Search results for: image validation

Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Najia Zulfiqar

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Imparting moral education is the need of time, considering the obvious moral decline in society. Recent research shows the downfall of moral competence among university students. The main objective of the present study was to develop moral development intervention strategies for undergraduate students of Sports and Physical Education. Using an interpretative phenomenological approach, insight into field-specific moral issues was gained through interviews with 7 subject experts and a focus-group discussion session with 8 students. Two research assistants who were trained in qualitative interviewing collected, transcribed and analyzed data into the MAXQDA software using content and discourse analyses. The identified moral issues in Sports and Physical Education were sports gambling and betting, pay-for-play, doping, coach misconduct, tampering, cultural bias, gender equity/nepotism, bullying/discrimination, and harassment. Next, intervention modules were developed for each moral issue based on hypothetical situations, and followed by guided reflection and dilemma discussion questions. The third moral development strategy was community services that included posture screening, diet plan for different age groups, open fitness ground training, exercise camps for physical fitness, balanced diet awareness camp, gymnastic camp, shoe assessment as per health standards, and volunteering for public awareness at the playground, gymnasium, stadium, park, etc. The intervention modules were given to four subject specialists for expert validation who were from different backgrounds within Sport Sciences. Upon refinement and finalization, four students were presented with these intervention modules and questioned about accuracy, relevance, comprehension, and content organization. Iterative changes were made in the content of the intervention modules to tailor them to the moral development needs of undergraduate students. This intervention will strengthen positive moral values and foster mature decision-making about right and wrong acts. As this intervention is easy to apply as a remedial tool, academicians and policymakers can use this to promote students’ moral development.

Keywords: community service, dilemma discussion, morality, physical education, university students.

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Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

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Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

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Authors: Ekaterina Razuvalova, Konstantin Rudenko

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In this article the most successful examples of international visual and virtual reconstructions of historical and culture objects, which are based on informative and communicative technologies, are represented. 3D reconstructions can demonstrate outward appearance, visualize different hypothesis, connected to represented object. Virtual reality can give us any daytime and season, any century and environment. We can see how different people from different countries and different era lived; we can get different information about any object; we can see historical complexes in real city environment, which are damaged or vanished. These innovations confirm the fact, that 3D reconstruction is important in museum development. Considering the most interesting examples of visual and virtual reconstructions, we can notice, that visual reconstruction is a 3D image of different objects, historical complexes, buildings and phenomena. They are constant and we can see them only as momentary objects. And virtual reconstruction is some environment with its own time, rules and phenomena. These reconstructions are continuous; seasons, daytime and natural conditions can change there. They can demonstrate abilities of virtual world existence. In conclusion: new technologies give us opportunities to expand the boundaries of museum space, improve abilities of museum expositions, create emotional atmosphere of game immersion, which can interest visitor. Usage of network sources allows increasing the number of visitors and virtual reconstruction opportunities show creative side of museum business.

Keywords: computer technologies, historical reconstruction, museums, museum expositions, virtual reconstruction

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Authors: Dana Hisham Mohamed Abdrabo

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The paper examines the effect of Drama works on the Egyptian public opinion regarding the religion of Judaism, Israel as a state and the Jew's image to Egyptian Muslims. The paper examines the role of Media and in particular, Dramas on achieving interreligious dialogue between Judaism and Islam and its role in making peace between the Egyptian Muslims -and Arabs in general- on the one hand, and the Jew on the other hand, and the implications of this on the relationship between Arab countries and Israel as a state. The research uses the Survey method with Egyptian Muslims as a main sample for the research to examine such effect. Dramas have a role in presenting the Jew, Judaism, and Israel as a state and as a political system in various ways. The paper is related to multidisciplinary fields; it is related to political sciences, political sociology, communication, social change, and cognitive sociology fields. The research adds a new analytical study for a new tool for the peacemaking process in the Middle East region through adopting an interdisciplinary approach which is needed in the studies aim to achieve stability and peace in the Middle East region and its neighboring countries.

Keywords: dramas tool, Egyptian public opinion, interreligious dialogue, Israel & Egyptian relations , Judaism

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Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

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Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

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Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: Richa Dhingra, Monika, Manav Malhotra, Tilak Raj Bhardwaj, Neelima Dhingra

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5-Alpha-reductases (5AR), a membrane bound, NADPH dependent enzyme and convert male hormone testosterone (T) into more potent androgen dihydrotestosterone (DHT). DHT is the required for the development and function of male sex organs, but its overproduction has been found to be associated with physiological conditions like Benign Prostatic Hyperplasia (BPH). Thus the inhibition of 5ARs could be a key target for the treatment of BPH. In present study, 2D and 3D Quantitative Structure Activity Relationship (QSAR) pharmacophore models have been generated for 5AR based on known inhibitory concentration (IC₅₀) values with extensive validations. The four featured 2D pharmacophore based PLS model correlated the topological interactions (–OH group connected with one single bond) (SsOHE-index); semi-empirical (Quadrupole2) and physicochemical descriptors (Mol. wt, Bromines Count, Chlorines Count) with 5AR inhibitory activity, and has the highest correlation coefficient (r² = 0.98, q² =0.84; F = 57.87, pred r² = 0.88). Internal and external validation was carried out using test and proposed set of compounds. The contribution plot of electrostatic field effects and steric interactions generated by 3D-QSAR showed interesting results in terms of internal and external predictability. The well validated 2D Partial Least Squares (PLS) and 3D k-nearest neighbour (kNN) models were used to search novel 5AR inhibitors with different chemical scaffold. To gain more insights into the molecular mechanism of action of these steroidal derivatives, molecular docking and in silico absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Studies have revealed the hydrophobic and hydrogen bonding of the ligand with residues Alanine (ALA) 63A, Threonine (THR) 60A, and Arginine (ARG) 456A of 4AT0 protein at the hinge region. The results of QSAR, molecular docking, in silico ADME studies provide guideline and mechanistic scope for the identification of more potent 5-Alpha-reductase inhibitors (5ARI).

Keywords: 5α-reductase inhibitor, benign prostatic hyperplasia, ligands, molecular docking, QSAR

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Authors: Archana Gandhi

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Indian apparel manufacturers see several benefits of Corporate Social Responsibility (CSR). At the same time, they clearly face steep challenges in its implementation. From the perspective of the participants, the challenges tend to outweigh the benefits. The short-term expenses, misperceptions about the financial benefits of CSR and the additional burden of implementing CSR-related policies and activities tend to overshadow perceptions of the long-term benefits. CSR activities currently seen in the Indian apparel industry are primarily people focused, society-focused or environment-focused. However, most CSR activities focus on employee welfare, including teaching employees about health and safety awareness, creating opportunities for community building, and providing general education to employees. Employee retention is very high in socially responsible Indian firms as compared to non-CSR firms, largely because CSR plays a crucial role in overall employee satisfaction, which translates to worker loyalty and low turnover. Employee retention and commitment are not the​ only potential benefits of CSR in the Indian apparel industry. CSR can also enhance a company’s image. Although it is a long-term benefit, being socially responsible can build a company’s social reputation and help it to gain others’ trust. Buyers do not hesitate to do business with these companies, since it is difficult to find socially responsible firms in India.

Keywords: corporate social responsibility, apparel industry, workers, improve work life

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: Dijana Sulejmanović

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Cognitive-behavioral modification (CBM) is a combination of cognitive and behavioral learning principles to shape and encourage the desired behaviors. A crucial element of cognitive-behavioral modification is that a change the behavior precedes awareness of how it affects others. CBM is oriented toward changing inner speech and learning to control behaviors through self-regulation techniques. It aims to teach individuals how to develop the ability to recognize, monitor and modify their thoughts, feelings, and behaviors. The review of literature emphasizes the efficiency the CBM approach in the treatment of children's hyperactivity and negative emotions such as anger. The results of earlier research show how impulsive and hyperactive behavior, agitation, and aggression may slow down and block the child from being able to actively monitor and participate in regular classes, resulting in the disruption of the classroom and the teaching process, and the children may feel rejected, isolated and develop long-term poor image of themselves and others. In this article, we will provide how the use of CBM, adapted to child's age, can incorporate measures of cognitive and emotional functioning which can help us to better understand the children’s cognitive processes, their cognitive strengths, and weaknesses, and to identify factors that may influence their behavioral and emotional regulation. Such a comprehensive evaluation can also help identify cognitive and emotional risk factors associated with aggressive behavior, specifically the processes involved in modulating and regulating cognition and emotions.

Keywords: aggressive behavior, cognitive behavioral modification, cognitive behavioral theory, modification

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Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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Authors: Sunghun Jung

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The existing web map service providers contract with the satellite operators to update their maps by paying an astronomical amount of money, but the cost could be minimized by operating a cheap and small UAV. In contrast to the satellites, we only need to replace aged battery packs from time to time for the usage of UAVs. Utilizing both a regular camera and an infrared camera mounted on a small, solar-powered, long-endurance, and hoverable UAV, daytime ground surface photographs, and nighttime infrared photographs will be continuously and repeatedly uploaded to the web map server and overlapped with the existing ground surface photographs in real-time. The real-time web map service using a small, solar-powered, long-endurance, and hoverable UAV can also be applied to the surveillance missions, in particular, to detect border area intruders. The improved real-time image stitching algorithm is developed for the graphic map data overlapping. Also, a small home server will be developed to manage the huge size of incoming map data. The map photographs taken at tens or hundreds of kilometers by a UAV would improve the map graphic resolution compared to the map photographs taken at thousands of kilometers by satellites since the satellite photographs are limited by weather conditions.

Keywords: long-endurance, real-time web map service (RWMS), solar-powered, unmanned aerial vehicle (UAV)

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Authors: Maria Jose Ramos Villagra

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Since the boom of tourism in the late 80s and 90s, Costa Rica is considered as one of the leading countries for tourism. The size and geography of its territory, its low population density, and its image of being one of the most stable Latin American democracies make Costa Rica an attractive and safe target for foreign investors. Land ownership by foreign investors has increased as the natural resources in rural communities have been exhausted. When nature becomes an instrument to increase profit, it loses its communal value contributing to local communities losing their sovereignty and access to basic resources. The rural regions in proximity to the most tourist areas are often the most marginalized. The purpose of this research is to use the case of the rural community Sardinal and its struggle to protect its aquifer to investigate the economic and cultural consequences of the tourism boom in Costa Rican rural communities. The process of reclaiming the access to and the preservation of the aquifer enabled individuals to redefine their political views and their political power. The case of Sardinal broke the stereotypes about rural individuals and their ability to politically educate themselves and organize. Sardinal´s conflict brought to light the necessity of questioning the role of modern tourism as part of Costa Rica’s national identity, and as a tool for development

Keywords: Costa Rica, tourism, rural development, economy, ecotourism, environment, water, Sardinal

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Authors: Jayanth C., Anirudh Sai Yetikuri, Kavitha S. N.

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This paper explores the development and application of computer vision and machine learning techniques for real-time pose detection, facial recognition, and number plate extraction. Utilizing MediaPipe for pose estimation, the research presents methods for detecting hand raises and ducking postures through real-time video analysis. Complementarily, facial recognition is employed to compare and verify individual identities using the face recognition library. Additionally, the paper demonstrates a robust approach for extracting and storing vehicle number plates from images, integrating Optical Character Recognition (OCR) with a database management system. The study highlights the effectiveness and versatility of these technologies in practical scenarios, including security and surveillance applications. The findings underscore the potential of combining computer vision techniques to address diverse challenges and enhance automated systems for both individual and vehicular identification. This research contributes to the fields of computer vision and machine learning by providing scalable solutions and demonstrating their applicability in real-world contexts.

Keywords: computer vision, pose detection, facial recognition, number plate extraction, machine learning, real-time analysis, OCR, database management

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Authors: Ismail Celik, Pavlo Antonenko, Seyit Ahmet Kiray, Ismail Sahin

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The aim of the present study was to thoroughly investigate the teachers’ interactive whiteboards (IWBs) use within the scope of the technological pedagogical and content knowledge (TPACK) framework based on the school practice observations of in-service teachers collected by pre-service teachers. In this study, teachers’ use of IWBs in their classes was investigated by using phenomenography, which is a qualitative research method design. The participants of this study consisted of teachers working in a province of Turkey. Within the scope of the study, 337 teachers from 61 different schools were observed by preservice teachers during School Experience classes. The teachers use the IWBs to review the points not understood by the students, to share knowledge, to enhance motivation, to maintain student participation/practice and for in-process, formative assessment. The problems teachers face while using the IWBs can be IWB-based (touchscreen problems/frozen image/lack of software), administration-based, student-based and teacher-based (lack of knowledge of use, need for technical support). It is considered that technological knowledge (TK) is important in solving the problems experienced with IWBs, and technological pedagogy knowledge (TPK) and technological content knowledge (TCK) are important in using the IWBs in an interactive and pedagogically meaningful way that uses IWBs affordances and is relevant to the instructional objectives.

Keywords: TPACK, technology integration, interactive whiteboard, technology in education

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Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: automatic detection, defects, fracture lines, wavelets

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Authors: Jesryl B. Paulite, Irene Alcantara-Papa, Teofila O. Zulaybar, Jocelyn T. Zarate, Virgie Ugay

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Banana is one of the major fruits in the Philippines in terms of volume of production and export earnings. The Philippines export of fresh Cavendish banana ranked No.1 with 22% share. One major threat to the industry is Fusarium wilt caused by Fusarium oxysporum f. sp. cubense. It tops as a major concern today affecting the Philippine banana industry since 2002 up to the present in Mindanao. Because of environmental and health issues concerning the use of chemical pesticides in the control of diseases, utilization of microorganisms has been significant in recent years as a promising alternative. This study aims to evaluate the potential of actinomycetes to control Fusarium wilt in Cavendish banana. The in-vitro experiments was carried out in Complete Randomized Design (CRD) while field experiment was laid out in a Randomized Complete Block Design (RCBD) with three treatments and three replications. Actinomycetes were isolated from mangrove soils in areas in Quezon and Bataan, Philippines. A total of 199 actinomycetes were isolated and 82 actinomycetes showed activity against the local Fusarium oxysporum (Foc) by agar plug assay. The test for antagonisms (AQ6, AQ30, and AQ121) of three best isolates Foc to were selected inhibiting Foc by 21.0mm, 22.0mm and 20.5mm, respectively. The same actinomycetes inhibited well Foc Tropical Race 4 showing 24.6 mm, 20.2mm and 19.0 mm zones of inhibition by agar plug assay, respectively. Combinations of the three isolates yielded an inhibition of 13.5 mm by cup cylinder assay. These findings led to the formulation of the mixed actinomycetes as biocontrol agents against Foc. A field experiment to evaluate the formulated mixed actinomycetes against Foc in a Foc infested field in Kinamayan, Sto Tomas, Davao Del Norte, Philippines. was conducted. Results showed that preventive method of application of the mixed actinomycetes against Foc showed promising results. A 56.66% mortality was observed in control set-up (no biocontrol agent added) compared to 33.33% mortality in preventive method. Further validation of the effectiveness of the mixed actinomycetes as biocontrol agent is presently being conducted in Asuncion, Davao Del Norte, Philippines.

Keywords: actinomycetes, biocontrol agents, cavendish banana, Fusarium oxysporum f. sp. cubense

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Authors: Olusola Omolola Olafuyi, Michael Coleman, Raj Kumar Singh Badhan

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Introduction: Malaria in pregnancy has morbidity and mortality implication on both mother and unborn child. Piperaquine (PQ) based antimalarial treatment is emerging as a choice antimalarial for pregnant women in the face of resistance to current antimalarial treatment recommendation in pregnancy. Physiological and biochemical changes in pregnant women may affect the pharmacokinetics of the antimalarial drug in these. In malaria endemic regions other infectious diseases like HIV/AIDs are prevalent. Pregnant women who are co-infected with malaria and HIV/AID are at even more greater risk of death not only due to complications of the diseases but also due to drug-drug interactions (DDIs) between antimalarials (AMT) and antiretroviral (ARVs). In this study, physiologically based pharmacokinetic (PBPK) modelling was used to investigate the effect of physiological and biochemical changes on the impact of ARV mediated DDIs in pregnant women in three countries. Method: A PBPK model for PQ was developed on SimCYP® using published physicochemical and pharmacokinetic data of PQ from literature, this was validated in three customized population groups from Thailand, Sudan and Papua New Guinea with clinical data. Validation of PQ model was also done in presence of interaction with efavirenz (pre-validated on SimCYP®). Different albumin levels and pregnancy stages was simulated in the presence of interaction with standard doses of efavirenz and ritonavir. PQ day 7 concentration of 30ng/ml was used as the efficacy endpoint for PQ treatment.. Results: The median day 7 concentration of PQ remained virtually consistent throughout pregnancy and were satisfactory across the three population groups ranging from 26-34.1ng/ml; this implied the efficacy of PQ throughout pregnancy. DDI interaction with ritonavir and efavirenz resulted in modest effect on the day 7 concentrations of PQ with AUCratio ranging from 0.56-0.8 and 1.64-1.79 for efavirenz and ritonavir respectively over 10-40 gestational weeks, however, a reduction in human serum albumin level reflective of severe malaria resulted in significantly reduced the number of subjects attaining the PQ day 7 concentration in the presence of both DDIs. The model demonstrated that the DDI between PQ and ARV in pregnant women with different malaria severities can alter the pharmacokinetic of PQ.

Keywords: antiretroviral, malaria, piperaquine, pregnancy, physiologically-based pharmacokinetics

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Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy

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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared together

Keywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network

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Authors: Irina Alexandra Paun, Mona Mihailescu, Marian Zamfirescu, Catalin Romeo Luculescu, Adriana Maria Acasandrei, Cosmin Catalin Mustaciosu, Roxana Cristina Popescu, Maria Dinescu

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A major concern in bone tissue engineering is to develop complex 3D architectures that mimic the natural cells environment, facilitate the cells growth in a defined manner and allow the flow transport of nutrients and metabolic waste. In particular, porous structures of controlled pore size and positioning are indispensable for growing human-like bone structures. Another concern is to monitor both the structures and the seeded cells with high spatial resolution and without interfering with the cells natural environment. The present approach relies on laser-based technologies employed for fabricating porous biomimetic structures that support the growth of osteoblast-like cells and for their non-invasive 3D imaging. Specifically, the porous structures were built by two photon polymerization –direct writing (2PP_DW) of the commercially available photoresists IL-L780, using the Photonic Professional 3D lithography system. The structures consist of vertical tubes with micrometer-sized heights and diameters, in a honeycomb-like spatial arrangement. These were fabricated by irradiating the IP-L780 photoresist with focused laser pulses with wavelength centered at 780 nm, 120 fs pulse duration and 80 MHz repetition rate. The samples were precisely scanned in 3D by piezo stages. The coarse positioning was done by XY motorized stages. The scanning path was programmed through a writing language (GWL) script developed by Nanoscribe. Following laser irradiation, the unexposed regions of the photoresist were washed out by immersing the samples in the Propylene Glycol Monomethyl Ether Acetate (PGMEA). The porous structures were seeded with osteoblast like MG-63 cells and their osteogenic potential was tested in vitro. The cell-seeded structures were analyzed in 3D using the digital holographic microscopy technique (DHM). DHM is a marker free and high spatial resolution imaging tool, where the hologram acquisition is performed non-invasively i.e. without interfering with the cells natural environment. Following hologram recording, a digital algorithm provided a 3D image of the sample, as well as information about its refractive index, which is correlated with the intracellular content. The axial resolution of the images went down to the nanoscale, while the temporal scales ranged from milliseconds up to hours. The hologram did not involve sample scanning and the whole image was available in one frame recorded going over 200μm field of view. The digital holograms processing provided 3D quantitative information on the porous structures and allowed a quantitative analysis of the cellular response in respect to the porous architectures. The cellular shape and dimensions were found to be influenced by the underlying micro relief. Furthermore, the intracellular content gave evidence on the beneficial role of the porous structures in promoting osteoblast differentiation. In all, the proposed laser-based protocol emerges as a promising tool for the fabrication and non-invasive imaging of porous constructs for bone tissue engineering. Acknowledgments: This work was supported by a grant of the Romanian Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project PN-II-RU-TE-2014-4-2534 (contract 97 from 01/10/2015) and by UEFISCDI PN-II-PT-PCCA no. 6/2012. A part of this work was performed in the CETAL laser facility, supported by the National Program PN 16 47 - LAPLAS IV.

Keywords: biomimetic, holography, laser, osteoblast, two photon polymerization

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Authors: Shantanu Vyas, Neerja Meena

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Facial infiltrating lipomatosis is a rare lipomatous lesion, first described by Slavin in 1983. It is a benign pseudotumor pathology. It corresponds to a non-encapsulated collection of mature adipocytes infiltrating the local tissue and hyperplasia of underlying bone leading to a craniofacial deformity. Very few cases have been reported in the literature. We report the case of a 19-year-old female patient, who was consulted for a swelling of the right hemiface progressively evolving since birth. Physical examination revealed facial asymmetry. On palpation, the mass was soft, painless, not compressible, not pulsatile, not fluctuating. In view of the asymptomatic nature and slow progression of the lesion, a lipomatous tumour, namely lipoma, was suggested. CT scan image shows a hyperplastic subcutaneous fat on the right hemiface. On the right jugal and temporal areas, there is a subcutaneous formation of fatty density, poorly limited, with no detectable peripheral capsule. It merges with the adjacent fat. In the bone window, there was a hyperplasia of underlying bone. Facial lipomatosis infiltration of the face is a benign pseudotumor pathology. As a result, it can be confused with other disorders, in particular, hemifacial hyperplasia. Combination of physical and radiological findings can establish the diagnosis. Surgical treatment is done for cosmetic purposes.

Keywords: cosmetic correction and facial assemetry, aesthetic results, facial infiltration, surgery

Procedia PDF Downloads 74

Authors: Hamd Ahmed

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During the Persian Gulf War in 1991s, The confederation forces were surprised when they were being shot at by friendly forces in Iraqi desert. As obvious was the fact that they were mislead due to the lack of proper guidance and technology resulting in unnecessary loss of life and bloodshed. This unforeseen incident along with many others led the US department of defense to open the doors of GPS. In the very beginning, this technology was for military use, but now it is being widely used and increasingly popular among the public due to its high accuracy and immeasurable significance. The GPS system simply consists of three segments, the space segment (the satellite), the control segment (ground control) and the user segment (receiver). This project work is about designing a 1.57GHZ mixer for triple conversion GPS receiver .The GPS Front-End receiver based on super heterodyne receiver which improves selectivity and image frequency. However the main principle of the super heterodyne receiver depends on the mixer. Many different types of mixers (single balanced mixer, Single Ended mixer, Double balanced mixer) can be used with GPS receiver, it depends on the required specifications. This research project will provide an overview of the GPS system and details about the basic architecture of the GPS receiver. The basic emphasis of this report in on investigating general concept of the mixer circuit some terms related to the mixer along with their definitions and present the types of mixer, then gives some advantages of using singly balanced mixer and its application. The focus of this report is on how to design mixer for GPS receiver and discussing the simulation results.

Keywords: GPS , RF filter, heterodyne, mixer

Procedia PDF Downloads 322

Authors: K. T. Sun, Y. H. Tai, H. W. Yang, H. T. Lin

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This paper presented the technique of robot control by event-related potentials (ERPs) of brain waves. Based on the proposed technique, severe physical disabilities can free browse outside world. A specific component of ERPs, N2P3, was found and used to control the movement of robot and the view of camera on the designed brain-computer interface (BCI). Users only required watching the stimuli of attended button on the BCI, the evoked potentials of brain waves of the target button, N2P3, had the greatest amplitude among all control buttons. An experimental scene had been constructed that the robot required walking to a specific position and move the view of camera to see the instruction of the mission, and then completed the task. Twelve volunteers participated in this experiment, and experimental results showed that the correct rate of BCI control achieved 80% and the average of execution time was 353 seconds for completing the mission. Four main contributions included in this research: (1) find an efficient component of ERPs, N2P3, for BCI control, (2) embed robot's viewpoint image into user interface for robot control, (3) design an experimental scene and conduct the experiment, and (4) evaluate the performance of the proposed system for assessing the practicability.

Keywords: severe physical disabilities, robot control, event-related potentials (ERPs), brain-computer interface (BCI), brain waves

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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Authors: Dian Nur Amalia, Rifqi Dhiemas Aji, Tri Septa Wahyuningsih, Endang Wahyuni

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Kepel fruit (Stelechocarpus burahol) is a scarce fruit that belongs as a logogram of Daerah Istimewa Yogyakarta. Kepel fruit can be used as substance of beauty treatment product, such as deodorant and good for skin health, and also contains antioxidant compound. Otherwise, this fruit is scarcely cultivated by people because of its image as a palace fruit and also the flesh percentage just a little, so it has low economic value. The flesh of kepel fruit is about 49% of its whole fruit. This little part as supporting point why kepel fruit has to be extracted and processed with the other product. Yoghurt is milk processing product that also have a role as functional food. Economically, the price of yoghurt is higher than whole milk or other milk processing product. Yoghurt is usually added with flavor of dye from plant or from chemical substance. Kepel fruit has a role as flavor in yoghurt, besides as product that good for digestion, yoghurt with kepel also has function as “beauty” food. Writing method that used is literature study by looking for the potential of kepel fruit as a local fruit of Yogyakarta and yoghurt as milk processing product. The process just like making common yoghurt because kepel fruit just have a role as flavor substance, so it does not affect to the other processing of yoghurt. Food diversification can be done as an effort to increase the value of local resources that proper to compete in Asean Economic Community (AEC), one of the way is producing kepel yoghurt.

Keywords: kepel, yoghurt, Daerah Istimewa Yogyakarta, functional food

Procedia PDF Downloads 317