Search results for: national models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10879

Search results for: national models

10039 The Museum of Museums: A Mobile Augmented Reality Application

Authors: Qian Jin

Abstract:

Museums have been using interactive technology to spark visitor interest and improve understanding. These technologies can play a crucial role in helping visitors understand more about an exhibition site by using multimedia to provide information. Google Arts and Culture and Smartify are two very successful digital heritage products. They used mobile augmented reality to visualise the museum's 3D models and heritage images but did not include 3D models of the collection and audio information. In this research, service-oriented mobile augmented reality application was developed for users to access collections from multiple museums(including V and A, the British Museum, and British Library). The third-party API (Application Programming Interface) is requested to collect metadata (including images, 3D models, videos, and text) of three museums' collections. The acquired content is then visualized in AR environments. This product will help users who cannot visit the museum offline due to various reasons (inconvenience of transportation, physical disability, time schedule).

Keywords: digital heritage, argument reality, museum, flutter, ARcore

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10038 Numerical Simulation of Kangimi Reservoir Sedimentation, Kaduna State, Nigeria

Authors: Abdurrasheed Sa'id, Abubakar Isma'il, Waheed Alayande

Abstract:

This study focused on carrying out numerical simulations of Kangimi reservoir sedimentation by reviewing different numerical sediment transport models, and GSTARS3 was selected. The model was developed using the 1977 data. It was calibrated by simulating the 2012 profile and sediment deposition and compared with 2012 hydrographic survey results of NWRI. The model was validated by simulating the 2016 deposition and compared the results with NWRI estimates. Also, the performance of the proposed model was tested using statistical parameters such as MSE (Mean Square Error), MAPE (Mean Average Percentage Error) and R2 (Coefficient of determination) with values of 1.32m, 0.17% and 0.914 respectively which shows strong agreement. After the calibration, validation and performance testing the model was used to simulate the 2032 and 2062 profiles and deposition. The results showed that by 2032 the reservoir will be silted by 25.34MCM or 43.3% of the design capacity and 60.7% of the capacity by the year 2062. A number of sedimentation mitigation measures were recommended.

Keywords: NWRI- national water resources institute, sedimentation, GSTARS3, model

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10037 Artificial Intelligence-Based Detection of Individuals Suffering from Vestibular Disorder

Authors: Dua Hişam, Serhat İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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10036 On Four Models of a Three Server Queue with Optional Server Vacations

Authors: Kailash C. Madan

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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: a three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state

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10035 Time Series Regression with Meta-Clusters

Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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10034 Creation and Management of Knowledge for Organization Sustainability and Learning

Authors: Deepa Kapoor, Rajshree Singh

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This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

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10033 Removal of Toxic Ni++ Ions from Wastewater by Nano-Bentonite

Authors: A. M. Ahmed, Mona A. Darwish

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Removal of Ni++ ions from aqueous solution by sorption ontoNano-bentonite was investigated. Experiments were carried out as a function amount of Nano-bentonite, pH, concentration of metal, constant time, agitation speed and temperature. The adsorption parameter of metal ions followed the Langmuir Freundlich adsorption isotherm were applied to analyze adsorption data. The adsorption process has fit pseudo-second order kinetic models. Thermodynamics parameters e.g.ΔG*, ΔS °and ΔH ° of adsorption process have also been calculated and the sorption process was found to be endothermic. The adsorption process has fit pseudo-second order kinetic models. Langmuir and Freundich adsorption isotherm models were applied to analyze adsorption data and both were found to be applicable to the adsorption process. Thermodynamic parameters, e.g., ∆G °, ∆S ° and ∆H ° of the on-going adsorption process have also been calculated and the sorption process was found to be endothermic. Finally, it can be seen that Bentonite was found to be more effective for the removal of Ni (II) same with some experimental conditions.

Keywords: waste water, nickel, bentonite, adsorption

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10032 Multi-National Corporations and International Communication. An Analysis of Arçelik globals’ Online Presences

Authors: Aisha Iddrsiu

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Public Relations (PR) has rapidly evolved around the world, just as companies have expanded to reach other parts of the world. With most multinational corporations conducting businesses in more than one country, only a few of these Multinational Corporations (MNC’s) are actual public relations firms, many have public relations departments or divisions that conduct public relations practices internationally. Hence international public relations is seen as a fast-growing specialty in the field of Public Relations. Multinational companies have devised strategies to effectively communicate and execute their roles within and between foreign publics and other cultures in which they operate through various means including the internet which is among the major inventions that have enabled corporations to establish their presents while targeting anonymous and diverse publics from varied cultures. International public relations practitioners rely on strategies coupled with internet use to communicate among and with foreign publics. Corporate websites and various social media handles have served as an important channel for public relations activities targeting both internal and international publics. In an incessant expansion of corporations and interactions with the publics from different cultures, it has become eminent to understand the public relation strategies used by MNCs in their international communication. This study therefore seeks to establish the international public relation strategies or models employed by Multinational Corporations specifically Arcelik Global in the management of its subsidiaries and communicating with international public. This study analyses both Arçelik global’s (one of the largest multinational companies in Turkey) website and social media accounts to understand the management strategy used with it subsidiary as well as strategies used to communicate with its global and local publics. Other underlying objective of this study are, 1. To examine the dominant international public relations models used by Multinational Corporations (Arcelik global). 2. To understand how Multinational Corporations manage (Arcelik global) its subsidiaries. 3. To understand how Multinational Corporations (Arcelik global) communicate with international or global publics. Research Questions 1. The main global PR strategies employed by multinational corporations (Arcelik global) 2. How subsidiaries of multinational corporations like Arcelik Global are managed. 3. How multinational corporations, like Arcelik worldwide, interact with international publics.

Keywords: multinational corporation, ethnocentric model, polycentric model, international public relations

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10031 Analyzing the Performance of Machine Learning Models to Predict Alzheimer's Disease and its Stages Addressing Missing Value Problem

Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

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Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

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10030 Persian Pistachio Nut (Pistacia vera L.) Dehydration in Natural and Industrial Conditions

Authors: Hamid Tavakolipour, Mohsen Mokhtarian, Ahmad Kalbasi Ashtari

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In this study, the effect of various drying methods (sun drying, shade drying and industrial drying) on final moisture content, shell splitting degree, shrinkage and color change were studied. Sun drying resulted higher degree of pistachio nuts shell splitting on pistachio nuts relative other drying methods. The ANOVA results showed that the different drying methods did not significantly effects on color change of dried pistachio nut. The results illustrated that pistachio nut dried by industrial drying had the lowest moisture content. After the end of drying process, initially, the experimental drying data were fitted with five famous drying models namely Newton, Page, Silva et al., Peleg and Henderson and Pabis. The results indicated that Peleg and Page models gave better results compared with other models to monitor the moisture ratio’s pistachio nut in industrial drying and open sun (or shade drying) methods, respectively.

Keywords: industrial drying, pistachio, quality properties, traditional drying

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10029 Credit Risk Evaluation Using Genetic Programming

Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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10028 Ideology and the Writer's Commitment to National Development: Profiling the Nigerian Soldier in Isidore Okpewho's ‘The Last Duty and Festus Iyayi's Heroes’

Authors: Edwin Onwuka, Segun Omidiora, Eugenia Abiodun-Eniaiyekan

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The Nigerian military is often the subject of active critical inquiries having played significant roles in Nigeria’s national development. However, the soldier is one of the most vilified characters in Nigeria’s imaginative literature, be it in poetry, drama or prose fiction. In the main, the characterization of soldiers is predictable because of their entrenched stereotype as oppressors, tyrants, bullies, rapists, despots, killers or at best law-breakers subject to no authority outside the military institution. In most novels, the soldier’s personality is associated with force and violence; still, few have defied the norm to portray soldiers that go against the grain of notoriety. Such novels have characterized the Nigerian soldier positively as a civil, thinking and human personality in relating to civil society. To a great extent, two major impetuses that influence literary representation of characters and institutions in African literature are ideology and commitment, and one necessarily impacts on the other in shaping the artistic vision of the writer. Using two war novels therefore as templates, this paper argues that the ideology that drives the Nigerian writer’s socio-cultural commitment to national development shapes their portrayal of the Nigerian soldier in imaginative literature. A major objective of this study, therefore, is to show through close textual analysis that the writers’ ideologies influence their perception and characterization of the Nigerian soldier in Isidore Okpewho’s The Last Duty and Festus Iyayi’s Heroes, two representative novels of both persuasions described above. New Historicism is the critical framework applied in this study and its conclusion is that the Nigerian writer’s characterization of the soldier is influenced by his ideological perception of the military in the policy against the backdrop of their past socio-political activities.

Keywords: commitment, ideology, national development, new historicism, Nigerian soldier

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10027 An Infinite Mixture Model for Modelling Stutter Ratio in Forensic Data Analysis

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

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10026 Adaptive Neuro Fuzzy Inference System Model Based on Support Vector Regression for Stock Time Series Forecasting

Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

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Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

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10025 Comparison of Fundamental Frequency Model and PWM Based Model for UPFC

Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider

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Among all FACTS devices, the unified power flow controller (UPFC) is considered to be the most versatile device. This is due to its capability to control all the transmission system parameters (impedance, voltage magnitude, and phase angle). With the growing interest in UPFC, the attention to develop a mathematical model has increased. Several models were introduced for UPFC in literature for different type of studies in power systems. In this paper a novel comparison study between two dynamic models of UPFC with their proposed control strategies.

Keywords: FACTS, UPFC, dynamic modeling, PWM, fundamental frequency

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10024 Sustainable Housing Framework for the Czech Republic: A Comparative Analysis of International and National Strategies

Authors: Jakub Adamec, Svatava Janouskova, Tomas Hak

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The necessity of sustainable housing is explicitly embedded in ‘The 2030 agenda for sustainable development’, in particular, goal 11 ‘sustainable cities and communities’. Every UN member state is obligated to implement strategies from the agenda, including a strategy for sustainable housing into the practice in the local context. As shown in many countries, the lack of knowledge represses the adaptation process of sustainable strategies by governments. Hence, this study explores the concept of sustainable housing within the Czech Republic. The research elaborates on this term, and its current definition concerning ‘Geneva UN Charter on Sustainable Housing’. To this day, the charter represents the most comprehensive framework for a sustainable housing concept. Researchers conducted a comparative analysis of 38 international and 195 Czech national strategic documents. As a result, the charter‘s and strategic documents‘ goals were interconnected, identifying the most represented targets (e.g. improved environmental and energy performance of dwellings, resilient urban settlements which use renewable energy, and sustainable and integrated transport systems). The research revealed, even though the concept of sustainable housing is still dominated by environmental aspects, that social aspects significantly increased its importance. Additionally, this theoretical framework will serve as a foundation for the sustainable housing index development for the Czech Republic.

Keywords: comparative analysis, Czech national strategy, Geneva un charter, sustainable housing, urban theory

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10023 Innovation Management Strategy towards the Detroit of Asia

Authors: Jarunee Wonglimpiyarat

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This paper explores the innovation management strategy of Thailand in moving towards the Detroit of Asia. The study analyses Thailand’s automotive cluster based on Porter’s Diamond Model and national innovation system (NIS) framework. A qualitative methodology was carried out, using semi-structured interviews with the players in the Thai automotive industry. Thailand took a different NIS approach by pursuing an Original Equipment Manufacture (OEM) strategy to attract foreign investments in building its automotive cluster, a different path from other Asian countries that competed with Own Brand Manufacture (OBM) strategies. The findings provide useful lessons for other newly industrialized countries (NICs) in adopting the cluster policies to move up the technological ladders.

Keywords: innovation management strategy, national innovation system (NIS), Detroit of Asia, original equipment manufacturer (OEM)

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10022 Influence of European Funds on the Sector of Bovine Milk and Meat in Romania in the Period 2007-2013

Authors: Andrei-Marius Sandu

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This study aims to analyze the bovine meat and milk sector for the period 2007-2013. For the period analyzed, it is known that Romania has benefited from EU funding through the National Rural Development Programme 2007-2013. In this programme, there were measures that addressed exclusively the animal husbandry sector in Romania. This paper presents data on bovine production of meat, milk and livestock in Romania, but also data on the price and impact the European Funds implementation had on them.

Keywords: European funds, measures, national rural development programme, price

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10021 ASEAN Air Transport Liberalization and Its Impact to Indonesian Air Service

Authors: Oentoeng Wahjoe

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Liberalisation of air transportation practically is known as open sky policy. In the practice, the liberalisation of air transportation is divided into two group of services, i.e.: air transportation services, for passengers and goods (air service) which is categorized as hard rights and supporting services of the air transportation services (ancillary services) which is categorized as soft rights. The research in this paper focused in air transportation services for passengers and goods, consists of nine freedom of the air. The impact of the policy such as the Agreement regarding ASEAN open sky policy, is the readiness of Indonesian air transportation companies to compete with foreign air transportation companies. The goverment of Indonesia has to regulate the implementation of ASEAN Open Sky Policy to be projected in order to comply with national development, i.e. the function of air law in national development. The policy has been implemented by enact or amend the existing law as air law that regulate flight lines, the following provisions: To regulate flight line for foreign airlines to open flight lines in Indonesia region which may not or have not land and sea transportation. The regulation is intended to supprot mobility of humans, goods and services that may fulfil the needs of the people of Indonesia, which materially and spiritually and the development of the region. The regulation of flight lines of foreign air transportation for region of tourism, industrial and trade centre. The regulation is intended to support the national economic development of Indonesia.

Keywords: transport, liberalization, impact, Indonesian air service

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10020 Monitoring Large-Coverage Forest Canopy Height by Integrating LiDAR and Sentinel-2 Images

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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10019 Experiments on Weakly-Supervised Learning on Imperfect Data

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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10018 Development of an Optimised, Automated Multidimensional Model for Supply Chains

Authors: Safaa H. Sindi, Michael Roe

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This project divides supply chain (SC) models into seven Eras, according to the evolution of the market’s needs throughout time. The five earliest Eras describe the emergence of supply chains, while the last two Eras are to be created. Research objectives: The aim is to generate the two latest Eras with their respective models that focus on the consumable goods. Era Six contains the Optimal Multidimensional Matrix (OMM) that incorporates most characteristics of the SC and allocates them into four quarters (Agile, Lean, Leagile, and Basic SC). This will help companies, especially (SMEs) plan their optimal SC route. Era Seven creates an Automated Multidimensional Model (AMM) which upgrades the matrix of Era six, as it accounts for all the supply chain factors (i.e. Offshoring, sourcing, risk) into an interactive system with Heuristic Learning that helps larger companies and industries to select the best SC model for their market. Methodologies: The data collection is based on a Fuzzy-Delphi study that analyses statements using Fuzzy Logic. The first round of Delphi study will contain statements (fuzzy rules) about the matrix of Era six. The second round of Delphi contains the feedback given from the first round and so on. Preliminary findings: both models are applicable, Matrix of Era six reduces the complexity of choosing the best SC model for SMEs by helping them identify the best strategy of Basic SC, Lean, Agile and Leagile SC; that’s tailored to their needs. The interactive heuristic learning in the AMM of Era seven will help mitigate error and aid large companies to identify and re-strategize the best SC model and distribution system for their market and commodity, hence increasing efficiency. Potential contributions to the literature: The problematic issue facing many companies is to decide which SC model or strategy to incorporate, due to the many models and definitions developed over the years. This research simplifies this by putting most definition in a template and most models in the Matrix of era six. This research is original as the division of SC into Eras, the Matrix of Era six (OMM) with Fuzzy-Delphi and Heuristic Learning in the AMM of Era seven provides a synergy of tools that were not combined before in the area of SC. Additionally the OMM of Era six is unique as it combines most characteristics of the SC, which is an original concept in itself.

Keywords: Leagile, automation, heuristic learning, supply chain models

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10017 Studying Iranian Religious Minority Architecture: Differences and Commonalities in Religious and National Architecture after Safavid

Authors: Saeideh Soltanmohammadlou, Pilar M Guerrieri, Amir Kianfar, Sara Sadeghian, Yasaman Nafezi, Emily Irvin

Abstract:

Architecture is rooted in the experiences of the residents in a place. Its foundations are based on needs and circumstances of each territory in terms of climate, available materials, economics and governmental policies, and cultural ideals and ideas of the people that live there. The architectural history of Iran echoes these architectural origins and has revealed certain trends reflecting this territory and culture. However, in recent years, new architectural patterns are developing that diverge from what has previously been considered classic forms of Iranian architecture. This article investigates architectural elements that make up the architecture created by religious minorities after the Safavid dynasty (one of the most significant ruling dynasties of Iran (from 1501 to 1736) in Iranian cities: Isfahan, Tabriz, Kerman, and Uremia. Similarities and differences are revealed between the architecture that composes neighborhoods of religious minorities in Iran and common national architectural trends in each era after this dynasty. This dynasty is specific as a point of reference in this article because Islam was identified as the state religion of Iran during this era. This decision changed the course of architecture in the country to incorporate religious motifs and meanings. The study associated with this article was conducted as a survey that sought to find links between architecture of religious minorities with Iranian national architecture. Interestingly, a merging of architectural forms and trends occur as immigrants interact with Iranian Islamic meanings. These observations are significant within the context of modern architecture around the world and within Western discourse because what are considered religious minorities in Iran are the dominant religions in Western nations. This makes Iran’s architecture particularly unique as it creates a kind of inverse relationship, than that of Western nations, to the ways in which religion influences architectural history.

Keywords: architecture, ethnic architecture, national architecture, religion architecture

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10016 Collective Redress in Consumer Protection in South East Europe: Cross-National Comparisons, Issues of Commonality and Difference

Authors: Veronika Efremova

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In recent decades, there have been significant developments in the European Union in the field of collective consumer redress. South East European countries (SEE) covered by this paper, in line with their EU accession priorities and duties under Stabilisation and Association Agreements, have to harmonize their national laws with the relevant EU acquis for consumer protection (Chapter 28: Health and Consumer). In these countries, only minimal compliance is achieved. SEE countries have introduced rudimentary collective redress mechanisms, with modest enforcement of collective redress and case law. This paper is based on comprehensive interdisciplinary research conducted for SEE countries on common principles for injunctive and compensatory collective redress mechanisms, emphasizing cross-national comparisons, underlining issues of commonality and difference aiming to develop recommendations for an adequate enforcement of collective redress. SEE countries are recognized by the sectoral approach for regulating collective redress contrary to the majority of EU Member States with having adopted horizontal approach to collective redress. In most SEE countries, the laws do not recognize compensatory but only injunctive collective redress in consumer protection. All responsible stakeholders for implementation of collective redress in SEE countries, lack information and awareness on collective redress mechanisms and the way they function in practice. Therefore, specific actions are needed in these countries to make the whole system of collective redress for consumer protection operational and efficient. Taking into consideration the various designated stakeholders in collective redress in each SEE countries, there is a need of their mutual coordination and cooperation in order to develop consumer protection system and policies. By putting into practice the national collective redress mechanisms, effective access to justice for all consumers, the principle of rule of law will be secured and appropriate procedural guarantees to avoid abusive litigation will be ensured.

Keywords: collective redress mechanism, consumer protection, commonality and difference, South East Europe

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10015 Numerical Investigation of Two Turbulence Models for Predicting the Temperature Separation in Conical Vortex Tube

Authors: M. Guen

Abstract:

A three-dimensional numerical study is used to analyze the behavior of the flow inside a vortex tube. The vortex tube or Ranque-Hilsch vortex tube is a simple device which is capable of dividing compressed air from the inlet nozzle tangentially into two flow with different temperatures warm and cold. This phenomenon is known from literature by temperature separation. The K ω-SST and K-ε turbulence models are used to predict the turbulent flow behaviour inside the tube. The vortex tube is an Exair 708 slpm (25 scfm) commercial tube. The cold and hot exits areas are 30.2 and 95 mm2 respectively. The vortex nozzle consists of 6 straight slots; the height and the width of each slot are 0.97 mm and 1.41 mm. The total area normal to the flow associated with six nozzles is therefore 8.15 mm 2. The present study focuses on a comparison between two turbulence models K ω-SST, K-ε by using a new configuration of vortex tube (Conical Vortex Tube). The performance curves of the temperature separation versus cold outlet mass fraction were calculated and compared with experimental and numerical study of other researchers.

Keywords: conical vortex tube, temperature separation, cold mass fraction, turbulence

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10014 Scoliosis Effect towards of Incidence of the Secondary Osteoarthritis on the Knee in Athletes at the National Sports Cibubur Hospital on July 2013-April 2014

Authors: Basuki Supartono, Nunuk Nugrohowati, Ryan Gamma Andiraldi

Abstract:

Osteoarthritis of the knee can occur due to scoliosis. The purpose of this study is to determine the effect of scoliosis cause secondary osteoarthritis on the knee. This research use an analytic cross-sectional design. The total sample of 92 athletes scoliosis taken by simple random sampling technique. The data obtained were analyzing with Chi-square test, Fisher and Prevalence Ratio. The results of analysis show that there are influences on the incidence of scoliosis secondary osteoarthritis on the knee in athletes at the National Sports Hospital. Based on the criteria in the Cobbs angle had the results (p = 0.022 (p <0.05)), moderate Cobbs angle degree were 7.5 times more at risk of causing secondary osteoarthritis on the knee than a mild degree. While the shape of the curve scoliosis is getting results (p = 0.038 (p <0.05)), the shape of the S curve scoliosis 3.2 times more at risk of causing secondary osteoarthritis on the knee than the curve C. It can be concluded that there is significant influence between the Cobbs angle, shape of the curve scoliosis on the incidence of secondary osteoarthritis on the knee in National Sports Cibubur Hospital on July 2013- April 2014

Keywords: Cobbs angle, curve shape scoliosis, secondary osteoarthritis on the knee, analytic cross-sectional design

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10013 Kinetics, Equilibrium and Thermodynamics of the Adsorption of Triphenyltin onto NanoSiO₂/Fly Ash/Activated Carbon Composite

Authors: Olushola S. Ayanda, Olalekan S. Fatoki, Folahan A. Adekola, Bhekumusa J. Ximba, Cecilia O. Akintayo

Abstract:

In the present study, the kinetics, equilibrium and thermodynamics of the adsorption of triphenyltin (TPT) from TPT-contaminated water onto nanoSiO2/fly ash/activated carbon composite was investigated in batch adsorption system. Equilibrium adsorption data were analyzed using Langmuir, Freundlich, Temkin and Dubinin–Radushkevich (D-R) isotherm models. Pseudo first- and second-order, Elovich and fractional power models were applied to test the kinetic data and in order to understand the mechanism of adsorption, thermodynamic parameters such as ΔG°, ΔSo and ΔH° were also calculated. The results showed a very good compliance with pseudo second-order equation while the Freundlich and D-R models fit the experiment data. Approximately 99.999 % TPT was removed from the initial concentration of 100 mg/L TPT at 80oC, contact time of 60 min, pH 8 and a stirring speed of 200 rpm. Thus, nanoSiO2/fly ash/activated carbon composite could be used as effective adsorbent for the removal of TPT from contaminated water and wastewater.

Keywords: isotherm, kinetics, nanoSiO₂/fly ash/activated carbon composite, tributyltin

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10012 Developing Primary Care Datasets for a National Asthma Audit

Authors: Rachael Andrews, Viktoria McMillan, Shuaib Nasser, Christopher M. Roberts

Abstract:

Background and objective: The National Review of Asthma Deaths (NRAD) found that asthma management and care was inadequate in 26% of cases reviewed. Major shortfalls identified were adherence to national guidelines and standards and, particularly, the organisation of care, including supervision and monitoring in primary care, with 70% of cases reviewed having at least one avoidable factor in this area. 5.4 million people in the UK are diagnosed with and actively treated for asthma, and approximately 60,000 are admitted to hospital with acute exacerbations each year. The majority of people with asthma receive management and treatment solely in primary care. This has therefore created concern that many people within the UK are receiving sub-optimal asthma care resulting in unnecessary morbidity and risk of adverse outcome. NRAD concluded that a national asthma audit programme should be established to measure and improve processes, organisation, and outcomes of asthma care. Objective: To develop a primary care dataset enabling extraction of information from GP practices in Wales and providing robust data by which results and lessons could be drawn and drive service development and improvement. Methods: A multidisciplinary group of experts, including general practitioners, primary care organisation representatives, and asthma patients was formed and used as a source of governance and guidance. A review of asthma literature, guidance, and standards took place and was used to identify areas of asthma care which, if improved, would lead to better patient outcomes. Modified Delphi methodology was used to gain consensus from the expert group on which of the areas identified were to be prioritised, and an asthma patient and carer focus group held to seek views and feedback on areas of asthma care that were important to them. Areas of asthma care identified by both groups were mapped to asthma guidelines and standards to inform and develop primary and secondary care datasets covering both adult and pediatric care. Dataset development consisted of expert review and a targeted consultation process in order to seek broad stakeholder views and feedback. Results: Areas of asthma care identified as requiring prioritisation by the National Asthma Audit were: (i) Prescribing, (ii) Asthma diagnosis (iii) Asthma Reviews (iv) Personalised Asthma Action Plans (PAAPs) (v) Primary care follow-up after discharge from hospital (vi) Methodologies and primary care queries were developed to cover each of the areas of poor and variable asthma care identified and the queries designed to extract information directly from electronic patients’ records. Conclusion: This paper describes the methodological approach followed to develop primary care datasets for a National Asthma Audit. It sets out the principles behind the establishment of a National Asthma Audit programme in response to a national asthma mortality review and describes the development activities undertaken. Key process elements included: (i) mapping identified areas of poor and variable asthma care to national guidelines and standards, (ii) early engagement of experts, including clinicians and patients in the process, and (iii) targeted consultation of the queries to provide further insight into measures that were collectable, reproducible and relevant.

Keywords: asthma, primary care, general practice, dataset development

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10011 Strategy Management of Soybean (Glycine max L.) for Dealing with Extreme Climate through the Use of Cropsyst Model

Authors: Aminah Muchdar, Nuraeni, Eddy

Abstract:

The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

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10010 Solar-Electric Pump-out Boat Technology: Impacts on the Marine Environment, Public Health, and Climate Change

Authors: Joy Chiu, Colin Hemez, Emma Ryan, Jia Sun, Robert Dubrow, Michael Pascucilla

Abstract:

The popularity of recreational boating is on the rise in the United States, which raises numerous national-level challenges in the management of air and water pollution, aquatic habitat destruction, and waterway access. The need to control sewage discharge from recreational vessels underlies all of these challenges. The release of raw human waste into aquatic environments can lead to eutrophication and algal blooms; can increase human exposure to pathogenic viruses, bacteria, and parasites; can financially impact commercial shellfish harvest/fisheries and marine bathing areas; and can negatively affect access to recreational and/or commercial waterways to the detriment of local economies. Because of the damage that unregulated sewage discharge can do to environments and human health/marine life, recreational vessels in the United States are required by law to 'pump-out' sewage from their holding tanks into sewage treatment systems in all designated 'no discharge areas'. Many pump-out boats, which transfer waste out of recreational vessels, are operated and maintained using funds allocated through the Federal Clean Vessel Act (CVA). The East Shore District Health Department of Branford, Connecticut is protecting this estuary by pioneering the design and construction of the first-in-the-nation zero-emissions, the solar-electric pump-out boat of its size to replace one of its older traditional gasoline-powered models through a Connecticut Department of Energy and Environmental Protection CVA Grant. This study, conducted in collaboration with the East Shore District Health Department, the Connecticut Department of Energy and Environmental Protection, States Organization for Boating Access and Connecticut’s CVA program coordinators, had two aims: (1) To perform a national assessment of pump-out boat programs, supplemented by a limited international assessment, to establish best pump-out boat practices (regardless of how the boat is powered); and (2) to estimate the cost, greenhouse gas emissions, and environmental and public health impacts of solar-electric versus traditional gasoline-powered pump-out boats. A national survey was conducted of all CVA-funded pump-out program managers and selected pump-out boat operators to gauge best practices; costs associated with gasoline-powered pump-out boat operation and management; and the regional, cultural, and policy-related issues that might arise from the adoption of solar-electric pump-out boat technology. We also conducted life-cycle analyses of gasoline-powered and solar-electric pump-out boats to compare their greenhouse gas emissions; production of air, soil and water pollution; and impacts on human health. This work comprises the most comprehensive study into pump-out boating practices in the United States to date, in which information obtained at local, state, national, and international levels is synthesized. This study aims to enable CVA programs to make informed recommendations for sustainable pump-out boating practices and identifies the challenges and opportunities that remain for the wide adoption of solar-electric pump-out boat technology.

Keywords: pump-out boat, marine water, solar-electric, zero emissions

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