Search results for: comprehensive feature extraction

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

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Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Samaneh Poormohammadi, Farid Golkar, Vahideh Khatibi Sarabi

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Climate change and consecutive droughts have increased the importance of using rainwater harvesting methods. One of the methods of rainwater harvesting and, in other words, the management of atmospheric water resources is the use of weather modification technologies. Weather modification (also known as weather control) is the act of intentionally manipulating or altering the weather. The most common form of weather modification is cloud seeding, which increases rain or snow, usually for the purpose of increasing the local water supply. Cloud seeding operations in Iran have been married since 1999 in central Iran with the aim of harvesting rainwater and reducing the effects of drought. In this research, we analyze the results of cloud seeding operations in the Simindashtplain in northern Iran. Rainwater harvesting with the help of cloud seeding technology has been evaluated through its effects on surface water and underground water. For this purpose, two different methods have been used to estimate runoff. The first method is the US Soil Conservation Service (SCS) curve number method. Another method, known as the reasoning method, has also been used. In order to determine the infiltration rate of underground water, the balance reports of the comprehensive water plan of the country have been used. In this regard, the study areas located in the target area of each province have been extracted by drawing maps of the influence coefficients of each area in the GIS software. It should be mentioned that the infiltration coefficients were taken from the balance sheet reports of the country's comprehensive water plan. Then, based on the area of each study area, the weighted average of the infiltration coefficient of the study areas located in the target area of each province is considered as the infiltration coefficient of that province. Results show that the amount of water extracted from the rain with the help of cloud seeding projects in Simindasht is as follows: an increase in runoff 63.9 million cubic meters (with SCS equation) or 51.2 million cubic meters (with logical equation) and an increase in ground water resources: 40.5 million cubic meters.

Keywords: rainwater harvesting, ground water, atmospheric water resources, weather modification, cloud seeding

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Authors: Angelo Thurairajah

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Sufficient ultimate deformation is necessary to demonstrate the member ductility, which is dependent on the section and the material ductility. The concrete cracking phase of softening prior to the plastic hinge formation is an essential feature as well. The nature of the overload behaviour is studied using the order of the ultimate deflection. The ultimate deflection is primarily dependent on the slenderness (span to depth ratio), the ductility of the reinforcing steel, the degree of moment redistribution, the type of loading, and the support conditions. The ultimate deflection and the degree of moment redistribution from the analytical study are in good agreement with the experimental results and the moment redistribution provisions of the Australian Standards AS3600 Concrete Structures Code.

Keywords: ductility, softening, ultimate deflection, overload behaviour, moment redistribution

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Authors: Hung-Yuan Chang, Wen-Lung Chiang, Kuo-Liang Wu, Chen-Tsung Lin

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National Space Organization (NSPO) has completed in 2014 the development of a space-borne GPS receiver, including design, manufacture, comprehensive functional test, environmental qualification test and so on. The main performance of this receiver include 8-meter positioning accuracy, 0.05 m/sec speed-accuracy, the longest 90 seconds of cold start time, and up to 15g high dynamic scenario. The receiver will be integrated in the autonomous FORMOSAT-7 NSPO-Built satellite scheduled to be launched in 2019 to execute pre-defined scientific missions. The flight model of this receiver manufactured in early 2015 will pass comprehensive functional tests and environmental acceptance tests, etc., which are expected to be completed by the end of 2015. The space-borne GPS receiver is a pure software design in which all GPS baseband signal processing are executed by a digital signal processor (DSP), currently only 50% of its throughput being used. In response to the booming global navigation satellite systems, NSPO will gradually expand this receiver to become a multi-mode, multi-band, high-precision navigation receiver, and even a science payload, such as the reflectometry receiver of a global navigation satellite system. The fundamental purpose of this extension study is to port some software algorithms such as signal acquisition and correlation, reused code and large amount of computation load to the FPGA whose processor is responsible for operational control, navigation solution, and orbit propagation and so on. Due to the development and evolution of the FPGA is pretty fast, the new system architecture upgraded via an FPGA should be able to achieve the goal of being a multi-mode, multi-band high-precision navigation receiver, or scientific receiver. Finally, the results of tests show that the new system architecture not only retains the original overall performance, but also sets aside more resources available for future expansion possibility. This paper will explain the detailed DSP/FPGA architecture, development, test results, and the goals of next development stage of this receiver.

Keywords: space-borne, GPS receiver, DSP, FPGA, multi-mode multi-band

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Authors: Cristian Chacha, David Asiain, Jesús Ponce de León, José Ramón Beltrán

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This work explores and characterizes the behavior of the AFE AD5941 in impedance measurement using an embedded algorithm with a constant current AC source. The main aim of this research is to improve the exact measurement of impedance values for their application in EDA-focused wearable devices. Through comprehensive study and characterization, it has been observed that employing a measurement sequence with a constant current source produces results with increased dispersion but higher accuracy. As a result, this approach leads to a more accurate system for impedance measurement.

Keywords: EDA, constant current AC source, wearable, precision, accuracy, impedance

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Authors: Dinka Fikadu, Mulugeta Shegaze

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Background: Currently in health facility, provider-initiated human immunodeficiency virus testing is the key entry point to prevention, care, treatment and support services, but most people remains unaware of their HIV status due to various reasons. In many high-prevalence countries, fewer than one in ten people with HIV are aware of their HIV status. HIV, the virus that causes AIDS, “acquired immunodeficiency syndrome, "has become one of the world’s most serious health and development challenges. Reaching individuals with HIV who do not know their serostatus is a global public health priority. Objective: To assess utilization of provider initiated HIV testing and counseling and associated factors among adult outpatient department patients. Methods: Health facility based cross sectional study was conducted among 392 adult outpatient department patients in Wonchi woreda from February 24 to March 24 /2013. The study participant was recruited patients from all adult outpatient department patients of all four public health facilities of wonchi woreda using systematic sampling. A structured interviewer administered questionnaire was used to elicit all important variables from the study participants and multiple logistic regression analysis was used. Result: A total of 371 adult outpatient department patients aged between 15 to 64 years were actively participated in the study and 291(78.4%) of them utilized provider initiated HIV testing and counseling and 80(21.6%) of them refused. Knowledge on HIV is low in the study population; majority of the participants didn’t have comprehensive knowledge (64.7%) and (35.3%) fail to reject misconception about means of HIV transmission and prevention. Utilization of provider-initiated HIV testing and counseling were associated with divorced/widowed marital status[AOR (95%CI) = 0.32(0.15, 0.69)], being male sex [AOR (95%CI) =1.81(1.01, 3.24)], having comprehensive knowledge on HIV [AOR (95%CI) =0.408(0.220,0.759)],having awareness about provider initiated HIV testing and counseling [AOR(95%CI) =2.89(1.48,5.66)] and receiving test on HIV before[AOR (95%CI)=4.15(2.30, 7.47)]. Conclusion: Utilization of provider initiated HIV testing and counseling among adult outpatient departments in wonchi woreda public health facility was [(78.4%)].Strengthening health information through mass media and peer education on HIV to address barrier to testing in the community such as low awareness on PITC, to increase up take of PITC among adult OPD patients.

Keywords: utilization, human immune deficiency, testing, provider, initiate

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Authors: Honggang Qu, Rongmei Liu, Bin Wang, Yong Xu, Zhenji Gao

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There is a big gap in the ability and level of the informatization technology innovation of cores and samples compared with developed countries. Under the current background of promoting the technology innovation, how to strengthen the informatization technology innovation of cores and samples for National Cores and Samples Archives, which is a national innovation research center, is an important research topic. The paper summarizes the development status of cores and samples informatization technology, and finds the gaps and deficiencies, and proposes the innovation research directions and content, including data extraction, recognition, processing, integration, application and so on, so as to provide some reference and guidance for the future innovation research of the archives and support better the geological technology innovation in China.

Keywords: cores and samples;, informatization technology;, innovation;, suggestion

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Authors: Joyce Chieh Hsin Lo

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In the forthcoming paper, we aim to comprehensively investigate the relation between floor movement and the health condition. We embark on an extensive exploration of the innovative Movement Flow system, a contemporary paradigm that is reshaping the landscape of physical fitness and well-being. Our primary aim is to dissect the profound potential of this groundbreaking approach, not only as a means to enhance our physical fitness but also as a transformative tool for nurturing mental health. Within the scope of this comprehensive analysis, we will delve into the multifaceted aspects of Movement Flow, highlighting its versatility and adaptability to various individuals' needs and objectives.

Keywords: prehab, floor movement, proprioception, movement flow

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Authors: Fatima Mokeddem

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The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Camille Perréard, Yoann Ladner, Fanny D'Orlyé, Stéphanie Descroix, Vélan Taniga, Anne Varenne, Cédric Guyon, Michael. Tatoulian, Frédéric Kanoufi, Cyrine Slim, Sophie Griveau, Fethi Bedioui

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The development of micro total analysis systems is of major interest for contaminant and biomarker analysis. As a lab-on-chip integrates all steps of an analysis procedure in a single device, analysis can be performed in an automated format with reduced time and cost, while maintaining performances comparable to those of conventional chromatographic systems. Moreover, these miniaturized systems are either compatible with field work or glovebox manipulations. This work is aimed at developing an analytical microsystem for trace and ultra trace quantitation in complex matrices. The strategy consists in the integration of a sample pretreatment step within the lab-on-chip by a confinement zone where selective ligands are immobilized for target extraction and preconcentration. Aptamers were chosen as selective ligands, because of their high affinity for all types of targets (from small ions to viruses and cells) and their ease of synthesis and functionalization. This integrated target extraction and concentration step will be followed in the microdevice by an electrokinetic separation step and an on-line detection. Polymers consisting of cyclic olefin copolymer (COC) or fluoropolymer (Dyneon THV) were selected as they are easy to mold, transparent in UV-visible and have high resistance towards solvents and extreme pH conditions. However, because of their low chemical reactivity, surface treatments are necessary. For the design of this miniaturized diagnostics, we aimed at modifying the microfluidic system at two scales : (1) on the entire surface of the microsystem to control the surface hydrophobicity (so as to avoid any sample wall adsorption) and the fluid flows during electrokinetic separation, or (2) locally so as to immobilize selective ligands (aptamers) on restricted areas for target extraction and preconcentration. We developed different novel strategies for the surface functionalization of COC and Dyneon, based on plasma, chemical and /or electrochemical approaches. In a first approach, a plasma-induced immobilization of brominated derivatives was performed on the entire surface. Further substitution of the bromine by an azide functional group led to covalent immobilization of ligands through “click” chemistry reaction between azides and terminal alkynes. COC and Dyneon materials were characterized at each step of the surface functionalization procedure by various complementary techniques to evaluate the quality and homogeneity of the functionalization (contact angle, XPS, ATR). With the objective of local (micrometric scale) aptamer immobilization, we developed an original electrochemical strategy on engraved Dyneon THV microchannel. Through local electrochemical carbonization followed by adsorption of azide-bearing diazonium moieties and covalent linkage of alkyne-bearing aptamers through click chemistry reaction, typical dimensions of immobilization zones reached the 50 µm range. Other functionalization strategies, such as sol-gel encapsulation of aptamers, are currently investigated and may also be suitable for the development of the analytical microdevice. The development of these functionalization strategies is the first crucial step in the design of the entire microdevice. These strategies allow the grafting of a large number of molecules for the development of new analytical tools in various domains like environment or healthcare.

Keywords: alkyne-azide click chemistry (CuAAC), electrochemical modification, microsystem, plasma bromination, surface functionalization, thermoplastic polymers

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Authors: Jing Jiang, Yuguang Gao, Yang Yu

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Facing increasingly challenging insurance payment pressures, the Chinese healthcare system is undergoing significant transformations, akin to the implementation of DRG payment models by the United States' Medicare. Consequently, there is a pressing need for Chinese hospitals to establish optimizations in departmental operations tailored to the ongoing healthcare payment reforms. This abstract delineates the meticulous construction of a scientifically rigorous and comprehensive index system at the departmental level in China strategically aligned with the evolving landscape of healthcare payment reforms. Methodologically, it integrates key process areas and maturity assessment theories, synthesizing relevant literature and industry standards to construct a robust framework and indicator pool. Employing the Delphi method, consultations with 21 experts were conducted, revealing a collective demonstration of high enthusiasm, authority, and coordination in designing the index system. The resulting model comprises four primary indicators -technical capabilities, cost-effectiveness, operational efficiency, and disciplinary potential- supported by 14 secondary indicators and 23 tertiary indicators with varied coefficient adjustment for department types (platform or surgical). The application of this evaluation system in a Chinese hospital within the northeastern region yielded results aligning seamlessly with the actual operational scenario. In conclusion, the index system comprehensively considers the integrity and effectiveness of structural, process, and outcome indicators and stands as a comprehensive reflection of the collective expertise of the engaged experts, manifesting in a model designed to elevate the operational management of hospital departments. Its strategic alignment with healthcare payment reforms holds practical significance in guiding departmental development positioning, brand cultivation, and talent development.

Keywords: Chinese healthcare system, Delphi method, departmental management, evaluation indicators, hospital operations, weight coefficients

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Authors: K. C. Tanuja, Mamatha P. Raj

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Urbanisation is happening rapidly all over the world. As population increasing in the urban settlements, its required to provide quality of life to all the inhabitants who live in. Urban design is a place making strategic planning. Urban design principles promote visualising any place environmentally, socially and economically viable. Urban design strategies include building mass, transit development, economic viability and sustenance and social aspects.

Keywords: livable streets, social interaction, pedestrian use, urban design

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Authors: A. Buruzs, M. F. Hatwágner, L. T. Kóczy

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The aim of the present paper is to develop an integrated method that may provide assistance to decision makers during system planning, design, operation and evaluation. In order to support the realization of Circular Economy (CE), it is essential to evaluate local needs and conditions which help to select the most appropriate system components and resource needs. Each of these activities requires careful planning, however, the model of CE offers a comprehensive interdisciplinary framework. The aim of this research was to develop and to introduce a practical methodology for evaluation of local and regional opportunities to promote CE.

Keywords: circular economy, factors, fuzzy cognitive map, model reduction, sustainability

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Matthew Arnaouti, Michael Baird, Gabrielle Cahill, Tamara Worlton, Michelle Joseph

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Introduction: Over ten years after the 7.0 magnitude Earthquake struck the capital of Haiti, impacting over three million people and leading to the deaths of over two hundred thousand, the multinational humanitarian response remains the largest disaster relief effort to date. This study critically evaluates the multi-sector and multinational disaster response to the Earthquake, looking at how the lessons learned from this analysis can be applied to future disaster response efforts. We put particular emphasis on assessing the interaction between civilian and military sectors during this humanitarian relief effort, with the hopes of highlighting how concrete guidelines are essential to improve future responses. Methods: An extensive scoping review of the relevant literature was conducted - where library scientists conducted reproducible, verified systematic searches of multiple databases. Grey literature and hand searches were utilised to identify additional unclassified military documents, for inclusion in the study. More than 100 documents were included for data extraction and analysis. Key domains were identified, these included: Humanitarian and Military Response, Communication, Coordination, Resources, Needs Assessment and Pre-Existing Policy. Corresponding information and lessons-learned pertaining to these domains was then extracted - detailing the barriers and facilitators to an effective response. Results: Multiple themes were noted which stratified all identified domains - including the lack of adequate pre-existing policy, as well as extensive ambiguity of actors’ roles. This ambiguity was continually influenced by the complex role the United States military played in the disaster response. At a deeper level, the effects of neo-colonialism and concern about infringements on Haitian sovereignty played a substantial role at all levels: setting the pre-existing conditions and determining the redevelopment efforts that followed. Furthermore, external factors significantly impacted the response, particularly the loss of life within the political and security sectors. This was compounded by the destruction of important infrastructure systems - particularly electricity supplies and telecommunication networks, as well as air and seaport capabilities. Conclusions: This study stands as one of the first and most comprehensive evaluations, systematically analysing the civilian and military response - including their collaborative efforts. This study offers vital information for improving future combined responses and provides a significant opportunity for advancing knowledge in disaster relief efforts - which remains a more pressing issue than ever. The categories and domains formulated serve to highlight interdependent factors that should be applied in future disaster responses, with significant potential to aid the effective performance of humanitarian actors. Further studies will be grounded in these findings, particularly the need for greater inclusion of the Haitian perspective in the literature, through additional qualitative research studies.

Keywords: civilian and military collaboration, combined response, disaster, disaster response, earthquake, Haiti, humanitarian response

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Luyao Liu, Dekui Yuan, Xu Li

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As one of the most important bays of China, the water exchange capacity of Bohai Bay can influence the economic development and urbanization of surrounding cities. However, the rapid reclamation has influenced the weak water exchange capacity of this semi-enclosed bay in recent years. This paper sets two hydrodynamic models of Bohai Bay with two shorelines before and after reclamation. The mean value and distribution of Turn-over Time, the distribution of residual current, and the feature of the tracer path are compared. After comparison, it is found that Bohai Bay keeps these characteristics; the spending time of water exchange in the northern is longer than southern, and inshore is longer than offshore. However, the mean water exchange time becomes longer after reclamation. In addition, the material spreading is blocked because of the inwardly extending shorelines, and the direction changed from along the shoreline to towards the center after reclamation.

Keywords: Bohai Bay, water exchange, reclamation, turn-over time

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Authors: Yusra Yahya

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In this paper, a new spell-out mechanism is developed and defended. This mechanism builds on the role of phase heads as both the loci of spell-out features and the transfer triggers via either Phase Impenetrability Condition 1 (PIC1) and/or Phase Impenetrability Condition 2 (PIC2). The assumption here is that phase heads, mainly v*, can regulate the spell-out process by deciding both the type of spell-out applying and the timing of spell-out relevant. This paper also proposes a new form of the constraint Wrap call it Wrap-XP’ and it is assumed to apply to IP as a functional maximal projection. This extension is shown to fall as a natural result once we assume the new theory of phases and multiple spell-out. Moreover, it is proposed in this work that some forms of XP movement are not motivated by an EPP feature of a strong phase head mainly v*, but they are rather motivated by a last resort strategy to accomplish the spell-out instruction of this phase head.

Keywords: linguistics, syntax, phonology, phase theory, optimality theory

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Authors: Cristiana Ortigão, Antonio Couto, Thiago Gabriel

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In the wake of Samarco Fundão’s failure in 2015 followed by Vale’s Brumadinho disaster in 2019, the Brazilian National Mining Agency started a comprehensive dam safety programmed to rank dam safety risks and establish monitoring and analysis procedures. This paper focuses on the use of accelerometers for static and dynamic applications. Static applications may employ tiltmeters, as an example shown later in this paper. Dynamic monitoring of a structure with accelerometers yields its dynamic signature and this technique has also been successfully used in Brazil and this paper gives an example of tailings dam.

Keywords: instrumentation, dynamic, monitoring, tailings, dams, tiltmeters, automation

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Authors: Homayon Ahmad Panahi, Seyed Mehdi Seyed Nejad, Elham Moniri

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A novel bio-adsorbent is fabricated by attaching a cibacron blue to yeast cells. The modified bio-sorbent has been characterized by some techniques like Fourier transform infrared spectroscopy (FT-IR) and elemental analysis (CHN) and applied for the preconcentration and determination of samarium from aqueous water samples. The best pH value for adsorption of the brilliant crecyle blue by yeast cells- cibacron blue was 7. The sorption capacity of modified biosorbent was 18.5 mg. g⁻¹. A recovery of 95.3% was obtained for Sm(III) when eluted with 0.5 M nitric acid. The method was applied for Sm(III) preconcentration and determination in river water sample.

Keywords: samarium, solid phase extraction, yeast cells, water sample, removal

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Authors: Shih-Chieh Liao, Cheng-Yan Shuai

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The feature of a side-scrolling shooting game is facing the surrounding enemy and barraging in entire screen. The player will be in trouble when they are trying to do complicated operations because of the physical and system limitations of the joystick in the games. This study designed the prototype of a new type of arcade stick by focus group and assessed by the expert. By filtering the most representative, and build up the control system for the arcade stick, and testing time and bullets consumed in two experiments, try to prove it works in the game. Finally, the prototype of L-1 solves the dilemma of scroll shooting games when the player uses the arcade stick and improves the function of the arcade stick.

Keywords: arcade stick, joystick, user interface, 2D STG

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Authors: Corey F. Fitzgerald

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This study provides a comprehensive examination of the biomechanical sequencing inherent in pitching motions, coupled with an advanced methodology for interpreting gathered data to inform programming strategies. The analysis is conducted utilizing state-of-the-art biomechanical laboratory equipment capable of detecting subtle changes and deviations, facilitating highly informed decision-making processes. Through this presentation, the intricate dynamics of pitching sequences are meticulously discussed to highlight the complex movement patterns accessible and actionable for performance enhancement purposes in the weight room.

Keywords: sport science, applied biomechanics, strength and conditioning, applied research

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Authors: S. Nagheli, N. Samani, D. A. Barry

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In this paper, the velocity potential and stream function of capture zone for a well field in an aquifer bounded by two parallel streams with or without a uniform regional flow of any directions are presented. The well field includes any number of extraction or injection wells or a combination of both types with any pumping rates. To delineate the capture envelope, the potential and streamlines equations are derived by conformal mapping method. This method can help us to release constrains of other methods. The equations can be applied as useful tools to design in-situ groundwater remediation systems, to evaluate the surface–subsurface water interaction and to manage the water resources.

Keywords: complex potential, conformal mapping, image well theory, Laplace’s equation, superposition principle

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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To develop a machine learning model to predict diabetes (DM) prevalence in the U.S. population using demographic characteristics, physical indicators, and lifestyle habits, and to analyze how these factors contribute to the likelihood of diabetes. We analyzed data from 23,546 participants aged 20 and older, who were non-pregnant, from the 2009-2018 National Health and Nutrition Examination Survey (NHANES). The dataset included key demographic (age, sex, ethnicity), physical (BMI, leg length, total cholesterol [TCHOL], fasting plasma glucose), and lifestyle indicators (smoking habits). A weighted sample was used to account for NHANES survey design features such as stratification and clustering. A classification machine learning model was trained to predict diabetes status. The target variable was binary (diabetes or non-diabetes) based on fasting plasma glucose measurements. The following models were evaluated: Logistic Regression (baseline), Random Forest Classifier, Gradient Boosting Machine (GBM), Support Vector Machine (SVM). Model performance was assessed using accuracy, F1-score, AUC-ROC, and precision-recall metrics. Feature importance was analyzed using SHAP values to interpret the contributions of variables such as age, BMI, ethnicity, and smoking status. The Gradient Boosting Machine (GBM) model outperformed other classifiers with an AUC-ROC score of 0.85. Feature importance analysis revealed the following key predictors: Age: The most significant predictor, with diabetes prevalence increasing with age, peaking around the 60s for males and 70s for females. BMI: Higher BMI was strongly associated with a higher risk of diabetes. Ethnicity: Black participants had the highest predicted prevalence of diabetes (14.6%), followed by Mexican-Americans (13.5%) and Whites (10.6%). TCHOL: Diabetics had lower total cholesterol levels, particularly among White participants (mean decline of 23.6 mg/dL). Smoking: Smoking showed a slight increase in diabetes risk among Whites (0.2%) but had a limited effect in other ethnic groups. Using machine learning models, we identified key demographic, physical, and lifestyle predictors of diabetes in the U.S. population. The results confirm that diabetes prevalence varies significantly across age, BMI, and ethnic groups, with lifestyle factors such as smoking contributing differently by ethnicity. These findings provide a basis for more targeted public health interventions and resource allocation for diabetes management.

Keywords: diabetes, NHANES, random forest, gradient boosting machine, support vector machine

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Authors: Violina Angelova, Krasimir Ivanov, Stefan Krustev, Dimitar Dimitrov

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Availability of a metal is characterised by its quantity transgressing from soil into different extractants or by its content in plants. In literature, the terms 'available forms of compounds' and 'mobile' are often considered as equivalents of the term 'accessible' to plants. Rapid and a sufficiently reliable method for defining the accessible for plants forms turns out to be their extraction through different extractants, imitating the functioning of the root system. As a criterion for the pertinence of the extractant to this purpose usually serves the significant statistic correlation between the extracted quantities of the element from soil and its content in plants. The aim of this work was to evaluate the effectiveness of various extractions (DTPA-TEA, AB-DTPA, Mehlich 3, 0.01 M CaCl₂, 1M NH₄NO₃) for the determination of bioavailability of heavy metals in industrially polluted soils from the metallurgical activity near Plovdiv and Kardjali, Bulgaria. Quantity measurements for contents of heavy metals were performed with ICP-OES. The results showed that extraction capacity was as follows: Mehlich 3>ABDTPA>DTPA-TEA>CaCl₂>NaNO₃. The content of the mobile form of heavy metals depends on the nature of metal ion, the nature of extractant and pH. The obtained results show that CaCl₂ extracts a greater quantity of mobile forms of heavy metals than NH₄NO₃. DTPA-TEA and AB-DTPA are capable of extracting from the soil not only the heavy metals participating in the exchange processes but also the heavy metals bound in carbonates and organic complexes, as well as bound and occluded in oxide and secondary clay minerals. AB-DTPA extracts a bit more heavy metals than DTPA-TEA. The darker color of the solutions obtained with AB-DTPA indicates that considerable quantities organic matter are being destructed. A comparison of the mobile forms of heavy metals extracted from clean and highly polluted soils has revealed that in the polluted soils the greater portion of heavy metals exists in a mobile form. High correlation coefficients are obtained between the metals extracted with different extractants and their total content in soil (r=0.9). A positive correlation between the pH, soil organic matter and the extracted quantities of heavy metals has been found. The results of correlation analysis revealed that the heavy metals extracted by DTPA-TEA, AB-DTPA, Mehlich 3, CaCl₂ and NaNO₃ correlated significantly with plant uptake. Significant correlation was found between DTPA-TEA, AB-DTPA, and CaCl₂ with heavy metals concentration in plants. Application of extracting methods contains chelating agents would be recommended in the future research onthe availabilityof heavy metals in polluted soils.

Keywords: availability, chemical extractants, heavy metals, mobile forms

Procedia PDF Downloads 355

Authors: Farouk Lawan Gambo, Hamada Mohammad

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Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.

Keywords: data compression, learning preference, mobile learning, multimedia

Procedia PDF Downloads 447

Authors: Ahmad Haidar

Abstract:

This research paper investigates the concept of modern management, concentrating on the development of managerial practices and the adoption of innovative strategies in response to the fast-changing business landscape caused by Artificial Intelligence (AI). The study begins by examining the historical context of management theories, tracing the progression from classical to contemporary models, and identifying key drivers of change. Through a comprehensive review of existing literature and case studies, this paper provides valuable insights into the principles and practices of modern management, offering a roadmap for organizations aiming to navigate the complexities of the contemporary business world. The paper examines the growing role of digital technology in modern management, focusing on incorporating AI, machine learning, and data analytics to streamline operations and facilitate informed decision-making. Moreover, the research highlights the emergence of new principles, such as adaptability, flexibility, public participation, trust, transparency, and digital mindset, as crucial components of modern management. Also, the role of business leaders is investigated by studying contemporary leadership styles, such as transformational, situational, and servant leadership, emphasizing the significance of emotional intelligence, empathy, and collaboration in fostering a healthy organizational culture. Furthermore, the research delves into the crucial role of environmental sustainability, corporate social responsibility (CSR), and corporate digital responsibility (CDR). Organizations strive to balance economic growth with ethical considerations and long-term viability. The primary research question for this study is: "What are the key principles, practices, and innovations that define modern management, and how can organizations effectively implement these strategies to thrive in the rapidly changing business landscape?." The research contributes to a comprehensive understanding of modern management by examining its historical context, the impact of digital technologies, the importance of contemporary leadership styles, and the role of CSR and CDR in today's business landscape.

Keywords: modern management, digital technology, leadership styles, adaptability, innovation, corporate social responsibility, organizational success, corporate digital responsibility

Procedia PDF Downloads 66

Authors: Albert Kwabena Osei Konadu

Abstract:

One of the endemic forest species of the savannah transition zones enlisted by the Convention of International Treaty for Endangered Species (CITES) in Appendix II is the Rosewood, also known as Pterocarpus erinaceus or Krayie. Its economic viability has made it increasingly popular and in high demand. Ghana’s forest resource management regime for these ecozones is mainly on conservation and very little on resource utilization. Consequently, commercial logging management standards are at teething stage and not fully developed, leading to a deficiency in the monitoring of logging operations and quantification of harvested trees volumes. Tree information form (TIF); a volume estimation and tracking regime, has proven to be an effective sustainable management tool for regulating timber resource extraction in the high forest zones of the country. This work aims to generate TIF that can track and capture requisite parameters to accurately estimate the volume of harvested rosewood within forest savannah transition zones. Tree information forms were created on three scenarios of individual billets, stacked billets and conveying vessel basis. The study was limited by the usage of regulators assigned volume as benchmark and also fraught with potential volume measurement error in the stacked billet scenario due to the existence of spaces within packed billets. These TIFs were field-tested to deduce the most viable option for the tracking and estimation of harvested volumes of rosewood using the smallian and cubic volume estimation formula. Overall, four districts were covered with individual billets, stacked billets and conveying vessel scenarios registering mean volumes of 25.83m3,45.08m3 and 32.6m3, respectively. These adduced volumes were validated by benchmarking to assigned volumes of the Forestry Commission of Ghana and known standard volumes of conveying vessels. The results did indicate an underestimation of extracted volumes under the quotas regime, a situation that could lead to unintended overexploitation of the species. The research revealed conveying vessels route is the most viable volume estimation and tracking regime for the sustainable management of the Pterocarpous erinaceus species as it provided a more practical volume estimate and data extraction protocol.

Keywords: cubic volume formula, smallian volume formula, pterocarpus erinaceus, tree information form, forest transition and savannah zones, harvested tree volume

Procedia PDF Downloads 44