Search results for: non-linear dynamics features

Authors: Shahroz Khan, Erkan Gunpinar, Kemal Mart

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Recently parametric design techniques became a vital concept in the field of Computer Aided Design (CAD), which helps to provide sophisticated platform to the designer in order to automate the design process in efficient time. In these techniques, design process starts by parameterizing the important features of design models (typically the key dimensions), with the implementation of design constraints. The design constraints help to retain the overall shape of the model while modifying its parameters. However, the process of initializing an appropriate number of design parameters and constraints is the crucial part of parametric design techniques, especially for complex surface models such as yacht hull. This paper introduces a method to create complex surface models in favor of parametric design techniques, a method to define the right number of parameters and respective design constraints, and a system to implement design parameters in contract to design constraints schema. For this, in our proposed approach the design process starts by dividing the yacht hull into three sections. Each section consists of different shape lines, which form the overall shape of yacht hull. The shape lines are created using Cubic Bezier Curves, which allow larger design flexibility. Design parameters and constraints are defined on the shape lines in 3D design space to facilitate the designers for better and individual handling of parameters. Afterwards, shape modifiers are developed, which allow the modification of each parameter while satisfying the respective set of criteria and design constraints. Such as, geometric continuities should be maintained between the shape lines of the three sections, fairness of the hull surfaces should be preserved after modification and while design modification, effect of a single parameter should be negligible on other parameters. The constraints are defined individually on shape lines of each section and mutually between the shape lines of two connecting sections. In order to validate and visualize design results of our shape modifiers, a real time graphic interface is created.

Keywords: design parameter, design constraints, shape modifies, yacht hull

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Camilo Andres Agudelo-Velez, Lina María Martinez-Sanchez, Natalia Perilla-Hernandez, Maria De Los Angeles Rodriguez-Gazquez, Felipe Hernandez-Restrepo, Dayana Andrea Quintero-Moreno, Camilo Ruiz-Mejia, Isabel Cristina Ortiz-Trujillo, Monica Maria Zuluaga-Quintero

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Chronic obstructive pulmonary disease is common condition, characterized by a persistent blockage of airflow, partially reversible and progressive, that represents 5% of total deaths around the world, and it is expected to become the third leading cause of death by 2030. Objective: To establish the clinical and epidemiological profile of patients with chronic obstructive pulmonary disease in a medical institution from the city of Medellin, Colombia. Methods: A cross-sectional study was performed, with a sample of 50 patients with a diagnosis of chronic obstructive pulmonary disease in a private institution in Medellin, during 2015. The software SPSS vr. 20 was used for the statistical analysis. For the quantitative variables, averages, standard deviations, and maximun and minimun values were calculated, while for ordinal and nominal qualitative variables, proportions were estimated. Results: The average age was 73.5±9.3 years, 52% of the patients were women, 50% of them had retired, 46% ere married and 80% lived in the city of Medellín. The mean time of diagnosis was 7.8±1.3 years and 100% of the patients were treated at the internal medicine service. The most common clinical features were: 36% were classified as class D for the disease, 34% had a FEV1 <30%, 88% had a history of smoking and 52% had oxygen therapy at home. Conclusion: It was found that class D was the most common, and the majority of the patients had a history of smoking, indicating the need to strengthen promotion and prevention strategies in this regard.

Keywords: pulmonary disease, chronic obstructive, pulmonary medicine, oxygen inhalation therapy

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Authors: Andra-Iulia Ursa

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James Joyce employs several unconventional stylistic features in this landmark novel meant to experiment with language. The episode known as “Sirens” is entirely conceived around music and linguistic structures subordinated to sound. However, the aspiration to the condition of music is reflected throughout this entire literary work, as musical effects are echoed systematically. The numerous melodies scattered across the narrative play an important role in enhancing the thoughts and feelings that pass through the minds of the characters. Often the lyrics are distorted or interweaved with other words, preoccupations or memories, intensifying the stylistic effect. The Victorian song “Love’s old sweet song” is one of the most commonly referred to and meaningful musical allusions in Ulysses, becoming a leitmotif of infidelity. The lyrics of the song “M’appari”, from the opera “Martha”, are compared to an event from Molly and Bloom’s romantic history. Moreover, repeated phrases using words from “The bloom is on the rye” or “The croppy boy” serve as glances into the minds of the characters. Therefore, the central purpose of this study is to shed light on the way musical allusions flit through the episodes from the point of view of the stream of consciousness technique and to compare and analyse how these constructions are rendered into Romanian. Mircea Ivănescu, the single Romanian translator who succeeded in carrying out the translation of the entire ‘stylistic odyssey’, received both praises and disapprovals from the critics. This paper is not meant to call forth eventual flaws of the Romanian translation, but rather to elaborate the complexity of the task. Following an attentive examination and analysis of the two texts, from the point of view of form and meaning of the references to various songs, the conclusions of this study will be able to point out the intricacies of the process of translation.

Keywords: Joyce, melodious constructions, stream of consciousness, style, translation

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Authors: Anne Waithira Dormal

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Climate change is threatening pastoral livelihoods in Kajiado County, Kenya, through water shortages, livestock deaths, and increasing poverty. This study examines how these impacts differ for men and women within these communities. Limited access to resources, limited land and livestock rights, and limited decision-making power increase women's vulnerability, which is further burdened by traditional gender roles in water procurement. The research recognizes the complexity of climate change and emphasizes that factors such as wealth, family dynamics, and socioeconomic status also influence resilience. Effective adaptation strategies must address all genders. While livestock farming provides a safety net, socioeconomic empowerment through access to credit, healthcare, and education strengthens entire communities. An intersectional perspective that takes ethnicity, social status, and other factors into account is also crucial. This research, therefore, aims to examine how gender-specific adaptation strategies interact with gender and socioeconomic factors to determine the resilience of these Kenyan pastoralist communities. Such strategies, which address the specific needs and vulnerabilities of men and women, are expected to lead to increased resilience to climate change. The aim of the study is to identify effective, gender-specific adaptation strategies that can be integrated into climate change planning and implementation. Additionally, research awaits a deeper understanding of how socioeconomic factors interact with gender to influence vulnerability and resilience within these communities. The study uses a gender-sensitive qualitative approach with focus group discussions in four different pastoral and agropastoral communities. Both qualitative and demographic data are used to capture sources of income, education level, and household size of focus group respondents to increase the power of the analysis. While the research acknowledges the limitations of specific focus sites and potential biases in self-reporting, it offers valuable insights into gender and climate change in pastoral contexts. This study contributes to understanding gender-based vulnerabilities and building resilience in these communities.

Keywords: climate adaptation strategies, climate change, climate resilience, gendered vulnerability, pastoralism

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Authors: Renata Szewczyk, Beata Lachtara, Kinga Wieczorek, Jacek Osek

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Campylobacter is recognized as the main cause of bacterial gastrointestinal infections in Europe. A main source of the pathogen is poultry and poultry meat; however, other animals like pigs and cattle can also be reservoirs of the bacteria. Human Campylobacter infections are often self-limiting but in some cases, macrolide and fluoroquinolones have to be used. The aim of this study was to determine antimicrobial resistance patterns (AMR) of Campylobacter isolated from pig and cattle carcasses. Between July 2009 and December 2015, 735 swabs from pig (n = 457) and cattle (n = 278) carcasses were collected at Polish slaughterhouses. All samples were tested for the presence of Campylobacter by ISO 10272-1 and confirmed to species level using PCR. The antimicrobial susceptibility of Campylobacter isolates was determined by a microbroth dilution method with six antimicrobials: gentamicin (GEN), streptomycin (STR), erythromycin (ERY), nalidixic acid (NAL), ciprofloxacin (CIP) and tetracycline (TET). It was found that 167 of 735 samples (22.7%) were contaminated with Campylobacter. The vast majority of them were of pig origin (134; 80.2%), whereas for cattle carcasses Campylobacter was less prevalent (33; 19.8%). Among positive samples C. coli was predominant species (123; 73.7%) and it was isolated mainly from pig carcasses. The remaining isolates were identified as C. jejuni (44; 26.3%). Antimicrobial susceptibility indicated that 22 out of 167 Campylobacter (13.2%) were sensitive to all antimicrobials used. Fourteen of them were C. jejuni (63.6%; pig, n = 6; cattle, n = 8) and 8 was C. coli (36.4%; pig, n = 4; cattle, n = 4). Most of the Campylobacter isolates (145; 86.8%) were resistant to one or more antimicrobials (C. coli, n = 115; C. jejuni, n = 30). Comparing the AMR for Campylobacter species it was found that the most common pattern for C. jejuni was CIP-NAL-TET (9; 30.0%), whereas CIP-NAL-STR-TET was predominant among C. coli (47; 40.9%). Multiresistance, defined as resistance to three or more classes of antimicrobials, was found in 57 C. coli strains, mostly obtained from pig (52 isolates). On the other hand, only one C. jejuni strain, isolated from cattle, showed multiresistance with pattern CIP-NAL-STR-TET. Moreover, CIP-NAL-STR-TET was characteristic for most of multiresistant C. coli isolates (47; 82.5%). For the remaining C. coli the resistance patterns were CIP-ERY-NAL-TET (7 strains; 12.3%) and for one strain of each patterns: ERY-STR-TET, CIP-STR-TET, CIP-NAL-GEN-STR-TET. According to the present findings resistance to erythromycin was observed only in 11 C. coli (pig, n = 10; cattle, n = 1). In conclusion, the results of this study showed that pig carcasses may be a serious public health concern because of contamination with C. coli that might features multiresistance to antimicrobials.

Keywords: antimicrobial resistance, Campylobacter, carcasses, multi resistance

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Authors: Zdzislaw Kaminski, Zbigniew Czyz, Tytus Tulwin

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This paper describes the geometrical model, algorithm and CFD simulation of an airflow around a Vertical Axis Wind Turbine rotor. A solver, ANSYS Fluent, was applied for the numerical simulation. Numerical simulation, unlike experiments, enables us to validate project assumptions when it is designed to avoid a costly preparation of a model or a prototype for a bench test. This research focuses on the rotor designed according to patent no PL 219985 with its blades capable of modifying their working surfaces, i.e. absorbing wind kinetic energy. The operation of this rotor is based on a regulation of blade angle α between the top and bottom parts of blades mounted on an axis. If angle α increases, the working surface which absorbs wind kinetic energy also increases. CFD calculations enable us to compare aerodynamic characteristics of forces acting on rotor working surfaces and specify rotor operation parameters like torque or turbine assembly power output. This paper is part of the research to improve an efficiency of a rotor assembly and it contains investigation of the impact of a blade angle of wind turbine working blades on the power output as a function of rotor torque, specific rotational speed and wind speed. The simulation was made for wind speeds ranging from 3.4 m/s to 6.2 m/s and blade angles of 30°, 60°, 90°. The simulation enables us to create a mathematical model to describe how aerodynamic forces acting each of the blade of the studied rotor are generated. Also, the simulation results are compared with the wind tunnel ones. This investigation enables us to estimate the growth in turbine power output if a blade angle changes. The regulation of blade angle α enables a smooth change in turbine rotor power, which is a kind of safety measures if the wind is strong. Decreasing blade angle α reduces the risk of damaging or destroying a turbine that is still in operation and there is no complete rotor braking as it is in other Horizontal Axis Wind Turbines. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: computational fluid dynamics, mathematical model, numerical analysis, power, renewable energy, wind turbine

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Authors: M. A. Brown, K. Hugill, D. Meredith

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Since the establishment of midwifery, as a professional identity in its own right, in the early years of the 20th century, midwifery-led models of childbirth have prevailed in many parts of the world. However, in many locations midwives’ scope of practice remains underdeveloped or absent. In Qatar, all births take place in hospital and are under the professional jurisdiction of obstetricians, predominately supported by internationally trained nurse-midwives and obstetric nurses. The strategic vision for health services in Qatar endorsed a desire to provide women with the ‘Best Care Always’ and the introduction of midwifery was seen as a way to achieve this. In 2015 the process of recruiting postgraduate educated Clinical Midwife Specialists from international sources began. The midwives were brought together to initiate an in hospital and community service transformation plan. This plan set out a series of wide-ranging actions to transform maternity and neonatal services to make care safer and give women more health choices. Change in any organization is a complex and dynamic process. This is made even more complex when multifaceted professional and cross cultural factors are involved. This presentation reports upon the motivations and challenges that exist and the progress around introducing a multicultural midwifery model of childbirth care in the state of Qatar. The paper examines and reflects upon the drivers and unique features of childbirth in the country. Despite accomplishments, progress still needs to be made in order to fully implement sustainable changes to further improve care and ensure women and neonates get the ‘Best Care Always’. The progress within the transformation plan highlights how midwifery may coexist with competing models of maternity care to create an innovative, eclectic and culturally sensitive paradigm that can best serve women and neonatal health needs.

Keywords: culture, managing change, midwifery, neonatal, service transformation plan

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Authors: Elitsa Kolentsova, Dimitar Dimitrov, Vasko Idakiev, Tatyana Tabakova, Krasimir Ivanov

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Formaldehyde production by selective oxidation of methanol is an important industrial process. The main by-products in the waste gas are CO and dimethyl ether (DME). The idea of this study is to combine the advantages of both Cu-Mn and Cu-Co catalytic systems by obtaining a new mixed Cu-Mn-Co catalyst with high activity and selectivity at the simultaneous oxidation of CO, methanol, and DME. Two basic Cu-Mn samples with high activity were selected for further investigation: (i) manganese-rich Cu-Mn/γ–Al2O3 catalyst with Cu/Mn molar ratio 1:5 and (ii) copper-rich Cu-Mn/γ-Al2O3 catalyst with Cu/Mn molar ratio 2:1. Manganese in these samples was replaced by cobalt in the whole concentration region, and catalytic properties were determined. The results show a general trend of decreasing the activity toward DME oxidation and increasing the activity toward CO and methanol oxidation with the increase of cobalt up to 60% for both groups of catalyst. This general trend, however, contains specific features, depending on the composition of the catalyst and the nature of the oxidized gas. The catalytic activity of the sample with Cu/(Mn+Co) molar ratio of 2:1 is gradually changed with increasing the cobalt content. The activity of the sample with Cu/(Mn+Co) molar ratio of 1: 5 passes through a maximum at 60% manganese replacement by cobalt, probably due to the formation of highly dispersed Co-based spinel structures (Co3O4 and/or MnCo2O4). In conclusion, the present study demonstrates that the Cu-Mn-Co/γ–alumina supported catalysts have enhanced activity toward CO, methanol and DME oxidation. Cu/(Mn+Co) molar ratio 1:5 and Co/Mn molar ratio 1.5 in the active component can ensure successful oxidation of CO, CH3OH and DME. The active component of the mixed Cu-Mn-Co/γ–alumina catalysts consists of at least six compounds - CuO, Co3O4, MnO2, Cu1.5Mn1.5O4, MnCo2O4 and CuCo2O4, depending on the Cu/Mn/Co molar ratio. Chemical composition strongly influences catalytic properties, this effect being quite variable with regards to the different processes.

Keywords: Cu-Mn-Co catalysts, oxidation, carbon oxide, VOCs

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Authors: Pengfei Meng, Shuangcheng Jia, Qian Li

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We proposed a real-time high-precision semantic segmentation network based on a multi-resolution feature fusion module, the auxiliary feature extracting module, upsampling module, and atrous spatial pyramid pooling (ASPP) module. We designed a feature fusion structure, which is integrated with sufficient features of different resolutions. We also studied the effect of side-branch structure on the network and made discoveries. Based on the discoveries about the side-branch of the network structure, we used a side-branch auxiliary feature extraction layer in the network to improve the effectiveness of the network. We also designed upsampling module, which has better results than the original upsampling module. In addition, we also re-considered the locations and number of atrous spatial pyramid pooling (ASPP) modules and modified the network structure according to the experimental results to further improve the effectiveness of the network. The network presented in this paper takes the backbone network of Bisenetv2 as a basic network, based on which we constructed a network structure on which we made improvements. We named this network deep multiple-resolution bilateral networks for real-time, referred to as DMBR-Net. After experimental testing, our proposed DMBR-Net network achieved 81.2% mIoU at 119FPS on the Cityscapes validation dataset, 80.7% mIoU at 109FPS on the CamVid test dataset, 29.9% mIoU at 78FPS on the COCOStuff test dataset. Compared with all lightweight real-time semantic segmentation networks, our network achieves the highest accuracy at an appropriate speed.

Keywords: multi-resolution feature fusion, atrous convolutional, bilateral networks, pyramid pooling

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Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

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Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: D. Avila

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The tourism industry is a phenomenon that has become a growing presence in international socio-economic dynamics, which in most cases exceeds the control parameters in the various environmental regulations and sustainability of existing resources. Because of this, the effects on the natural environment at the regional and national levels represent a challenge, for which a number of strategies are necessary to minimize the environmental impact generated by the occupation of the territory. The hotel tourist building and sustainable development in the coastal zone, have an important impact on the environment and on the physical and psychological health of the inhabitants. Environmental quality associated with the comfort of humans to the sustainable development of natural resources; applied to the hotel architecture this concept involves the incorporation of new demands on all of the constructive process of a building, changing customs of developers and users. The methodology developed provides an initial analysis to determine and rank the different tourist buildings, with the above it will be feasible to establish methods of study and environmental impact assessment. Finally, it is necessary to establish an overview regarding the best way to implement tourism development on the coast, containing guidelines to improve and protect the natural environment. This paper analyzes the parameters and strategies to reduce environmental impacts derived from deployments tourism on the coast, through a series of recommendations towards sustainability, in the context of the Bahia de Banderas, Puerto Vallarta, Jalisco. The environmental impact caused by the implementation of tourism development, perceived in a coastal environment, forcing a series of processes, ranging from the identification of impacts, prediction and evaluation of them. For this purpose are described below, different techniques and valuation procedures: Identification of impacts. Methods for the identification of damage caused to the environment pursue general purpose to obtain a group of negative indicators that are subsequently used in the study of environmental impact. There are several systematic methods to identify the impacts caused by human activities. In the present work, develops a procedure based and adapted from the Ministry of works public urban reference in studies of environmental impacts, the representative methods are: list of contrast, arrays, and networks, method of transparencies and superposition of maps.

Keywords: environmental impact, physical health, sustainability, tourist building

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Authors: Temesgen Minase Woldegebriel

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This study undertakes a comparative analysis of two distinct staples from diverse culinary heritages: Polish traditional bread and Teff Injera. Despite originating from disparate cultural contexts, both these foods hold significant roles in their respective societies, serving as dietary staples rich in cultural symbolism and nutritional value. Our investigation delves into the historical, cultural, and nutritional dimensions of Polish bread and Teff Injera, shedding light on their ingredients, preparation methods, and consumption patterns. Firstly, we explore the rich history and cultural significance embedded within Polish traditional bread, tracing its evolution through centuries of tradition and craftsmanship. From the ubiquitous Polish Rye bread to the intricate regional variations, we unravel the socio-cultural narratives intertwined with each loaf, reflecting Polish identity and culinary heritage. In contrast, our analysis extends to Teff Injera, a staple of Ethiopian and Eritrean cuisine known for its spongy texture and tangy flavor. We delve into the ancient origins of Teff cultivation, highlighting its pivotal role in Ethiopian culture and its symbolic significance in communal dining practices, such as the traditional Ethiopian coffee ceremony. Furthermore, we undertake a comparative examination of the nutritional profiles of Polish bread and Teff Injera, assessing their respective contributions to dietary health and well-being. Through comprehensive nutritional analysis, we elucidate the unique attributes of each staple, considering factors such as gluten content, fiber composition, and micronutrient density. Moreover, our study investigates the contemporary relevance of these traditional staples in the context of shifting dietary preferences and global culinary trends. We analyze consumer perceptions and market dynamics surrounding Polish bread and Teff Injera, discerning patterns of consumption and avenues for innovation in a rapidly evolving food landscape. In conclusion, our comparative analysis illuminates the multifaceted dimensions of Polish traditional bread and Teff Injera, transcending mere culinary discourse to encompass broader themes of cultural heritage, nutrition, and gastronomic diversity.

Keywords: bread, culinary, injera, teff

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

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Authors: Oleg Redkin, Olga Bernikova

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Globalization and migrations have made cross-cultural contacts more frequent and intensive. Sometimes, these contacts may lead to misunderstanding between partners of communication and misinterpretations of the verbal messages that some researchers tend to consider as the 'clash of civilizations'. In most cases, reasons for that may be found in cultural and linguistic differences and hence misinterpretations of intentions and behavior. The current research examines factors of verbal and non-verbal communication that should be taken into consideration in verbal and non-verbal contacts. Language is one of the most important manifestations of the cultural code, and it is often considered as one of the special features of a civilization. The Arabic language, in particular, is commonly associated with Islam and the language and the Arab-Muslim civilization. It is one of the most important markers of self-identification for more than 200 million of native speakers. Arabic is the language of the Quran and hence the symbol of religious affiliation for more than one billion Muslims around the globe. Adequate interpretation of Arabic texts requires profound knowledge of its grammar, semantics of its vocabulary. Communicating sides who belong to different cultural groups are guided by different models of behavior and hierarchy of values, besides that the vocabulary each of them uses in the dialogue may convey different semantic realities and vary in connotations. In this context direct, literal translation in most cases cannot adequately convey the original meaning of the original message. Besides that peculiarities and diversities of the extralinguistic information, such as the body language, communicative etiquette, cultural background and religious affiliations may make the dialogue even more difficult. It is very likely that the so called 'clash of civilizations' in most cases is due to misinterpretation of counterpart's means of discourse such as language, cultural codes, and models of behavior rather than lies in basic contradictions between partners of communication. In the process of communication, one has to rely on universal values rather than focus on cultural or religious peculiarities, to take into account current linguistic and extralinguistic context.

Keywords: Arabic, civilization, discourse, language, linguistic

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Authors: Bolatbek Rysbaiuly, Nazerke Rysbayeva, Aigerim Rysbayeva

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Relevance: Energy saving elevated to public policy in almost all developed countries. One of the areas for energy efficiency is improving and tightening design standards. In the tie with the state standards, make high demands for thermal protection of buildings. Constructive arrangement of layers should ensure normal operation in which the humidity of materials of construction should not exceed a certain level. Elevated levels of moisture in the walls can be attributed to a defective condition, as moisture significantly reduces the physical, mechanical and thermal properties of materials. Absence at the design stage of modeling the processes occurring in the construction and predict the behavior of structures during their work in the real world leads to an increase in heat loss and premature aging structures. Method: To solve this problem, widely used method of mathematical modeling of heat and mass transfer in materials. The mathematical modeling of heat and mass transfer are taken into the equation interconnected layer [1]. In winter, the thermal and hydraulic conductivity characteristics of the materials are nonlinear and depends on the temperature and moisture in the material. In this case, the experimental method of determining the coefficient of the freezing or thawing of the material becomes much more difficult. Therefore, in this paper we propose an approximate method for calculating the thermal conductivity and moisture permeability characteristics of freezing or thawing material. Questions. Following the development of methods for solving the inverse problem of mathematical modeling allows us to answer questions that are closely related to the rational design of fences: Where the zone of condensation in the body of the multi-layer fencing; How and where to apply insulation rationally his place; Any constructive activities necessary to provide for the removal of moisture from the structure; What should be the temperature and humidity conditions for the normal operation of the premises enclosing structure; What is the longevity of the structure in terms of its components frost materials. Tasks: The proposed mathematical model to solve the following problems: To assess the condition of the thermo-physical designed structures at different operating conditions and select appropriate material layers; Calculate the temperature field in a structurally complex multilayer structures; When measuring temperature and moisture in the characteristic points to determine the thermal characteristics of the materials constituting the surveyed construction; Laboratory testing to significantly reduce test time, and eliminates the climatic chamber and expensive instrumentation experiments and research; Allows you to simulate real-life situations that arise in multilayer enclosing structures associated with freezing, thawing, drying and cooling of any layer of the building material.

Keywords: energy saving, inverse problem, heat transfer, multilayer walling

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Authors: Eman H. El-Gamal, Maher E. Saleh, Mohamed Rashad, Ibrahim Elsokkary, Mona M. Abd El-Latif

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Biochar application to calcareous soils could potentially influence the nitrogen dynamics that affect the bioavailability of plants. This study was carried out to investigate the effect of incubation periods on the changes of nitrogen levels (total nitrogen TN and exchangeable ammonium NH₄⁺ and nitrate NO₃⁻) in biochar-treated calcareous soil. The incubation course was extended to 144 days at 30 ± 3 ℃ and at 50% of soil water holding capacity (WHC). Two types of biochars were obtained by pyrolysis at 500 ℃ from rice husk (RHB) and sugarcane bagasse (SCBB). The experiment was planned in a factorial experimental design with three factors (6 periods '24 days for each period' × 3 biochar types 'un-amended, RHB and SCBB' × 3 nitrogen fertilizers 'control, ammonium nitrate; AN and animal manure; AM') in a completely randomized design. The results obtained showed that the highest level of TN was found in the first 24 days of the incubation period in all treatments. However, the amount of TN was decreased with proceeding incubation period up to 144 days and reached to the lowest level at the end of incubation with values of change rate was 17.5, 16.6, and 14.6 g kg⁻¹ day⁻¹ for the un-amended, RHB and SCBB treated soil, respectively. The values of change rate in biochar-soils treated with nitrogen fertilizers were decreased gradually through the whole incubation time from 127.22 to 12.45 g kg⁻¹ day⁻¹ and from 65.00 to 13.43 g kg⁻¹ day⁻¹ for AN and AM respectively, in the case of RHB-soil. While in SCBB-soil, these values were decreased from 70.83 to 12.13 g kg⁻¹ day⁻¹ and from 59.17 to 11.48 g kg⁻¹ day⁻¹ for AN and AM treatments, respectively. The lowest concentration of exchangeable NH₄⁺ was generally found through the period from 24-48 days of incubation. However, the addition of nitrogen fertilizers, enhanced NH₄⁺ production through incubation periods. In the case of RHB-soil, the value of change rate in NH₄⁺ level in the first 24 days of incubation was 0.43 mg kg⁻¹ day⁻¹ and with the addition of AN and AM this value increased to 1.54 and 4.38 mg kg⁻¹ day⁻¹, respectively. In the case of SCBB-soil, the value of change rate in NH₄⁺ level was 0.29 mg kg⁻¹ day⁻¹ which increased to 1.04 mg kg⁻¹ day⁻¹ at the end of incubation, and due to the addition of AN and AM this value increased to 2.78 and 1.90 mg kg⁻¹ day⁻¹ in the first 24 days of incubation period, respectively. However, as compared to the control treatment, the lowest rate of change in NH₄⁺ level was found at the end of incubation. On the other hand, incubation of all biochars-amended soil and treated with AN and AM decreased the concentration levels of NO₃⁻, especially through the first 24-72 days of incubation period. As a result, the values of change rate in NO₃⁻ concentrations in all treatments were almost negative.

Keywords: ammonium nitrate, animal manure, biochar, rice husk, sugarcane bagasse

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Authors: Jennifer Walinga, Samantha Heron

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The goal of the study was to inform the design of effective leadership and mentorship development programming for sport science leaders within the network of Canadian sport institutes and centers. The LEAD (Learn, Engage, Accelerate, Develop) program was implemented to equip sport science leaders with the leadership knowledge, skills, and practice to foster a high - performance culture, enhance the daily training environment, and contribute to optimal performance in sport. After two years of delivery, this analysis of LEAD’s effect on individual and organizational health and performance factors informs the quality of future deliveries and identifies best practice for leadership development across the Canadian sport system and beyond. A larger goal for this project was to inform the public sector more broadly and position sport as a source of best practice for human and social health, development, and performance. The objectives of this study were to review and refine the LEAD program in collaboration with Canadian Sport Institute and Centre leaders, 40-50 participants from three cohorts, and the LEAD program advisory committee, and to trace the effects of the LEAD leadership development program on key leadership mentorship and organizational health indicators across the Canadian sport institutes and centers so as to capture best practice. The study followed a participatory action research framework (PAR) using semi structured interviews with sport scientist participants, program and institute leaders inquiring into impact on specific individual and organizational health and performance factors. Findings included a strong increase in self-reported leadership knowledge, skill, language and confidence, enhancement of human and organizational health factors, and the opportunity to explore more deeply issues of diversity and inclusion, psychological safety, team dynamics, and performance management. The study was significant in building sport leadership and mentorship development strategies for managing change efforts, addressing inequalities, and building personal and operational resilience amidst challenges of uncertainty, pressure, and constraint in real time.

Keywords: sport leadership, sport science leader, leadership development, professional development, sport education, mentorship

Procedia PDF Downloads 26

Authors: Ziwei Song, Junjun Fan, Jeremy Teo, Yang Yu, Yukun Ma, Jie Yan, Shupei Mo, Lisa Tucker-Kellogg, Peter So, Hanry Yu

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Liver is the center of detoxification and exposed to toxic metabolites all the time. It is highly regenerative after injury, with the ability to restore even after 70% partial hepatectomy. Most of the previous studies were using hepatectomy as injury models for liver regeneration study. There is limited understanding of small-scale liver injury, which can be caused by either low dose drug consumption or hepatocyte routine metabolism. Although these small in situ injuries do not cause immediate symptoms, repeated injuries will lead to aberrant wound healing in liver. Therefore, the cellular dynamics during liver regeneration is critical for our understanding of liver regeneration mechanism. We aim to study the liver regeneration of small-scale in situ liver injury in transgenic mice labeling actin (Lifeact-GFP). Previous studies have been using sample sections and biopsies of liver, which lack real-time information. In order to trace every individual hepatocyte during the regeneration process, we have developed and optimized an intravital imaging system that allows in vivo imaging of mouse liver for consecutive 5 days, allowing real-time cellular tracking and quantification of hepatocytes. We used femtosecond-laser ablation to make controlled and repeatable liver injury model, which mimics the real-life small in situ liver injury. This injury model is the first case of its kind for in vivo study on liver. We found that small-scale in situ liver injury is repaired by the coordination of hypertrophy and migration of hepatocytes. Hypertrophy is only transient at initial phase, while migration is the main driving force to complete the regeneration process. From cellular aspect, Akt/mTOR pathway is activated immediately after injury, which leads to transient hepatocyte hypertrophy. From mechano-sensing aspect, the actin cable, formed at apical surface of wound proximal hepatocytes, provides mechanical tension for hepatocyte migration. This study provides important information on both chemical and mechanical signals that promote liver regeneration of small in situ injury. We conclude that hypertrophy and migration play a dominant role at different stages of liver regeneration.

Keywords: hepatocyte, hypertrophy, intravital imaging, liver regeneration, migration

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Authors: Bülent Kantar, Numan Ünaldı

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This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

Procedia PDF Downloads 537

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 504

Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

Procedia PDF Downloads 290

Authors: Moustafa Osman Mohammed

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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: autopoiesis, nanoparticles, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system

Procedia PDF Downloads 127

Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

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Authors: Aklilu Getahun Sulito

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Land Use and Land Cover change dynamics is a result of complex interactions betweenseveral bio- physical and socio-economic conditions. The impacts of the landcoverchange on stream flow and sediment yield were analyzed statistically usingthehydrological model, SWAT. Genale Dawa Dam III watershed is highly af ectedbydeforestation, over grazing, and agricultural land expansion. This study was aimedusingSWAT model for the assessment of impacts of land use land cover change on sediment yield, evaluating stream flow on wet &dry seasons and spatial distribution sediment yieldfrom sub-basins of the Genale Dawa Dam III watershed. Land use land cover maps(LULC) of 2000, 2008 and 2016 were used with same corresponding climate data. During the study period most parts of the forest, dense forest evergreen and grass landchanged to cultivated land. The cultivated land increased by 26.2%but forest land, forest evergreen lands and grass lands decreased by 21.33%, 11.59 % and 7.28 %respectively, following that the mean annual sediment yield of watershed increased by 7.37ton/haover16 years period (2000 – 2016). The analysis of stream flow for wet and dry seasonsshowed that the steam flow increased by 25.5% during wet season, but decreasedby29.6% in the dry season. The result an average annual spatial distribution of sediment yield increased by 7.73ton/ha yr -1 from (2000_2016). The calibration results for bothstream flow and sediment yield showed good agreement between observed and simulateddata with the coef icient of determination of 0.87 and 0.84, Nash-Sutclif e ef iciencyequality to 0.83 and 0.78 and percentage bias of -7.39% and -10.90%respectively. Andthe result for validation for both stream flow and sediment showed good result withCoef icient of determination equality to 0.83 and 0.80, Nash-Sutclif e ef iciency of 0.78and 0.75 and percentage bias of 7.09% and 3.95%. The result obtained fromthe model based on the above method was the mean annual sediment load at Genale DawaDamIIIwatershed increase from 2000 to 2016 for the reason that of the land uses change. Sotouse the Genale Dawa Dam III the land use management practices are neededinthefuture to prevent further increase of sediment yield of the watershed.

Keywords: Genale Dawa Dam III watershed, land use land cover change, SWAT, spatial distribution, sediment yield, stream flow

Procedia PDF Downloads 55

Authors: Ann Devitt, Mairead Brady, Markus Lamest, Stephen Gomez

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This study set out to explore the use of an online collaborative serious game for student learning in a postgraduate introductory marketing module. The simulation game aimed to bridge the theory-practice divide in marketing by allowing students to apply theory in a safe, simulated marketplace. This study addresses the following research questions: Does an online marketing simulation game engage students higher order cognitive skills? Does collaborative activity required develop students’ “soft” skills, such as communication and negotiation? What specific affordances of the online simulation promote learning? This qualitative case study took place in 2014 with 40 postgraduate students on a Business Masters Programme. The two-week intensive module combined lectures with collaborative activity on a marketing simulation game, MMX from Pearsons. The game requires student teams to compete against other teams in a marketplace and design a marketing plan to maximize key performance indicators. The data for this study comprise essays written by students after the module reflecting on their learning on the module. A thematic analysis was conducted of the essays using the following a priori theme sets: 6 levels of the cognitive domain of Blooms taxonomy; 5 principles of Cooperative Learning; affordances of simulation environments including experiential learning; motivation and engagement; goal orientation. Preliminary findings would strongly suggest that the game facilitated students identifying the value of theory in practice, in particular for future employment; enhanced their understanding of group dynamics and their role within that; and impacted very strongly, both positively and negatively on motivation. In particular the game mechanics of MMX, which hinges on the correct identification of a target consumer group, was identified as a key determinant of extrinsic and intrinsic motivation for learners. The findings also suggest that the situation of the simulation game within a broader module which required post-game reflection was valuable in identifying key learning of marketing concepts in both the positive and the negative experiences of the game.

Keywords: simulation, marketing, serious game, cooperative learning, bloom's taxonomy

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Authors: Saeeda Batool, Ather Maqsood Ahmed

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This study investigates the impact of public healthcare facilities and socio-economic circumstances on the status of child health in Pakistan. The complete analysis is carried out in correspondence with fourth and sixth millennium development goals. Further, the health variables chosen are also inherited from targeted indicators of the mentioned goals (MDGs). Trends in the Human Opportunity Index (HOI) for both health inequalities and coverage are analyzed using the Pakistan Social and Living Standards Measurement (PLSM) data set for 2001-02 to 2012-13 at the national and provincial level. To reveal the relative importance of each circumstance in achieving the targeted values for child health, Shorrocks decomposition is applied on HOI. The annual point average growth rate of HOI is used to simulate the time period for the achievement of target set by MDGs and universal access also. The results indicate an improvement in HOI for a reduction in child mortality rates from 52.1% in 2001-02 to 67.3% in 2012-13, which confirms the availability of healthcare opportunities to a larger segment of society. Similarly, immunization against measles and other diseases such as Diphtheria, Polio, Bacillus Calmette-Guerin (BCG), and Hepatitis has also registered an improvement from 51.6% to 69.9% during the period of study at the national level. On a positive note, no gender disparity has been found for child health indicators and that health outcome is mostly affected by the parental and geographical features and availability of health infrastructure. However, the study finds that this achievement has been uneven across provinces. Pakistan is not only lagging behind in achieving its health goals, disappointingly with the current rate of health care provision, but it will take many additional years to achieve its targets.

Keywords: socio-economic circumstances, unmet MDGs, public healthcare services, child and infant mortality

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

Abstract:

Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

Procedia PDF Downloads 143