Search results for: space detection to first responders

Authors: Jaechun No

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This paper focuses on I/O optimizations of N-hybrid (New-Form of hybrid), which provides a hybrid file system space constructed on SSD and HDD. Although the promising potentials of SSD, such as the absence of mechanical moving overhead and high random I/O throughput, have drawn a lot of attentions from IT enterprises, its high ratio of cost/capacity makes it less desirable to build a large-scale data storage subsystem composed of only SSDs. In this paper, we present N-hybrid that attempts to integrate the strengths of SSD and HDD, to offer a single, large hybrid file system space. Several experiments were conducted to verify the performance of N-hybrid.

Keywords: SSD, data section, I/O optimizations, hybrid system

Procedia PDF Downloads 418

Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

Procedia PDF Downloads 191

Authors: Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

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Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately and still require systematic clarification. The present study aimed to investigate the spatial-temporal clustering relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites were used to develop an index comprising rainfall, humidity and temperature data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling temporal analysis, spatial statistical analysis and space-time clustering analysis. Our present results showed that increases in the number of the combination of ecological factor and socio-economic and demographic factors with above the average or the presence contribute to significantly high rates of space-time dengue clusters.

Keywords: ALOS/AVNIR-2, dengue, space-time clustering analysis, Sri Lanka

Procedia PDF Downloads 476

Authors: Beata Patuszynska

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Children are largely absent from Polish social discourse, a fact which is mirrored in urban planning processes. Their absence creates a vicious circle – an unfriendly urban space discourages children from going outside on their own, meaning adults do not see a need to make spaces more friendly for a group, not present. The pandemic and lockdown, with their closed schools and temporary ban on unaccompanied minors on the streets, have only reinforced this. The project – co-writing with children a book concerning their first steps into urban independence - aims at empowering children, enabling them to find their voice when it comes to urban space. The foundation for the book was data collected during research and workshops with children from Warsaw primary schools, aged 7-10 - the age they begin independent travel in the city. The project was carried out with the participation and involvement of children at each creative step. Children were (1) models: the narrator is an 7-year-old boy getting ready for urban independence. He shares his experience as well as the experience of his school friends and his 10-year-old sister, who already travels on her own. Children were (2) teachers: the book is based on authentic children’s stories and experience, along with the author’s findings from research undertaken with children. The material was extended by observations and conclusions made during the pandemic. Children were (3) reviewers: a series of draft chapters from the book underwent review by children during workshops performed in a school. The process demonstrated that all children experience similar pleasures and worries when it comes to interaction with urban space. Furthermore, they also have similar needs that need satisfying. In my article, I will discuss; (1) the advantages of creating together with children; (2) my conclusions on how to work with children in participatory processes; (3) research results: perceptions of urban space by children age 7-10, when they begin their independent travel in the city; the barriers to and pleasures derived from independent urban travel; the influence of the pandemic on children’s feelings and their behaviour in urban spaces.

Keywords: children, urban space, co-creation, participation, human rights

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Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

Procedia PDF Downloads 134

Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

Procedia PDF Downloads 184

Authors: Suhib A. Abu-Seini, Kyung-Doo Kim

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A heat loss model for ATLAS facility was introduced using SPACE code predefined correlations and various dialing factors. As all previous simulations were carried out using a heat loss free input; the facility was considered to be completely insulated and the core power was reduced by the experimentally measured values of heat loss to compensate to the account for the loss of heat, this study will consider heat loss throughout the simulation. The new heat loss model will be affecting SPACE code simulation as heat being leaked out of the system throughout a transient will alter many parameters corresponding to temperature and temperature difference. For that, a Station Blackout followed by a multiple Steam Generator Tube Rupture accident will be simulated using both the insulated system approach and the newly introduced heat loss input of the steady state. Major parameters such as system temperatures, pressure values, and flow rates to be put into comparison and various analysis will be suggested upon it as the experimental values will not be the reference to validate the expected outcome. This study will not only show the significance of heat loss consideration in the processes of prevention and mitigation of various incidents, design basis and beyond accidents as it will give a detailed behavior of ATLAS facility during both processes of steady state and major transient, but will also present a verification of how credible the data acquired of ATLAS are; since heat loss values for steady state were already mismatched between SPACE simulation results and ATLAS data acquiring system. Acknowledgement- This work was supported by the Korean institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea.

Keywords: ATLAS, heat loss, simulation, SPACE, station blackout, steam generator tube rupture, verification

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Authors: Maleh Yassine, Ezzati Abdellah

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Wireless Sensor Networks (WSNs) are currently used in different industrial and consumer applications, such as earth monitoring, health related applications, natural disaster prevention, and many other areas. Security is one of the major aspects of wireless sensor networks due to the resource limitations of sensor nodes. However, these networks are facing several threats that affect their functioning and their life. In this paper we present security attacks in wireless sensor networks, and we focus on a review and analysis of the recent Intrusion Detection schemes in WSNs.

Keywords: wireless sensor networks, security attack, denial of service, IDS, cluster-based model, signature based IDS, hybrid IDS

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Authors: D. S. Palimkar

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Random fixed point theory has received much attention in recent years, and it is needed for the study of various classes of random equations. The study of random fixed point theorems was initiated by the Prague school of probabilistic in the 1950s. The existence and uniqueness of fixed points for the self-maps of a metric space by altering distances between the points with the use of a control function is an interesting aspect in the classical fixed point theory. In a new category of fixed point problems for a single self-map with the help of a control function that alters the distance between two points in a metric space which they called an altering distance function. In this paper, we prove the results of existence of random common fixed point and its uniqueness for a pair of random mappings under weakly contractive condition for generalizing alter distance function in polish spaces using Random Common Fixed Point Theorem for Generalized Weakly Contractions.

Keywords: Polish space, random common fixed point theorem, weakly contractive mapping, altering function

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Authors: Yangyang Zhang

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In The Valley of the Moon, Jack London implicitly presents the connection between the city and the male, the country and the female, constructing a gender space where the city and the countryside are opposed. But meanwhile, London is constantly dismantling the gender space through the reversed travel map so as to highlight the fluidity and productivity of female space. Under such circumstance, the original gender space has to be reorganized. Through the construction of gendered urban and rural spaces, Jack London presents the national crisis in the process of urbanization of the American West in the late 19th century, while the female-led reversed travel map reproduces the original contribution of the American West to the construction of nationality. In the end, the reorganized neutral space “valley of the moon” reflects the “garden” motif in American national imagination and plays an important role in rebuilding national identity. This research studies the feminist geography and cartography in Jack London's novel The Valley of the Moon and analyzes the gender-politics attribution in the literary geography writing in London's novel on this basis. The research returns to the American historical context at the end of the 19th century, focusing on how London’s feminist geography embodies his sense of nationality and investigating how female-dominated literary cartography reconstructs American identity. This paper takes Literary Cartography, and feminist geography as the ideological guide combines with the discourse of gender politics. comprehensively uses various literary criticism methods such as deconstructionist literary criticism, and new historicism literary criticism, etc., Through the study of Jack London's work, the paper aims to analyse how London constructs a national image by literary geography.

Keywords: American identity, American west, feminist geography, garden motif, the valley of the moon

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Authors: Gurpreet Kaur, Manoj Kumar, Vandana Bhalla

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Strong acceptor-weak acceptor system FN-TPy has been designed and synthesized which undergoes solvent dependent self-assembly in mixed aqueous media to generate through space intermolecular charge transfer assemblies. The as prepared entropically favoured assemblies of FN-TPy exhibit excellent photostability and photosensitizing properties in the assembled state to activate aerial oxygen for efficient generation of reactive oxygen species (ROS) through Type-I and Type-II pathways. The FN-TPy assemblies exhibit excellent potential for regulated oxidation of alcohols and aldehydes under mild reaction conditions (visible light irradiation, aqueous media, room temperature) using aerial oxygen as the ‘oxidant’. The present study demonstrates the potential of FN-TPy assemblies to catalyze controlled oxidation of benzyl alcohol to benzaldehyde and to corresponding benzoic acid.

Keywords: oxidations, photosensitizer, reactive oxygen species, supramolecular assemblies, through space charge transfer.

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Zipei Yin

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Community space is the main place for children's daily outdoor activities. The mountain community space has the typical characteristics of a closed natural environment, a scattered population layout with height differences, and a relatively independent group structure. This has resulted in special limitations on children's outdoor activities in terms of safety, accessibility, and appropriateness, which urgently makes it necessary to explore how to construct children's activity spaces in mountainous societies under the special limitations. This study investigated the activity spaces for children aged 3-11 years old in typical old communities in Chongqing and evaluated them based on the dimensions of spatial characteristics, environmental safety, and connectivity to summarise three typical patterns of children's outdoor activity spaces in old communities in mountainous cities. Then, under the framework of the appeal of the child-friendly urban environment, taking advantage of the characteristics of the old community in mountain cities compared with the plain urban community, such as complex social form, diversified functional positioning, and good foundation of autonomy, this paper explores the micro-renewal path and strategy of the compound utilization of community public space from the two levels of design and governance, so as to further promote the research and practice of the healthy development of mountain urban community environment.

Keywords: child-friendly, healthy community, community public space, mountainous urban community, community renewal

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Authors: Sanaa Chafik, Imane Daoudi, Mounim A. El Yacoubi, Hamid El Ouardi

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Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

Keywords: approximate nearest neighbor search, content based image retrieval (CBIR), curse of dimensionality, locality sensitive hashing, multidimensional indexing, scalability

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Authors: Ravi Kant, Banshi D. Gupta

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The unbridled application of insecticides to enhance agricultural yield has become a matter of grave concern to both the environment and the human health and, thus pose a potential threat to sustainable development. Fenitrothion is an extensively used organophosphate insecticide whose residues are reported to be extremely toxic for birds, humans and aquatic life. A sensitive, swift and accurate detection protocol for fenitrothion is, thus, highly demanded. In this work, we report an SPR based fiber optic sensor for the detection of fenitrothion, where a nanocomposite arrangement of Ta2O5 and reduced graphene oxide (rGO) (Ta₂O₅: rGO) decorated on silver coated unclad core region of an optical fiber forms the sensing channel. A nanocomposite arrangement synergistically integrates the properties of involved components and consequently furnishes a conducive framework for sensing applications. The modification of the dielectric function of the sensing layer on exposure to fenitrothion solutions of diverse concentration forms the sensing mechanism. This modification is reflected in terms of the shift in resonance wavelength. Experimental variables such as the concentration of rGO in the nanocomposite configuration, dip time of silver coated fiber optic probe for deposition of sensing layer and influence of pH on the performance of the sensor have been optimized to extract the best performance of the sensor. SPR studies on the optimized sensing probe reveal the high sensitivity, wide operating range and good reproducibility of the fabricated sensor, which unveil the promising utility of Ta₂O₅: rGO nanocomposite framework for developing an efficient detection methodology for fenitrothion. FOSPR approach in cooperation with nanomaterials projects the present work as a beneficial approach for fenitrothion detection by imparting numerous useful advantages such as sensitivity, selectivity, compactness and cost-effectiveness.

Keywords: surface plasmon resonance, optical fiber, sensor, fenitrothion

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Authors: Neha Narayanan

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The paper tries to explore the role of language in determining spaces occupied by women in everyday lives. It is inspired from an ongoing action research work which employs ‘immersion’- arriving at a research problematic through community research, as a methodology in a Kondh adivasi village, Kirkalpadu located in Rayagada district of the Indian state of Odisha. In the dominant development discourse, language is associated with either preservation or conservation of endangered language or empowerment through language. Beyond these, is the discourse of language as a structure, with the hegemonic quality to organise lifeworld in a specific manner. This rigid structure leads to an experience of constriction of space for women. In Kirkalpadu, the action research work is with young and unmarried women of the age 15-25. During daytime, these women are either in the agricultural field or in the bari -the backyard of the house whose rooms are linearly arranged one after the other ending with the kitchen followed by an open space called bari (in Odia) which is an intimate and gendered space- where they are not easily visible. They justify the experience of restriction in mobility and fear of moving out of the village alone by the argument that the place and the men are nihi-aaeh (not good). These women, who have dropped out of school early to contribute to the (surplus) labour requirement in the household, want to learn English to be able to read signboards when they are on the road, to be able to fill forms at a bank and use mobile phones to communicate with their romantic partner(s). But the incapacity to have within one’s grasp the province of language and the incapacity to take the mobile phone to the kind of requirements marked by the above mentioned impossible transactions with space restricts them to the bari of the house. The paper concludes by seeking to explore the possibilities of learning and rethinking languages which takes into cognizance the gendered experience of women and the desire of women to cross the borders and occupy spaces restricted to them.

Keywords: action research, gendered experience, language, space

Procedia PDF Downloads 171

Authors: Behnaz Sohani, Sahand Shahalinezhad, Amir Rahmani, Aliyu Aliyu

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Recently, medical imaging and specifically medical image processing is becoming one of the most dynamically developing areas of medical science. It has led to the emergence of new approaches in terms of the prevention, diagnosis, and treatment of various diseases. In the process of diagnosis of lung cancer, medical professionals rely on computed tomography (CT) scans, in which failure to correctly identify masses can lead to incorrect diagnosis or sampling of lung tissue. Identification and demarcation of masses in terms of detecting cancer within lung tissue are critical challenges in diagnosis. In this work, a segmentation system in image processing techniques has been applied for detection purposes. Particularly, the use and validation of a novel lung cancer detection algorithm have been presented through simulation. This has been performed employing CT images based on multilevel thresholding. The proposed technique consists of segmentation, feature extraction, and feature selection and classification. More in detail, the features with useful information are selected after featuring extraction. Eventually, the output image of lung cancer is obtained with 96.3% accuracy and 87.25%. The purpose of feature extraction applying the proposed approach is to transform the raw data into a more usable form for subsequent statistical processing. Future steps will involve employing the current feature extraction method to achieve more accurate resulting images, including further details available to machine vision systems to recognise objects in lung CT scan images.

Keywords: lung cancer detection, image segmentation, lung computed tomography (CT) images, medical image processing

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Authors: Rene Davids

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Urban undergrounds spaces such as parking garages or metro stations are perceived as interludes before reaching desired destinations, as commodities devoid of aesthetic value. Within the encoded space of the city, commercial underground spaces are the closest expression to pure to structures of consumption and commodity. Even in the house, the cellar is associated with castoffs and waste or, as scholar Mircea Eliade has pointed out at best, with a place to store abandoned household and childhood objects, which lie forgotten and on rediscovery evoke a nostalgic and uncanny sense of the past. Despite a growing body of evidence presented by an increasing number of buildings situated entirely below or semi underground that feature exemplary spatial and sensuous qualities, critics and scholars see them largely as efforts to produce efforts in producing low consumption non-renewable energy. Buildings that also free space above ground. This critical approach neglects to mention and highlight other project drivers such as the notion that the ground and sky can be considered a building’s fundamental context, that underground spaces are conducive to the exploration of pure space, namely an architecture that doesn’t have to deal with facades and or external volumes and that digging into geology can inspire the textural and spatial richness. This paper will argue that while the assessment about the reduced energy consumption of underground construction is important, it does not do justice to the qualities underground buildings can contribute to a city’s expanded urban and or landscape experiences.

Keywords: low non-renewable energy consumption, pure space, underground buildings, urban and landscape experience

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Authors: Marta Kaprzyk

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The cinema of Alejandro González Iñárritu hasn’t been subjected to a lot of detailed analysis yet, what makes it an exceptionally interesting research material. The purpose of this presentation is to discuss the significance of urban space in three films of this Mexican director, that forms Death Trilogy: ‘Amores Perros’ (2000), ‘21 Grams’ (2003) and ‘Babel’ (2006). The fact that in the aforementioned movies the urban space itself becomes an additional protagonist with its own identity, psychology and the ability to transform and affect other characters, in itself warrants for independent research and analysis. Independently, such mode of presenting urban space has another function; it enables the director to complement the rest of characters. The basis for methodology of this description of cinematographic space is to treat its visual layer as a point of departure for a detailed analysis. At the same time, the analysis itself will be supported by recognised academic theories concerning special issues, which are transformed here into essential tools necessary to describe the world (mise-en-scène) created by González Iñárritu. In ‘Amores perros’ the Mexico City serves as a scenery – a place full of contradictions- in the movie depicted as a modern conglomerate and an urban jungle, as well as a labyrinth of poverty and violence. In this work stylistic tropes can be found in an intertextual dialogue of the director with photographies of Nan Goldin and Mary Ellen Mark. The story recounted in ‘21 Grams’, the most tragic piece in the trilogy, is characterised by almost hyperrealistic sadism. It takes place in Memphis, which on the screen turns into an impersonal formation full of heterotopias described by Michel Foucault and non-places, as defined by Marc Augé in his essay. By contrast, the main urban space in ‘Babel’ is Tokio, which seems to perfectly correspond with the image of places discussed by Juhani Pallasmaa in his works concerning the reception of the architecture by ‘pathological senses’ in the modern (or, even more adequately, postmodern) world. It’s portrayed as a city full of buildings that look so surreal, that they seem to be completely unsuitable for the humans to move between them. Ultimately, the aim of this paper is to demonstrate the coherence of the manner in which González Iñárritu designs urban spaces in his Death Trilogy. In particular, the author attempts to examine the imperative role of the cities that form three specific microcosms in which the protagonists of the Mexican director live their overwhelming tragedies.

Keywords: cinematographic space, Death Trilogy, film Studies, González Iñárritu Alejandro, urban space

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Radhika Ranjan Roy

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Deployment of machine learning (ML)/deep learning (DL) algorithms for cyberattack detection in operational communications networks (wireless and/or wire-line) is being delayed because of low-performance parameters (e.g., recall, precision, and f₁-score). If datasets become imbalanced, which is the usual case for communications networks, the performance tends to become worse. Complexities in handling reducing dimensions of the feature sets for increasing performance are also a huge problem. Mahalanobis algorithms have been widely applied in scientific research because Mahalanobis distance metric learning is a successful framework. In this paper, we have investigated the Mahalanobis binary classifier algorithm for increasing cyberattack detection performance over communications networks as a proof of concept. We have also found that high-dimensional information in intermediate features that are not utilized as much for classification tasks in ML/DL algorithms are the main contributor to the state-of-the-art of improved performance of the Mahalanobis method, even for imbalanced and sparse datasets. With no feature reduction, MD offers uniform results for precision, recall, and f₁-score for unbalanced and sparse NSL-KDD datasets.

Keywords: Mahalanobis distance, machine learning, deep learning, NS-KDD, local intrinsic dimensionality, chi-square, positive semi-definite, area under the curve

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Authors: D. Maneetham, L. Sivhour

Abstract:

Robotic arm manipulators are widely used to accomplish many kinds of tasks. SCORBOT-ER 4u is a 5-degree of freedom (DOF) vertical articulated educational robotic arm, and all joints are revolute. It is specifically designed to perform pick and place task with its gripper. The pick and place task consists of consideration of the end effector coordinate of the robotic arm and the desired position coordinate in its workspace. This paper describes about forward kinematics modeling and analysis of the robotic end effector motion through joint space. The kinematics problems are defined by the transformation from the Cartesian space to the joint space. Denavit-Hartenberg (D-H) model is used in order to model the robotic links and joints with 4x4 homogeneous matrix. The forward kinematics model is also developed and simulated in MATLAB. The mathematical model is validated by using robotic toolbox in MATLAB. By using this method, it may be applicable to get the end effector coordinate of this robotic arm and other similar types to this arm. The software development of SCORBOT-ER 4u is also described here. PC-and EtherCAT based control technology from BECKHOFF is used to control the arm to express the pick and place task.

Keywords: forward kinematics, D-H model, robotic toolbox, PC- and EtherCAT-based control

Procedia PDF Downloads 179

Authors: Junichiro Kawaguchi

Abstract:

Space debris problems have emerged and threatened the use of low earth orbit around the Earth owing to a large number of spacecraft. In debris removal, a number of research and patents have been proposed and published so far. They assume servicing spacecraft, robots to be built for accessing the target debris objects. The robots should be sophisticated enough automatically to access the debris articulating the attitude and the translation motion with respect to the debris. This paper presents the idea of using the torpedo-like third unsophisticated and disposable body, in addition to the first body of the servicing robot and the second body of the target debris. The third body is launched from the first body from a distance farer than the size of the second body. This paper presents the method and the system, so that the third body is launched from the first body. The third body carries both a net and an inflatable or extendible drag deceleration device and is built small and light. This method enables even a micro to nano satellite to perform contactless and multiple debris removal even via a single flight.

Keywords: ballute, debris removal, echo satellite, gossamer, gun-net, inflatable space structure, small satellite, un-cooperated target

Procedia PDF Downloads 121

Authors: Marwa Qaraqe, Muhammad Ismail, Erchin Serpedin

Abstract:

This paper presents a novel architecture for a patient-specific epileptic seizure onset detector using scalp electroencephalography (EEG). The proposed architecture is based on the decision fusion calculated from energy and neural synchronization related features. Specifically, one level of the detector calculates the condition number (CN) of an EEG matrix to evaluate the amount of neural synchronization present within the EEG channels. On a parallel level, the detector evaluates the energy contained in four EEG frequency subbands. The information is then fed into two independent (parallel) classification units based on support vector machines to determine the onset of a seizure event. The decisions from the two classifiers are then combined together according to two fusion techniques to determine a global decision. Experimental results demonstrate that the detector based on the AND fusion technique outperforms existing detectors with a sensitivity of 100%, detection latency of 3 seconds, while it achieves a 2:76 false alarm rate per hour. The OR fusion technique achieves a sensitivity of 100%, and significantly improves delay latency (0:17 seconds), yet it achieves 12 false alarms per hour.

Keywords: epilepsy, EEG, seizure onset, electroencephalography, neuron, detection

Procedia PDF Downloads 478

Authors: Nataša Todorović, Jovana Nikolov, Ivana Stojković, Milan Vraneš, Jovana Panić, Slobodan Gadžurić

Abstract:

The detection of ²¹⁰Pb levels in aquatic environments evokes interest in various scientific studies. Its precise determination is important not only for the radiological assessment of drinking waters but also ²¹⁰Pb, and ²¹⁰Po distribution in the marine environment are significant for the assessment of the removal rates of particles from the ocean and particle fluxes during transport along the coast, as well as particulate organic carbon export in the upper ocean. Measurement techniques for ²¹⁰Pb determination, gamma spectrometry, alpha spectrometry, or liquid scintillation counting (LSC) are either time-consuming or demand expensive equipment or complicated chemical pre-treatments. However, one other possibility is to measure ²¹⁰Pb on an LS counter if it is in equilibrium with its progeny ²¹⁰Bi - through the Cherenkov counting method. It is unaffected by the chemical quenching and assumes easy sample preparation but has the drawback of lower counting efficiencies than standard LSC methods, typically from 10% up to 20%. The aim of the presented research in this paper is to investigate the possible increment of detection efficiency of Cherenkov counting during ²¹⁰Pb/²¹⁰Bi detection on an LS counter Quantulus 1220. Considering naturally low levels of ²¹⁰Pb in aqueous samples, the addition of ionic liquids to the counting vials with the analysed samples has the benefit of detection limit’s decrement during ²¹⁰Pb quantification. Our results demonstrated that ionic liquid, 1-butyl-3-methylimidazolium salicylate, is more efficient in Cherenkov counting efficiency increment than the previously explored 2-hydroxypropan-1-amminium salicylate. Consequently, the impact of a few other ionic liquids that were synthesized with the same cation group (1-butyl-3-methylimidazolium benzoate, 1-butyl-3-methylimidazolium 3-hydroxybenzoate, and 1-butyl-3-methylimidazolium 4-hydroxybenzoate) was explored in order to test their potential influence on Cherenkov counting efficiency. It was confirmed that, among the explored ones, only ionic liquids in the form of salicylates exhibit a wavelength shifting effect. Namely, the addition of small amounts (around 0.8 g) of 1-butyl-3-methylimidazolium salicylate increases the detection efficiency from 16% to >70%, consequently reducing the detection threshold by more than four times. Moreover, the addition of ionic liquids could find application in the quantification of other radionuclides besides ²¹⁰Pb/²¹⁰Bi via Cherenkov counting method.

Keywords: liquid scintillation counting, ionic liquids, Cherenkov counting, ²¹⁰PB/²¹⁰BI in water

Procedia PDF Downloads 103

Authors: Alaa A. Almarzuki, Nora A. Farraj, Aisha M. Alshiky, Omar A. Batarfi

Abstract:

The number of internet users is dramatically increased every year. Most of these users are exposed to the dangers of attackers in one way or another. The reason for this lies in the presence of many weaknesses that are not known for native users. In addition, the lack of user awareness is considered as the main reason for falling into the attackers’ snares. Cross Site Request Forgery (CSRF) has placed in the list of the most dangerous threats to security in OWASP Top Ten for 2013. CSRF is an attack that forces the user’s browser to send or perform unwanted request or action without user awareness by exploiting a valid session between the browser and the server. When CSRF attack successes, it leads to many bad consequences. An attacker may reach private and personal information and modify it. This paper aims to detect and prevent a specific type of CSRF, called reflected CSRF. In a reflected CSRF, a malicious code could be injected by the attackers. This paper explores how CSRF Detection Extension prevents the reflected CSRF by checking browser specific information. Our evaluation shows that the proposed solution succeeds in preventing this type of attack.

Keywords: CSRF, CSRF detection extension, attackers, attacks

Procedia PDF Downloads 414

Authors: Ahmed Ashit

Abstract:

Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

Procedia PDF Downloads 364