was judged as 'less effective' positive discrimination actions such as setting a minimum percentage for the representation of disabled people in various fields (studies, employment, politics ...).

Keywords: disability, perception, social image, young people, influencing factors, levers for action

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