Search results for: geophysical database referenced navigation

Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Sana Ilyas, Kishalaya Mukherjee, Suresh Shetty

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Lip Augmentation has become more common in recent years. Patients do not expect to experience facial palsy after having lip augmentation. This poster will present the findings of such a presentation and will discuss the possible pathophysiology and management. (This poster has been published as a paper in the dental update, June 2022) Aim: The aim of the study was to explore the link between facial nerve palsy and lip fillers, to explore the literature surrounding facial nerve palsy, and to discuss the case of a patient who presented with facial nerve palsy with seemingly unknown cause. Methodology: There was a thorough assessment of the current literature surrounding the topic. This included published papers in journals through PubMed database searches and printed books on the topic. A case presentation was discussed in detail of a patient presenting with peripheral facial nerve palsy and associating it with lip augmentation that she had a day prior. Results and Conclusion: Even though the pathophysiology may not be clear for this presentation, it is important to highlight uncommon presentations or complications that may occur after treatment. This can help with understanding and managing similar cases, should they arise.It is also important to differentiate cause and association in order to make an accurate diagnosis. This may be difficult if there is little scientific literature. Therefore, further research can help to improve the understanding of the pathophysiology of similar presentations. This poster has been published as a paper in dental update, June 2022, and therefore shares a similar conclusiom.

Keywords: facial palsy, lip augmentation, causation and correlation, dental cosmetics

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Authors: Mostafa Shahriari, Sergio Rojas, David Pardo, Angel Rodriguez- Rozas, Shaaban A. Bakr, Victor M. Calo, Ignacio Muga

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Logging-While Drilling (LWD) is a technique to record down-hole logging measurements while drilling the well. Nowadays, LWD devices (e.g., nuclear, sonic, resistivity) are mostly used commercially for geo-steering applications. Modern borehole resistivity tools are able to measure all components of the magnetic field by incorporating tilted coils. The depth of investigation of LWD tools is limited compared to the thickness of the geological layers. Thus, it is a common practice to approximate the Earth’s subsurface with a sequence of 1D models. For a 1D model, we can reduce the dimensionality of the problem using a Hankel transform. We can solve the resulting system of ordinary differential equations (ODEs) either (a) analytically, which results in a so-called semi-analytic method after performing a numerical inverse Hankel transform, or (b) numerically. Semi-analytic methods are used by the industry due to their high performance. However, they have major limitations, namely: -The analytical solution of the aforementioned system of ODEs exists only for piecewise constant resistivity distributions. For arbitrary resistivity distributions, the solution of the system of ODEs is unknown by today’s knowledge. -In geo-steering, we need to solve inverse problems with respect to the inversion variables (e.g., the constant resistivity value of each layer and bed boundary positions) using a gradient-based inversion method. Thus, we need to compute the corresponding derivatives. However, the analytical derivatives of cross-bedded formation and the analytical derivatives with respect to the bed boundary positions have not been published to the best of our knowledge. The main contribution of this work is to overcome the aforementioned limitations of semi-analytic methods by solving each 1D model (associated with each Hankel mode) using an efficient multi-scale finite element method. The main idea is to divide our computations into two parts: (a) offline computations, which are independent of the tool positions and we precompute only once and use them for all logging positions, and (b) online computations, which depend upon the logging position. With the above method, (a) we can consider arbitrary resistivity distributions along the 1D model, and (b) we can easily and rapidly compute the derivatives with respect to any inversion variable at a negligible additional cost by using an adjoint state formulation. Although the proposed method is slower than semi-analytic methods, its computational efficiency is still high. In the presentation, we shall derive the mathematical variational formulation, describe the proposed multi-scale finite element method, and verify the accuracy and efficiency of our method by performing a wide range of numerical experiments and comparing the numerical solutions to semi-analytic ones when the latest are available.

Keywords: logging-While-Drilling, resistivity measurements, multi-scale finite elements, Hankel transform

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

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Authors: Asadollah Bahrami

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In the present study, spectral radiative entropy generation is analyzed in a furnace filled with a mixture of H₂O, CO₂ and soot at radiative equilibrium. For the angular and spatial discretization of the radiative transfer equation and radiative entropy generation equations, the discrete ordinates method and the finite volume method are used, respectively. Spectral radiative properties are obtained using the correlated-k (CK) non-gray model with updated parameters based on the HITEMP2010 high-resolution database. In order to evaluate the effects of the location of the heat source, boundary condition and wall emissivity on radiative entropy generation, five cases are considered with different conditions. The spectral and total radiative entropy generation in the system are calculated for all cases and the effects of mentioned parameters on radiative entropy generation are attentively analyzed and finally, the optimum condition is especially presented. The most important results can be stated as follows: Results demonstrate that the wall emissivity has a considerable effect on the radiative entropy generation. Also, irreversible radiative transfer at the wall with lower temperatures is the main source of radiative entropy generation in the furnaces. In addition, the effect of the location of the heat source on total radiative entropy generation is less than other factors. Eventually, it can be said that characterizing the effective parameters of radiative entropy generation provides an approach to minimizing the radiative entropy generation and enhancing the furnace's performance practicality.

Keywords: spectral radiative entropy generation, non-gray medium, correlated k(CK) model, heat source

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Authors: Jiajia Peng, Jianqing Qiu, Jianjun Ren, Yu Zhao

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Background: We aimed to compare clinical and survival differences between B-cell (B-NHL) and NKT-cell non-Hodgkin lymphomas (NKT-NHL) located in the nasal cavity, nasopharynx and paranasal sinuses, which are always categorized as one sinonasal type. Methods: Patients diagnosed with primary B-NHL and NKT-NHL in the nasal cavity, nasopharynx, and paranasal sinuses from the SEER database were included. We identified these patients based on histological types and anatomical sites and subsequently conducted univariate and multivariate Cox regression and Kaplan–Meier analyses to examine cancer-special survival (CSS) outcomes. Results: Overall, most B-NHL cases originated from the nasopharynx, while the majority of NKT-NHL cases occurred in the nasal cavity. Notably, the CSS outcomes improved significantly in all sinonasal B-NHL cases over time, whereas no such improvement trend was observed in each sinonasal NKT-NHL type. Additionally, increasing age was linked with an elevated risk of death in B-NHL, particularly in the nasal cavity (HR:3.37), rather than in NKT-NHL. Compared with B-NHL, the adverse effect of the higher stage on CSS was more evident in NKT-NHL, particularly in its nasopharynx site (HR: 5.12). Furthermore, radiotherapy was beneficial for survival in patients with sinonasal B-NHL and NKT-NHL, except in those with NKT-NHL in the nasopharynx site. However, chemotherapy has only been beneficial for CSS in patients with B-NHL in paranasal sinuses (HR: 0.42) since 2010, rather than in other types of B-NHL or NKT-NHL. Conclusions: Although B-NHL and NKT-NHL in the nasal cavity, nasopharynx and paranasal sinuses have similar anatomical locations, their clinic demographics and prognoses are largely different and should be treated and studied as distinct diseases.

Keywords: B-cell non-Hodgkin lymphomas, NKT-cell non-Hodgkin lymphomas, nasal cavity lymphomas, nasal sinuses lymphomas, nasopharynx lymphomas

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Authors: Rajkumar Ghosh

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Earthquakes pose significant risks to human life and infrastructure, highlighting the importance of effective earthquake mitigation strategies. Traditional earthquake modelling and mitigation efforts have largely focused on the primary fault segments and their slip behaviour. However, earthquakes can exhibit complex rupture dynamics, including out-of-sequence thrust (OOST) events, which occur on secondary or subsidiary faults. This abstract examines the impact of OOST dynamics on earthquake mitigation strategies and their implications for hazard assessment and disaster planning. OOST events challenge conventional seismic hazard assessments by introducing additional fault segments and potential rupture scenarios that were previously unrecognized or underestimated. Consequently, these events may increase the overall seismic hazard in affected regions. The study reviews recent case studies and research findings that illustrate the occurrence and characteristics of OOST events. It explores the factors contributing to OOST dynamics, such as stress interactions between fault segments, fault geometry, and mechanical properties of fault materials. Moreover, it investigates the potential triggers and precursory signals associated with OOST events to enhance early warning systems and emergency response preparedness. The abstract also highlights the significance of incorporating OOST dynamics into seismic hazard assessment methodologies. It discusses the challenges associated with accurately modelling OOST events, including the need for improved understanding of fault interactions, stress transfer mechanisms, and rupture propagation patterns. Additionally, the abstract explores the potential for advanced geophysical techniques, such as high-resolution imaging and seismic monitoring networks, to detect and characterize OOST events. Furthermore, the abstract emphasizes the practical implications of OOST dynamics for earthquake mitigation strategies and urban planning. It addresses the need for revising building codes, land-use regulations, and infrastructure designs to account for the increased seismic hazard associated with OOST events. It also underscores the importance of public awareness campaigns to educate communities about the potential risks and safety measures specific to OOST-induced earthquakes. This sheds light on the impact of out-of-sequence thrust dynamics in earthquake mitigation. By recognizing and understanding OOST events, researchers, engineers, and policymakers can improve hazard assessment methodologies, enhance early warning systems, and implement effective mitigation measures. By integrating knowledge of OOST dynamics into urban planning and infrastructure development, societies can strive for greater resilience in the face of earthquakes, ultimately minimizing the potential for loss of life and infrastructure damage.

Keywords: earthquake mitigation, out-of-sequence thrust, seismic, satellite imagery

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Authors: Omotoke Omosalewa Owolowo

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Mass literacy adult and non-formal education are part of the provisions of Nigeria’s National policy on Education. The advent of Information and Communication Technology (ICT), especially in this era of industrial revolution, calls for approaching these literacy and adult education in different perspective for community development. There is dire need of Needs Assessment for effective training of rural dwellers to actualize the policy requirement and for the purpose of aligning with the Sustainable Development Goals in South - West Nigeria. The present study is a preliminary survey designed to determine level of awareness, use and familiarity of community dwellers of social media. Adult dwellers from 24 communities from four states in Southern Nigeria constitute the sample, a total of 578 adults (380 females, 198 males) with age range between 21 and 52 years. The survey shows that 68% are aware of SMS, 21% of WhatsApp, 14% of Facebook while the remaining could not say precisely what social medium is their favorite. However, most of them (80%) could not see how their phones can be used to boost their status, improve their vacations or be used to develop them in their respective community. The study is expected to lead to a more elaborate training program on assessment of knowledge acquisition, participation and attitude of adult literate and non- literate members in communities for empowerment and to integrate ICT techniques. The results of this study provides a database for the larger study.

Keywords: mass literacy, community development, information and communication technology, adult learners

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Authors: Kevin F. Hsu, Alvin Chua, Sarah X. Lin

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As a multilingual society, Singaporean names for different parts of the city have changed over time. Residents included Indigenous Malays, dialect-speakers from China, European settler-colonists, and Tamil-speakers from South India. Each group would name locations in their own languages. Today, as ancestral tongues are increasingly supplanted by English, contemporary Singaporeans’ understanding of once-common place names is disappearing. After demolition or redevelopment, some urban places will only exist in archival records or in human memory. United Nations conferences on the standardization of geographic names have called attention to how place names relate to identity, well-being, and a sense of belonging. The Singapore Place-Naming Project responds to these imperatives by capturing past and present place names through digitizing historical maps, mining archival records, and applying selective crowd-sourcing to trace the evolution of place names throughout the city. The project ensures that both formal and vernacular geographical names remain accessible to historians, city planners, and the public. The project is compiling a gazetteer, a geospatial archive of placenames, with streets, buildings, landmarks, and other points of interest (POI) appearing in the historic maps and planning documents of Singapore, currently held by the National Archives of Singapore, the National Library Board, university departments, and the Urban Redevelopment Authority. To create a spatial layer of information, the project links each place name to either a geo-referenced point, line segment, or polygon, along with the original source material in which the name appears. This record is supplemented by crowd-sourced contributions from civil service officers and heritage specialists, drawing from their collective memory to (1) define geospatial boundaries of historic places that appear in past documents, but maybe unfamiliar to users today, and (2) identify and record vernacular place names not captured in formal planning documents. An intuitive interface allows participants to demarcate feature classes, vernacular phrasings, time periods, and other knowledge related to historical or forgotten spaces. Participants are stratified into age bands and ethnicity to improve representativeness. Future iterations could allow additional public contributions. Names reveal meanings that communities assign to each place. While existing historical maps of Singapore allow users to toggle between present-day and historical raster files, this project goes a step further by adding layers of social understanding and planning documents. Tracking place names illuminates linguistic, cultural, commercial, and demographic shifts in Singapore, in the context of transformations of the urban environment. The project also demonstrates how a moderated, selectively crowd-sourced effort can solicit useful geospatial data at scale, sourced from different generations, and at higher granularity than traditional surveys, while mitigating negative impacts of unmoderated crowd-sourcing. Stakeholder agencies believe the project will achieve several objectives, including Supporting heritage conservation and public education; Safeguarding intangible cultural heritage; Providing historical context for street, place or development-renaming requests; Enhancing place-making with deeper historical knowledge; Facilitating emergency and social services by tagging legal addresses to vernacular place names; Encouraging public engagement with heritage by eliciting multi-stakeholder input.

Keywords: collective memory, crowd-sourced, digital heritage, geospatial, geographical names, linguistic heritage, place-naming, Singapore, Southeast Asia

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: J. Milton, C. Uzoigwe, O. Ayeko, B. Offorha, K. Anderson, R. G. Middleton

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Background: We used the UK National Hip Fracture database to determine the effect of institution hip fracture case volume on hip fracture healthcare outcomes in 2019. Using logistic regression for each healthcare outcome, we compared the best performing 50 units with the poorest performing 50 units in order to determine if the unit volume was associated with performance for each particular outcome. Method: We analysed 175 institutions treating a total of 67,673 patients over the course of a year. Results: The number of hip fractures seen per unit ranged between 86 and 952. Larger units tendered to perform health assessments more consistently and mobilise patients more expeditiously post-operatively. Patients treated at large institutions had shorter lengths of stay. With regard to most other outcomes, there was no association between unit case volume and performance, notably compliance with the Best Practice Tariff, time to surgery, proportion of eligible patients undergoing total hip arthroplasty, length of stay, delirium risk, and pressure sore risk assessments. Conclusion: There is no relationship between unit volume and the majority of health care outcomes. It would seem that larger institutions tend to perform better at parameters that are dependent upon personnel numbers. However, where the outcome is contingent, even partially, on physical infrastructure capacity, there was no difference between larger and smaller units.

Keywords: institution volume, mortality, neck of femur fractures, osteoporosis

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Authors: Athanasia Kouroupa

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Existing research highlights the effect of employing robots in sessions with children and young people on the autism spectrum to develop and practice skills important to independent and functional living. The systematic review aimed to explore the way robots has been used with children and young people on the autism spectrum and the effect of using robots as a therapeutic interface. An electronic bibliographic database search using a combination of expressions was conducted. Data were extracted in relation to robot types, session characteristics, and outcomes and analysed using narrative synthesis. Forty studies were selected in the review. Humanoid robots were predominantly used to practice a range of social and communication skills. On average, children and young people on the autism spectrum had five sessions, twice a week, for approximately half an hour. Having sessions with a robot was commonly equal to or more effective than 'traditional' interventions delivered by a human therapist or having no therapy. The review reported encouraging outcomes to practice and develop a range of skills with children and young people on the autism spectrum. These findings suggest that some form of intervention is favourable over no intervention. However, there is little evidence for the relative effectiveness of the robot-based intervention as an innovative alternative option. Many of the studies had methodological weaknesses that make them vulnerable to bias. There is a need for further research that adheres to strict scientific methods making direct comparisons between different treatment options.

Keywords: autism, children, robots, outcomes

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Authors: Muhammad Akbar Hussain, Muhammad Mehdi Hussain, Waqar Haider

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There are tens of thousands of undetected and uncatalogued pieces of space debris in the Low Earth Orbit (LEO). They are not only difficult to be detected and tracked, their sheer number puts active satellites and humans in orbit around Earth into danger. With the entry of more governments and private companies into harnessing the Earth’s orbit for communication, research and military purposes, there is an ever-increasing need for not only the detection and cataloguing of these pieces of space debris, it is time to take measures to take them out and clean up the space around Earth. Current optical and radar-based Space Situational Awareness initiatives are useful mostly in detecting and cataloguing larger pieces of debris mainly for avoidance measures. Smaller than 10 cm pieces are in a relatively dark zone, yet these are deadly and capable of destroying satellites and human missions. A network of mobile observatories, connected to each other in real time and working in unison as a single instrument, may be able to detect small pieces of debris and achieve effective triangulation to help create a comprehensive database of their trajectories and parameters to the highest level of precision. This data may enable ground-based laser systems to help deorbit individual debris. Such a network of observatories can join current efforts in detection and removal of space debris in Earth’s orbit.

Keywords: space debris, low earth orbit, mobile observatories, triangulation, seamless operability

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Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava

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Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.

Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)

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Authors: Thilivhali Emmanuel Tshikalange, Phiwokuhle Mamba

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Ten medicinal plants used traditionally in the treatment of sexually transmitted diseases (STDs) and urinary tract infections (UTIs) were selected from an ethnobotanical database developed in Mpumalanga. The plants were investigated for their antimicrobial activity against five bacterial strains (Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Neisseria gonorrhoeae and Staphylococcus aureus) and one fungal strain (Candida albicans). Eight of the plants inhibited the growth of all microorganisms at a concentration range of 0.4 mg/ml to 12.5 mg/ml. Acacia karroo showed the most promising antimicrobial activity, with a minimum inhibitory concentration (MIC) of 0.4 mg/ml on Staphylococcus aureus and 0.8 mg/ml on Neisseria gonorrhoeae. All ten plants were further investigated for their antioxidant activities using the DPPH scavenging method. Acacia karroo and Rhoicissus tridentata subsp. cuneifolia showed good antioxidant activity with IC50 values of 0.83 mg/ml and 0.06 mg/ml, respectively. The toxicity of plants was determined using the XTT reduction method against Vero cells. None of the ten plants showed toxicity on the cells. The obtained results confirmed that Acacia karroo and possibly Rhoicissus tridentata subsp. cuneifolia have the potential of being used as antimicrobial agents in the treatment of STDs and UTIs. These results support and validate traditional use of medicinal plants studied.

Keywords: antimicrobial, antioxidant, Neisseria gonorrhoeae, sexually transmitted diseases

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Authors: Marwa Al-Subhi, Eiman Al-Ajmi, Mallak Al-Maamari, Humood Al-Dhuhli, Srinivasa Rao

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The orbit and its contents are affected by various pathologies and craniofacial anomalies. Sound knowledge of the normal orbital dimensions is clinically essential for successful surgical outcomes and also in the field of forensic anthropology. Racial, ethnic, and regional variations in the orbital dimensions have been reported. This study sought to determine the orbital dimensions of Omani subjects who had been referred for computed tomography (CT) images at a tertiary care hospital. A total of 273 patients’ CT images were evaluated retrospectively by using an electronic medical records database. The orbital dimensions were recorded using both axial and sagittal planes of CT images. The mean orbital index (OI) was found to be 83.25±4.83 and the prevalent orbital type was categorized as mesoseme. The mean orbital index was 83.34±5.05 and 83.16±4.57 in males and females, respectively, with their difference being statistically not significant (p=0.76). A statistically significant association was observed between the right and left orbits with regard to horizontal distance (p<0.05) and vertical distance (p<0.01) of orbit and OI (p<0.05). No significant difference between the OI and age groups was observed in both males and females. The mean interorbital distance and interzygomatic distance were found to be 19.45±1.52 mm and 95.59±4.08 mm, respectively. Both of these parameters were significantly higher in males (p<0.05). Results of the present study provide reference values of orbital dimensions in Omani subjects. The prevalent orbital type of Omani subjects is mesoseme, which is a hallmark of the white race.

Keywords: orbit, orbital index, mesoseme, ethnicity, variation

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Authors: Parker Townes, Prabdeep Panesar, Chunlin Liu, Soo Youn Lee, Dan Devoe, Paul D. Arnold, Jennifer Crosbie, Russell Schachar

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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are impairing childhood neurodevelopmental disorders with problems in executive functions. Executive functions are higher-level mental processes essential for daily functioning and goal attainment. There is genetic and neural overlap between ADHD and ASD. The aim of this meta-analysis was to evaluate if pediatric ASD and ADHD have distinct executive function profiles. This review was completed following Cochrane guidelines. Fifty-eight articles were identified through database searching, followed by a blinded screening in duplicate. A meta-analysis was performed for all task performance metrics evaluated by at least two articles. Forty-five metrics from 24 individual tasks underwent analysis. No differences were found between youth with ASD and ADHD in any domain under direct comparison. However, individuals with ASD and ADHD exhibited deficient attention, flexibility, visuospatial abilities, working memory, processing speed, and response inhibition compared to controls. No deficits in planning were noted in either disorder. Only 11 studies included a group with comorbid ASD+ADHD, making it difficult to determine whether common executive function deficits are a function of comorbidity. Further research is needed to determine if comorbidity accounts for the apparent commonality in executive function between ASD and ADHD.

Keywords: autism spectrum disorder, ADHD, neurocognition, executive function, youth

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Authors: José de Jesús Rivero Oliva, Jesús Salomón Llanes, Manuel Perdomo Ojeda, Antonio Torres Valle

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Combinatorial explosion is a common problem to both predominant methods for solving fault trees: Minimal Cut Set (MCS) approach and Binary Decision Diagram (BDD). High memory consumption impedes the complete solution of very complex fault trees. Only approximated non-conservative solutions are possible in these cases using truncation or other simplification techniques. The paper proposes a method (CSolv+) for solving complex fault trees, without any possibility of combinatorial explosion. Each individual MCS is immediately discarded after its contribution to the basic events importance measures and the Top gate Upper Bound Probability (TUBP) has been accounted. An estimation of the Top gate Exact Probability (TEP) is also provided. Therefore, running in a computer cluster, CSolv+ will guarantee the complete solution of complex fault trees. It was successfully applied to 40 fault trees from the Aralia fault trees database, performing the evaluation of the top gate probability, the 1000 Significant MCSs (SMCS), and the Fussell-Vesely, RRW and RAW importance measures for all basic events. The high complexity fault tree nus9601 was solved with truncation probabilities from 10-²¹ to 10-²⁷ just to limit the execution time. The solution corresponding to 10-²⁷ evaluated 3.530.592.796 MCSs in 3 hours and 15 minutes.

Keywords: system reliability analysis, probabilistic risk assessment, fault tree analysis, basic events importance measures

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Authors: Boris Kolev, Matt Kokan, Mohammad Deriszadeh, Farshid Bateni

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Due to the increasing demand for real estate and the need for efficient land utilization in Greater Vancouver, developers have been increasingly considering the construction of high-rise structures with multiple below-grade parking. The temporary excavations required to allow for the construction of underground levels have recently reached up to 40 meters in depth. One of the challenges with deep excavations is the prediction of wall displacements and ground settlements due to their effect on the integrity of City utilities, infrastructure, and adjacent buildings. A large database of survey monitoring data has been collected for deep excavations in various soil conditions and shoring systems. The majority of the data collected is for tie-back anchors and shotcrete lagging systems. The data were categorized, analyzed and the results were evaluated to find a relationship between the most dominant parameters controlling the displacement, such as depth of excavation, soil properties, and the tie-back anchor loading and arrangement. For a select number of deep excavations, finite element modeling was considered for analyses. The lateral displacements from the simulation results were compared to the recorded survey monitoring data. The study concludes with a discussion and comparison of the available empirical and numerical modeling methodologies for evaluating lateral displacements in deep excavations.

Keywords: deep excavations, lateral displacements, numerical modeling, shoring walls, tieback anchors

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Authors: Adewole Tomiwa Adetunji, Francis Bayo Lewu, Richard Mundembe

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Plants require nitrogen (N) to support desired production levels. There is a need for better understanding of N transport mechanism in order to improve N assimilation by plant root. Nitrogen is available to plants in the form of nitrate or ammonium, which are transported into the cell with the aid of various transport proteins. Ammonium transporters (AMTs) play a role in the uptake of ammonium, the form in which N is preferentially absorbed by plants. Solanum tuberosum AMT1 (StAMT1) was amplified, sequenced and characterized using molecular biology and bioinformatics methods. Nucleotide database sequences were used to design 976 base pairs AMT1-specific primers which include forward primer 5’- GCCATCGCCGCCGCCGG-3’ and reverse primer 5’-GGGTCAGATCCATACCCGC-3’. These primers were used to amplify the Solanum tuberosum AMT1 internal regions. Nucleotide sequencing, alignment and phylogenetic analysis assigned StAMT1 to the AMT1 family due to the clade and high similarity it shared with other plant AMT1 genes. The deduced amino acid sequences showed that StAMT1 is 92%, 83% and 76% similar to Solanum lycopersicum LeAMT1.1, Lotus japonicus LjAMT1.1, and Solanum lycopersicum LeAMT1.2 respectively. StAMT1 fragments were shown to correspond to the 5th-10th trans-membrane domains. Residue StAMT1 D15 is predicted to be essential for ammonium transport, while mutations of StAMT1 S76A may further enhance ammonium transport.

Keywords: ammonium transporter, bioinformatics, nitrogen, primers, Solanum tuberosum

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Authors: N. J. Shanono, J. G. Ndiritu

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The poor performance of water resource systems (WRS) has been reportedly linked to not only climate variability and the water demand dynamics but also human behaviour-driven unlawful activities. Some of these unlawful activities that have been adversely affecting water sector include unauthorized water abstractions, water wastage behaviour, refusal of water re‐use measures, excessive operational losses, discharging untreated or improperly treated wastewater, over‐application of chemicals by agricultural users and fraudulent WRS operation. Despite advances in WRS planning, operation, and analysis incorporating such undesirable human activities to quantitatively assess their impact on WRS performance remain elusive. This study was then inspired by the need to develop a methodological framework for WRS performance assessment that integrates the impact of human behaviour with WRS performance assessment analysis. We, therefore, proposed a conceptual framework for assessing the impact of human behaviour on WRS performance using the concept of socio-hydrology. The framework identifies and couples four major sources of WRS-related values (water values, water systems, water managers, and water users) using three missing links between human and water in the management of WRS (interactions, outcomes, and feedbacks). The framework is to serve as a database for choosing relevant social and hydrological variables and to understand the intrinsic relations between the selected variables to study a specific human-water problem in the context of WRS management.

Keywords: conceptual framework, human behaviour; socio-hydrology; water resource systems

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Peri Harish Kumar, Sai Sharan Dwarka, Tajbinder Singh Bains, Suneet John Joseph, Chaitanya Kiran, Sambhu Dutta, Sarah Makram, Mohamed Sayed Zaazouee, Alaa Ahmed Elshanbary

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Objective: To identify cancer and non-cancer causes of death in hepatocellular carcinoma (HCC) patients over different time periods after diagnosis and to compare the mortality risk of each cause in HCC patients with the general population. Methods: In this retrospective cohort study, data of 67,637 HCC patients from 1975 to 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. We investigated the association between different causes of death and the following variables: age, race, tumor stage at diagnosis, and treatment (surgery, chemotherapy, and radiotherapy); each according to the periods of <1 year, 1-5 years, 5-10 years, and >10 years following the diagnosis. Standardized mortality ratios (SMRs) and their 95% confidence intervals (CIs) were calculated for cancer and non-cancer deaths in each of the mentioned periods following diagnosis. Results: Data of 67,637 patients, of whom 50,571 patients died during the follow-up period, were analyzed. Most deaths were due to HCC itself (35,535, 70.3%), followed by other cancers (3,983, 7.9%). Common causes of non-cancer mortality included infectious and parasitic diseases including HIV (2,823 patients, SMR=105.68, 95% CI: 101.82-109.65), chronic liver disease (2,719 patients, SMR=76.56, 95% CI: 73.71,79.5), and heart diseases (1,265 patients, SMR=2.26, 95% CI: 2.14-2.39), with higher mortality risk in HCC patients than in the general population. Conclusion: Cancers stand for most deaths in patients with HCC. Besides, infectious, and parasitic diseases including HIV represent the commonest non-cancer cause of mortality.

Keywords: hepatocellular carcinoma, seer, causes of death, mortality

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Authors: Pouyan Jahanbin, Mahmoud Houshmand, Omid Fatahi Valilai

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A flexible manufacturing system (FMS) is a manufacturing system having the capability of handling the variations of products features that is the result of ever-changing customer demands. The flexibility of the manufacturing systems help to utilize the resources in a more effective manner. However, the control of such systems would be complicated and challenging. FMS needs CNC machines and robots and other resources for establishing the flexibility and enhancing the efficiency of the whole system. Also it needs to integrate the resources to reach required efficiency and flexibility. In order to reach this goal, an integrator framework is proposed in which the machining data of CNC machine tools is received through a STEP-NC file. The interoperability of the system is achieved by the information system. This paper proposes an information system that its data model is designed based on object oriented approach and is implemented through a knowledge-based system. The framework is connected to a database which is filled with robot’s control commands. The framework programs the robots by rules embedded in its knowledge based system. It also controls the interactions of CNC machine tools for loading and unloading actions by robot. As a result, the proposed framework improves the integration of manufacturing resources in Flexible Manufacturing Systems.

Keywords: CNC machine tools, industrial robots, knowledge-based systems, manufacturing recourses integration, flexible manufacturing system (FMS), object-oriented data model

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Authors: Peter Yamoah, Frasia Oosthuizen

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Introduction: Reporting of Adverse Events Following Immunization continues to be a challenge. Pharmacovigilance centers throughout the world are mandated by the WHO to submit AEFI reports from various countries to a large pool of adverse drug reaction electronic database called Vigibase. Despite the relevant information of AEFI in Vigibase, it is unavailable to the general public. However, the WHO has an alternative website called VigiAccess which is an open access website serving as a repository of reported adverse drug reactions and AEFIs. The aim of the study was to ascertain the reporting pattern of a number of commonly used vaccines in VigiAccess. Methods: VigiAccess was thoroughly searched on the 5th of February 2018 for AEFI reports of measles vaccine, oral polio vaccine (OPV), yellow fever vaccine, pneumococcal vaccine, rotavirus vaccine, meningococcal vaccine, tetanus vaccine and tuberculosis (BCG) vaccine. These were reports from all pharmacovigilance centers in the world from the time they joined the WHO drug monitoring program. Results: After a thorough search in VigiAccess, there were 9,062 measles vaccine AEFIs, 185,829 OPV AEFIs, 24,577 yellow fever vaccine AEFIs, 317,208 pneumococcal vaccine AEFIs, 73,513 rotavirus vaccine AEFIs, 145,447 meningococcal vaccine AEFIs, 22,781 tetanus vaccine AEFIs and 35,556 BCG vaccine AEFIs. Conclusion: The study revealed that out of the eight vaccines studied, pneumococcal vaccines are associated with the highest number of AEFIs whilst measles vaccines were associated with the least AEFIs.

Keywords: vaccines, adverse reactions, VigiAccess, adverse event reporting

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Authors: Elena Carcano, James Ball

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This work details the strategies adopted by the Italian Water Utilities during the distribution of water in emergency conditions which glide from earthquakes and droughts to floods and fires. Several water bureaus located over the national territory have been interviewed, and the collected information has been used in a database of potential interventions to be taken. The work discusses the actions adopted by water utilities. These are generally prioritized in order to minimize the social, temporal, and economic burden that the damaged and nearby areas need to support. Actions are defined relying on the Bayesian Network Approach, which constitutes the hard core of any decision support system. The Bayesian Networks give answers to interventions to real and most likely risky cases. The added value of this research consists in supplying the National Bureau, namely Protezione Civile, in charge of managing havoc and catastrophic situations with a univocal plot outline so as to be able to handle actions uniformly at the expense of different local laws or contradictory customs which squander any recovery conditions, proper technical service, and economic aids. The paper is organized as follows: in section 1, the introduction is stated; section 2 provides a brief discussion of BNNs (Bayesian Networks), section 3 introduces the adopted methodology; and in the last sections, results are presented, and conclusions are drawn.

Keywords: hierarchical process, strategic plan, water emergency conditions, water supply

Procedia PDF Downloads 160