Search results for: low cost technology

Authors: Rob Leslie, Taher Karimian

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The blockage of cross drainage structures is a risk that needs to be understood and managed or lessened through the design. A blockage is a random event, influenced by site-specific factors, which needs to be quantified for design. Under and overestimation of blockage can have major impacts on flood risk and cost associated with drainage structures. The importance of this matter is heightened for those projects located within sensitive lands. It is a particularly complex problem for large linear infrastructure projects (e.g., rail corridors) located within floodplains where blockage factors can influence flooding upstream and downstream of the infrastructure. The selection of the appropriate blockage factors for hydraulic modeling has been subject to extensive research by hydraulic engineers. This paper has been prepared to review the current Australian Rainfall and Runoff 2019 (ARR 2019) methodology for blockage assessment by applying this method to a transport corridor brownfield upgrade case study in New South Wales. The results of applying the method are also validated against asset data and maintenance records. ARR 2019 – Book 6, Chapter 6 includes advice and an approach for estimating the blockage of bridges and culverts. This paper concentrates specifically on the blockage of cross drainage structures. The method has been developed to estimate the blockage level for culverts affected by sediment or debris due to flooding. The objective of the approach is to evaluate a numerical blockage factor that can be utilized in a hydraulic assessment of cross drainage structures. The project included an assessment of over 200 cross drainage structures. In order to estimate a blockage factor for use in the hydraulic model, a process has been advanced that considers the qualitative factors (e.g., Debris type, debris availability) and site-specific hydraulic factors that influence blockage. A site rating associated with the debris potential (i.e., availability, transportability, mobility) at each crossing was completed using the method outlined in ARR 2019 guidelines. The hydraulic results inputs (i.e., flow velocity, flow depth) and qualitative factors at each crossing were developed into an advanced spreadsheet where the design blockage level for cross drainage structures were determined based on the condition relating Inlet Clear Width and L10 (average length of the longest 10% of the debris reaching the site) and the Adjusted Debris Potential. Asset data, including site photos and maintenance records, were then reviewed and compared with the blockage assessment to check the validity of the results. The results of this assessment demonstrate that the estimated blockage factors at each crossing location using ARR 2019 guidelines are well-validated with the asset data. The primary finding of the study is that the ARR 2019 methodology is a suitable approach for culvert blockage assessment that has been validated against a case study spanning a large geographical area and multiple sub-catchments. The study also found that the methodology can be effectively coded within a spreadsheet or similar analytical tool to automate its application.

Keywords: ARR 2019, blockage, culverts, methodology

Procedia PDF Downloads 373

Authors: Manushi Srivastava

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Introduction: Doctor’s role, and relation with respect to patient care is at the core of medical ethics. The rapid pace of medical advances along with increasing consumer awareness about their rights and hike in cost of effective health care demand a robust, transparent and patient-friendly medical care system. However, doctors’ role performance is still in the frame of activity-passivity model of Doctor-Patient Relationship (DPR) where doctors act as parent and use to instruct their patients, without their consensus that is not going to help in the 21st century. Thus the current situation is a new challenge for traditional doctor-patient relationship after the introduction of Consumer Protection Act (CPA) in medical profession and the same is evidenced by increasing cases of medical litigation. To strengthen this system of medical services, the doctor plays a vital role, and the same should be reviewed in the present context. Objective: To understand the opinion of consultants regarding medical negligence and effect of Consumer Protection Act in terms of current practices of patient care. Method: This is a cross-sectional study in which both quantitative and qualitative methods are applied. Total 69 consultants were selected from multi-specialty hospitals of densely populated Varanasi city catering a population of about 1.8 million. Two-stage sampling was used for selection of respondents. At the first stage, selection of major wards (Medicine, Surgery, Ophthalmology, Gynaecology, Orthopaedics, and Paediatrics) was carried out, which are more susceptible to medical negligence. At the second stage, selection of consultants from the respective wards was carried out. In-depth Interviews were conducted with the help of semi-structured schedule. Two case studies of medical negligence were also carried out as part of the qualitative study. Analysis: Data were analyzed with the help of SPSS software (21.0 trial version). Semi-structured research tool was used to know consultant’s opinion about the pattern of medical negligence cases, litigations and claims made by patient community and inclusion of government medical services in CPA. Statistical analysis was done to describe data, and non-parametric test was used to observe the association between the variables. Analysis of Verbatim was used in case-study. Findings and Conclusion: Majority (92.8%) of consultants felt changes in the behaviour of community (patient) after implementation of CPA, as it had increased awareness about their rights. Less than half of the consultants opined that Medical Negligence is an Unintentional act of doctors and generally occurs due to communication gap and behavioural problem between doctor and patients. Experienced consultants ( > 10 years) pointed out that unethical practice by doctors and mal-intention of patient to harass doctors were additional reasons of Medical Negligence. In-depth interview revealed that now patients’ community expects more transparency and hence they demand cafeteria approach in diagnosis and management of cases. Thus as study results, we propose ‘Agreement Model’ of DPR to re-ensure ethical practice in medical profession.

Keywords: doctors, communication, consumer protection act (CPA), medical error

Procedia PDF Downloads 164

Authors: Velimir Monty Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: Cansu Bozer, Saadet İrem Turgut

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Artificial intelligence (AI) has become one of the most important technologies of the digital age and is transforming many sectors, including education. The advantages offered by AI, such as automation, personalised learning, and data analytics, create new opportunities for both teachers and students in education systems. Preschool education plays a fundamental role in the cognitive, social, and emotional development of children. In this period, the foundations of children's creative thinking, problem-solving, and critical thinking skills are laid. Educational technologies, especially artificial intelligence-based applications, are thought to contribute to the development of these skills. For example, artificial intelligence-supported digital learning tools can support learning processes by offering activities that can be customised according to the individual needs of each child. However, the successful use of artificial intelligence-based applications in preschool education can be realised under the guidance of teachers who have the right knowledge about this technology. Therefore, it is of great importance to measure preschool teachers' awareness levels of artificial intelligence and to understand which variables affect this awareness. The aim of this study is to measure preschool teachers' awareness levels of artificial intelligence and to determine which factors are related to this awareness. In line with this purpose, teachers' level of knowledge about artificial intelligence, their thoughts about the role of artificial intelligence in education, and their attitudes towards artificial intelligence will be evaluated. The study will be conducted with 100 teachers working in Turkey using a descriptive survey model. In this context, ‘Artificial Intelligence Awareness Level Scale for Teachers’ developed by Ferikoğlu and Akgün (2022) will be used. The collected data will be analysed using SPSS (Statistical Package for the Social Sciences) software. Descriptive statistics (frequency, percentage, mean, standard deviation) and relationship analyses (correlation and regression analyses) will be used in data analysis. As a result of the study, the level of artificial intelligence awareness of preschool teachers will be determined, and the factors affecting this awareness will be identified. The findings obtained will contribute to the determination of studies that can be done to increase artificial intelligence awareness in preschool education.

Keywords: education, child development, artificial intelligence, preschool teachers

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Authors: Jens Hagman, Jenny Janhager Stier, Ellen Olausson, Anne Y. Faxer, Ana Magazinius

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Sweden has the second highest electric vehicle (plug-in hybrid and battery electric vehicle) sales per capita in Europe but in relation to sales of internal combustion engine electric vehicles sales are still minuscular (< 4%). Much research effort has been placed on various technical and user focused barriers and enablers for adoption of electric vehicles. Less effort has been placed on investigating the retail (dealership-customer) sales process of vehicles in general and electric vehicles in particular. Arguably, no one ought to be better informed about needs and desires of potential electric vehicle buyers than car salesmen, originating from their daily encounters with customers at the dealership. The aim of this paper is to explore the conditions of selling electric vehicle from a car salesmen’s perspective. This includes identifying barriers and enablers for electric vehicle sales originating from internal (dealership and brand) and external (customer, government) sources. In this interview study five car brands (manufacturers) that sell both electric and internal combustion engine vehicles have been investigated. A total of 15 semi-structured interviews have been conducted (three per brand, in rural and urban settings and at different dealerships). Initial analysis reveals several barriers and enablers, experienced by car salesmen, which influence electric vehicle sales. Examples of as reported by car salesmen identified barriers are: -Electric vehicles earn car salesmen less commission on average compared to internal combustion engine vehicles. -It takes more time to sell and deliver an electric vehicle than an internal combustion engine vehicle. -Current leasing contracts entails relatively low second-hand value estimations for electric vehicles and thus a high leasing fee, which negatively affects the attractiveness of electric vehicles for private consumers in particular. -High purchasing price discourages many consumers from considering electric vehicles. -The education and knowledge level of electric vehicles differs between car salesmen, which could affect their self-confidence in meeting well prepared and question prone electric vehicle buyers. Examples of identified enablers are: -Company car tax regulation promotes sales of electric vehicles; in particular, plug-in hybrid electric vehicles are sold extensively to companies (up to 95 % of sales). -Low operating cost of electric vehicles such as fuel and service is an advantage when understood by consumers. -The drive performance of electric vehicles (quick, silent and fun to drive) is attractive to consumers. -Environmental aspects are considered important for certain consumer groups. -Fast technological improvements, such as increased range are opening up a wider market for electric vehicles. -For one of the brands; attractive private lease campaigns have proved effective to promote sales. This paper gives insights of an important but often overlooked aspect for the diffusion of electric vehicles (and durable products in general); the interaction between car salesmen and customers at the critical acquiring moment. Extracted through interviews with multiple car salesmen. The results illuminate untapped potential for sellers (salesmen, dealerships and brands) to mitigating sales barriers and strengthening sales enablers and thus becoming a more important actor in the electric vehicle diffusion process.

Keywords: customer barriers, electric vehicle promotion, sales of electric vehicles, interviews with car salesmen

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Authors: Jianli Jiang, Bai-Chen Xie

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The climate issue has aroused global concern. Achieving sustainable development is a good path for countries to mitigate environmental and climatic pressures, although there are many difficulties. The first step towards sustainable development is to evaluate the environmental efficiency of the energy industry with proper methods. The power sector is a major source of CO2, SO2, and NOx emissions. Evaluating the environmental efficiency (EE) of power systems is the premise to alleviate the terrible situation of energy and the environment. Data Envelopment Analysis (DEA) has been widely used in efficiency studies. However, measuring the efficiency of a system (be it a nation, region, sector, or business) is a challenging task. The classic DEA takes the decision-making units (DMUs) as independent, which neglects the interaction between DMUs. While ignoring these inter-regional links may result in a systematic bias in the efficiency analysis; for instance, the renewable power generated in a certain region may benefit the adjacent regions while the SO2 and CO2 emissions act oppositely. This study proposes a spatial network DEA (SNDEA) with a slack measure that can capture the spatial spillover effects of inputs/outputs among DMUs to measure efficiency. This approach is used to study the EE of China's power system, which consists of generation, transmission, and distribution departments, using a panel dataset from 2014 to 2020. In the empirical example, the energy and patent inputs, the undesirable CO2 output, and the renewable energy (RE) power variables are tested for a significant spatial spillover effect. Compared with the classic network DEA, the SNDEA result shows an obvious difference tested by the global Moran' I index. From a dynamic perspective, the EE of the power system experiences a visible surge from 2015, then a sharp downtrend from 2019, which keeps the same trend with the power transmission department. This phenomenon benefits from the market-oriented reform in the Chinese power grid enacted in 2015. The rapid decline in the environmental efficiency of the transmission department in 2020 was mainly due to the Covid-19 epidemic, which hinders economic development seriously. While the EE of the power generation department witnesses a declining trend overall, this is reasonable, taking the RE power into consideration. The installed capacity of RE power in 2020 is 4.40 times that in 2014, while the power generation is 3.97 times; in other words, the power generation per installed capacity shrank. In addition, the consumption cost of renewable power increases rapidly with the increase of RE power generation. These two aspects make the EE of the power generation department show a declining trend. Incorporation of the interactions among inputs/outputs into the DEA model, this paper proposes an efficiency evaluation method on the basis of the DEA framework, which sheds some light on efficiency evaluation in regional studies. Furthermore, the SNDEA model and the spatial DEA concept can be extended to other fields, such as industry, country, and so on.

Keywords: spatial network DEA, environmental efficiency, sustainable development, power system

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Authors: MD Mashiur Rahman, Muhammad Arshadul Haque

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Emerging conservation agriculture (CA) is an option for improving soil health and maintaining environmental sustainability for intensive agriculture, especially in the tropical climate. Three years lengthy research experiment was performed in arid climate from 2018 to 2020 at research field of Bangladesh Agricultural Research Station (RARS)F, Jamalpur (soil texture belongs to Agro-Ecological Zone (AEZ)-8/9, 24˚56'11''N latitude and 89˚55'54''E longitude and an altitude of 16.46m) to evaluate the effect of CA approaches on energy use efficiency and a streamlined life cycle greenhouse gas (GHG) emission of wheat production. For this, the conservation tillage practices (strip tillage (ST) and minimum tillage (MT)) were adopted in comparison to the conventional farmers' tillage (CT), with retained a fixed level (30 cm) of residue retention. This study examined the relationship between energy consumption and life cycle greenhouse gas (GHG) emission of wheat cultivation in Jamalpur region of Bangladesh. Standard energy equivalents megajoules (MJ) were used to measure energy from different inputs and output, similarly, the global warming potential values for the 100-year timescale and a standard unit kilogram of carbon dioxide equivalent (kg CO₂eq) was used to estimate direct and indirect GHG emissions from the use of on-farm and off-farm inputs. Farm efficiency analysis tool (FEAT) was used to analyze GHG emission and its intensity. A non-parametric data envelopment (DEA) analysis was used to estimate the optimum energy requirement of wheat production. The results showed that the treatment combination having MT with optimum energy inputs is the best suit for cost-effective, sustainable CA practice in wheat cultivation without compromising with the yield during the dry season. A total of 22045.86 MJ ha⁻¹, 22158.82 MJ ha⁻¹, and 23656.63 MJ ha⁻¹ input energy for the practice of ST, MT, and CT was used in wheat production, and output energy was calculated as 158657.40 MJ ha⁻¹, 162070.55 MJ ha⁻¹, and 149501.58 MJ ha⁻¹, respectively; where energy use efficiency/net energy ratio was found to be 7.20, 7.31 and 6.32. Among these, MT is the most effective practice option taken into account in the wheat production process. The optimum energy requirement was found to be 18236.71 MJ ha⁻¹ demonstrating for the practice of MT that if recommendations are followed, 18.7% of input energy can be saved. The total greenhouse gas (GHG) emission was calculated to be 2288 kgCO₂eq ha⁻¹, 2293 kgCO₂eq ha⁻¹ and 2331 kgCO₂eq ha⁻¹, where GHG intensity is the ratio of kg CO₂eq emission per MJ of output energy produced was estimated to be 0.014 kg CO₂/MJ, 0.014 kg CO₂/MJ and 0.015 kg CO₂/MJ in wheat production. Therefore, CA approaches ST practice with 30 cm residue retention was the most effective GHG mitigation option when the net life cycle GHG emission was considered in wheat production in the silt clay loam soil of Bangladesh. In conclusion, the CA approaches being implemented for wheat production involving MT practice have the potential to mitigate global warming potential in Bangladesh to achieve soil carbon footprint, where the life cycle assessment approach needs to be applied to a more diverse range of wheat-based cropping systems.

Keywords: conservation agriculture and tillage, energy use efficiency, life cycle GHG, Bangladesh

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Authors: Jeffrey Chase

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Historically the profession of Occupational Therapy was closely tied to the treatment of those suffering from mental illness; more recently, and especially in the U.S., the percentage of OTs identifying as working in the mental health area has declined significantly despite the estimate that by 2020 behavioral health disorders will surpass physical illnesses as the major cause of disability worldwide. In the U.S. less than 10% of OTs identify themselves as working with the mentally ill and/or practicing in mental health settings. Such a decline has implications for both those suffering from mental illness and the profession of Occupational Therapy. One reason cited for the decline of OT in mental health has been the limited research in the discipline addressing mental health practice. Despite significant advances in technology and growth in the field of neuroscience, major institutions and funding sources such as the National Institute of Mental Health (NIMH) have noted that research into the etiology and treatment of mental illness have met with limited success over the past 25 years. One major reason posited by NIMH is that research has been limited by how we classify individuals, that being mostly on what is observable. A new classification system being developed by NIMH, the Research Domain Criteria (RDoc), has the goal to look beyond just descriptors of disorders for common neural, genetic, and physiological characteristics that cut across multiple supposedly separate disorders. The hope is that by classifying individuals along RDoC measures that both reliability and validity will improve resulting in greater advances in the field. As a result of this change NIH and NIMH will prioritize research funding to those projects using the RDoC model. Multiple disciplines across many different setting will be required for RDoC or similar classification systems to be developed. During this shift in research methodology OT has an opportunity to reassert itself into the research and treatment of mental illness, both in developing new ways to more validly classify individuals, and to document the legitimacy of previously ill-defined and validated disorders such as sensory integration.

Keywords: global mental health and neuroscience, research opportunities for ot, greater integration of ot in mental health research, research and funding opportunities, research domain criteria (rdoc)

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Authors: Selin Tosun

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The improvements in technology have started to transform the way we live, work, play, and commute in our cities. The emerging smart city understanding has been paving the way for more efficient, more useful, and more profitable cities. Smart sensors, smart lighting, smart waste, water and electricity management, smart transportation and communication systems are introduced to cities at a rapid pace. In today's world, innovation is often correlated with start-up companies and technological pioneers seeking broader economic objectives such as production and competitiveness. The government's position is primarily that of an enabler, with creativity mostly coming from the private sector. The paper argues that to achieve sustainable development, the ways in which smart and sustainable city approaches are being applied to cities need to be redefined. The research aims to address common discussions in the discourse of smart and sustainable cities criticizing the priority of lifestyle sterilization over human-centered sustainable interventions and social innovation strategies. The dichotomy between the fact that smart cities are mostly motivated by the competitive global market and the fact that the delocalization is, in fact, their biggest problem in the way of becoming authentic, sustainable cities is the main challenge that we face today. In other words, the key actors in smart cities have different and somewhat conflicting interests and demands. By reviewing the roles of the public and private actors in smart city making, the paper aspires to reconceptualize the understanding of “smartness” in achieving sustainable development in which the “smartness” is understood as a multi-layered complex phenomenon that can be channeled through different dynamics. The case cities around the world are explored and compared in terms of their technological innovations, governance and policy innovations, public-private stakeholder relationships, and the understanding of the public realm. The study aims to understand the current trends and general dynamics in the field, key issues that are being addressed, the scale that is preferred to reflect upon and the projects that are designed for the particular issues.

Keywords: smart city, sustainable development, technological innovation, social innovation

Procedia PDF Downloads 204

Authors: Kuo-Dung Chiou, Yen-Xue Chen, Chia-Ying Chang

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This study uses AI technology to establish an expert system and establish a fruit appearance database for pineapples and custard apples. It collects images based on appearance defects and fruit maturity. It uses deep learning to detect the location of the fruit and can detect the appearance of the fruit in real-time. Flaws and maturity. In addition, a hyperspectral camera was used to scan pineapples and custard apples, and the light reflection at different frequency bands was used to find the key frequency band for pectin softening in post-ripe fruits. Conducted a large number of multispectral image collection and data analysis to establish a database of Pineapple Custard Apple and Big Eyed Custard Apple, which includes a high-definition color image database, a hyperspectral database in the 377~1020 nm frequency band, and five frequency band images (450, 500, 670, 720, 800nm) multispectral database, which collects 4896 images and manually labeled ground truth; 26 hyperspectral pineapple custard apple fruits (520 images each); multispectral custard apple 168 fruits (5 images each). Using the color image database to train deep learning Yolo v4's pre-training network architecture and adding the training weights established by the fruit database, real-time detection performance is achieved, and the recognition rate reaches over 97.96%. We also used multispectral to take a large number of continuous shots and calculated the difference and average ratio of the fruit in the 670 and 720nm frequency bands. They all have the same trend. The value increases until maturity, and the value will decrease after maturity. Subsequently, the sub-bands will be added to analyze further the numerical analysis of sugar content and moisture, and the absolute value of maturity and the data curve of maturity will be found.

Keywords: hyperspectral image, fruit firmness, deep learning, automatic detection, automatic measurement, intelligent labor saving

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Authors: Kebron Abich Asnake

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The outbreak of COVID-19 has had far-reaching socio-economic consequences globally, and Ethiopia is no exception. This abstract provides a summary of a research study on the socio-economic impact of COVID-19 in Ethiopia. The study analyzes the health impact, economic repercussions, social consequences, government response measures, and opportunities for post-crisis recovery. In terms of health impact, the research explores the spread and transmission of the virus, the capacity and response of the healthcare system, and the mortality rate, with a focus on vulnerable populations. The economic impact analysis entails investigating the contraction of the GDP, employment and income loss, disruption in key sectors such as agriculture, tourism, and manufacturing, and the specific implications for small and medium-sized enterprises (SMEs), foreign direct investment, and remittances. The social impact section looks at the disruptions in education and the digital divide, food security and nutrition challenges, increased poverty and inequality, gender-based violence, and mental health issues. The research also examines the measures taken by the Ethiopian government, including health and safety regulations, economic stimulus packages, social protection programs, and support for vulnerable populations. Furthermore, the study outlines long-term recovery prospects, social cohesion, and community resilience challenges. It highlights the need to strengthen the healthcare system and finds a balance between health and economic priorities. The research concludes by presenting recommendations for policy-makers and stakeholders, emphasizing opportunities for post-crisis recovery such as diversification of the economy, enhanced healthcare infrastructure, investment in digital infrastructure and technology, and support for domestic tourism and local industries. This research provides valuable insights into the socio-economic impact of COVID-19 in Ethiopia, offering a comprehensive analysis of the challenges faced and potential pathways towards recovery.

Keywords: impact, covid, ethiopia, health

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Authors: Ariane Plaisance, Holly O. Witteman, Patrick Michel Archambault

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Upon admission to an intensive care unit (ICU), all patients should discuss their wishes concerning life-sustaining interventions (e.g., cardiopulmonary resuscitation (CPR)). Without such discussions, interventions that prolong life at the cost of decreasing its quality may be used without appropriate guidance from patients. We employed user-centered design to adapt an existing decision aid (DA) about CPR to create a novel wiki-based DA adapted to the context of a single ICU and tailored to individual patient’s risk factors. During Phase 1, we conducted three weeks of ethnography of the decision-making context in our ICU to identify clinician and patient needs for a decision aid. During this time, we observed five dyads of intensivists and patients discussing their wishes concerning life-sustaining interventions. We also conducted semi-structured interviews with the attending intensivists in this ICU. During Phase 2, we conducted three rounds of rapid prototyping involving 15 patients and 11 other allied health professionals. We recorded discussions between intensivists and patients and used a standardized observation grid to collect patients’ comments and sociodemographic data. We applied content analysis to field notes, verbatim transcripts and the completed observation grids. Each round of observations and rapid prototyping iteratively informed the design of the next prototype. We also used the programming architecture of a wiki platform to embed the GO-FAR prediction rule programming code that we linked to a risk graphics software to better illustrate outcome risks calculated. During Phase I, we identified the need to add a section in our DA concerning invasive mechanical ventilation in addition to CPR because both life-sustaining interventions were often discussed together by physicians. During Phase II, we produced a context-adapted decision aid about CPR and mechanical ventilation that includes a values clarification section, questions about the patient’s functional autonomy prior to admission to the ICU and the functional decline that they would judge acceptable upon hospital discharge, risks and benefits of CPR and invasive mechanical ventilation, population-level statistics about CPR, a synthesis section to help patients come to a final decision and an online calculator based on the GO-FAR prediction rule. Even though the three rounds of rapid prototyping led to simplifying the information in our DA, 60% (n= 3/5) of the patients involved in the last cycle still did not understand the purpose of the DA. We also identified gaps in the discussion and documentation of patients’ preferences concerning life-sustaining interventions (e.g.,. CPR, invasive mechanical ventilation). The final version of our DA and our online wiki-based GO-FAR risk calculator using the IconArray.com risk graphics software are available online at www.wikidecision.org and are ready to be adapted to other contexts. Our results inform producers of decision aids on the use of wikis and user-centered design to develop DAs that are better adapted to users’ needs. Further work is needed on the creation of a video version of our DA. Physicians will also need the training to use our DA and to develop shared decision-making skills about goals of care.

Keywords: ethnography, intensive care units, life-sustaining therapies, user-centered design

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Md. Akiz Uddin

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This research attempted to identify the determining factors that extensively persuaded customers of the First Security Islamic Bank Limited (FSIBL) to open accounts and their perception and satisfaction level towards it. Initially, a theoretical model was established based on existing literature reviews. After that, a self-administered structured questionnaire was developed, and data were collected from 180 customers of the FSIBL of Bangladesh using purposive sampling technique. The collected data were later analyzed through a statistical software. Structural Equation Modelling (SEM) was used to verify the model of the study and test the hypotheses. The study particularly examined the determinants of opening accounts, customers’ perception and their satisfaction level towards the bank on several factors like the bank’s compliance with Shariah law, use of modern technology, assurance, reliability, empathy, profitability, and responsiveness. To examine the impact of religious belief on being FSIBL clients, the study also investigates non-Muslim clients’ perception about FSIBL. The study focused on FSIBL customers only from five branches of Dhaka city. The study found that the religious beliefs is the most significant factors for Muslim customers for considering FSIBL to open an account, and they are satisfied with the services, too. However, for non-Muslim customers, other benefits like E-banking, various user-friendly services are the most significant factors for choosing FSIBL. Their satisfaction level is also statistically significant. Furthermore, even if the non- Muslim customers didn’t consider religious beliefs as determinant factors for choosing FSIBL, the respondents informed that they have trust that people who believe in shariah law are more reliable to keep money with them. These findings open up the avenue for future researchers to conduct more study in this area through employing a larger sample size and more branches and extending the current model by incorporating new variables. The study will be an important addition to the potentials of Islamic banking system, literature of service quality and customer satisfaction level, particularly in the success of Islamic banking system in Bangladesh.

Keywords: islamic banking, customers’ satisfaction, customers’ perception, shariah law

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Authors: Ariba Siddiqui, Amber Khan

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The need for bio-implantable devices in the field of medical sciences has been increasing day by day; however, the charging of these devices is a major issue. Batteries, a very common method of powering the implants, have a limited lifetime and bulky nature. Therefore, as a replacement of batteries, acoustic power transfer (APT) technology is being accepted as the most suitable technique to wirelessly power the medical implants in the present scenario. The basic model of APT consists of piezoelectric transducers that work on the principle of converse piezoelectric effect at the transmitting end and direct piezoelectric effect at the receiving end. This paper provides mechanistic insight into the parameters affecting the design and efficient working of acoustic power transfer systems. The optimum design considerations have been presented that will help to compress the size of the device and augment the intensity of the pressure wave. A COMSOL model of the PZT (Lead Zirconate Titanate) transducer was developed. The model was simulated and analyzed on a frequency spectrum. The simulation results displayed that the efficiency of these devices is strongly dependent on the frequency of operation, and a wrong choice of the operating frequency leads to the high absorption of acoustic field inside the tissue (medium), poor power strength, and heavy transducers, which in effect influence the overall configuration of the acoustic systems. Considering all the tradeoffs, the simulations were performed again by determining an optimum frequency (900 kHz) that resulted in the reduction of the transducer's thickness to 1.96 mm and augmented the power strength with an intensity of 432 W/m². Thus, the results obtained after the second simulation contribute to lesser attenuation, lightweight systems, high power intensity, and also comply with safety limits provided by the U.S Food and Drug Administration (FDA). It was also found that the chosen operating frequency enhances the directivity of the acoustic wave at the receiver side.

Keywords: acoustic power, bio-implantable, COMSOL, Lead Zirconate Titanate, piezoelectric, transducer

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Authors: Amir M. Shikhli, Refaat H. Abdel-Razek, Salaheddine Bendak

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Innovation is considered to be one of the key factors that influence long-term success of any company. The problem of many organizations in developing countries is trying to implement innovation without a strong basis within the organizational culture to support it. The objective of this study is to assess the effects of organizational culture on innovation in one of the biggest information technology organizations in UAE, Injazat Data System. First, an Organizational Culture Assessment Instrument (OCAI) was used as a survey and Competing Value Framework as a model to analyze the existing culture within the organization and determine its characteristics. Following that, a modified version of the Community Innovation Survey (CIS) was used to determine innovation types introduced by the organization. Then multiple linear regression analysis was used to find out the effects of existing organizational culture on innovation. Results show that existing organizational culture is composed of a combination of Hierarchy (29.4%), Clan (25.8%), Market (24.9%) and Adhocracy (19.9%). Results of the second survey show that the organization focuses on organizational innovation (26.8%) followed by market and product innovations (25.6%) and finally process innovation (22.0%). Regression analysis results reveal that for each innovation type there is a recommended combination of the four culture types. For product innovation, the combination is 47.4% Clan, 17.9% Adhocracy, 1.0% Market and 33.3% Hierarchy; for process innovation it is 19.7% Clan, 45.2% Adhocracy, 32.0% Market and 3.1% Hierarchy; for organizational innovation the combination is 5.4% Clan, 32.7% Adhocracy, 6.0% Market and 55.9% Hierarchy; and for market innovation it is 25.5% Clan, 42.6% Adhocracy, 32.6% Market and 8.4% Hierarchy. Based on these recommended combinations, this study suggests two ways to enhance the innovation culture in the organization. First, if the management decides on the innovation type to be enhanced, a comparison between the existing culture and the recommended combination of selected innovation types will lead to difference in percentages of each culture type. Then further analysis should show how to modify the existing culture to match the recommended combination. Second, if the innovation type is not selected, but the management wants to enhance innovation culture in the organization, the difference in percentages of each culture type will lead to finding out the recommended combination of culture types that gives the narrowest gap between existing culture and recommended combination.

Keywords: developing countries, organizational culture, innovation types, product innovation, process innovation, organizational innovation, marketing innovation

Procedia PDF Downloads 277

Authors: Lok Yi Joyce Poon

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China's mobile payment market has boomed in the past few years. WeChat (Chinese name as Weixin) owned by Tencent is known as the fastest growing all-in-one social messaging platforms. The company has launched the WeChat Pay in 2013, in which users can link their credit card to their user account and make payments within the app’s built in digital wallet. WeChat Payment is a one-stop payment tool that can provide a seamless online experience for the shoppers to transfer money between WeChat users (peer-to-peer) and make payments online by scanning a QR code, a prominent facilitator for transactions in WeChat, to complete the payment with the app without directing the users to the external websites. The aims of this study are to examine the effectiveness of WeChat mobile payment in China as well as the impacts of the China teen’s online purchasing behavior since the establishment of WeChat Payment. The research method of this study is conducted by both online survey on Sojump, a popular online survey platform in China. A total of 120 respondents among 18 to 25 teens in China completed the survey. Data sources included participants’ response to an end-of-session questionnaire, encompassing with the types of multiple choice, open-ended questions. To have an in-depth analysis, a face-to-face interview with a Chinese teen who is a frequent user of the WeChat Pay. The main finding of the study shows that the majority of the teenagers frequently use the WeChat payment tool because of its convenience, user-friendliness and the scenarios offered within the WeChat Wallet. The respondents claimed that they will settle the bills in their daily lives via WeChat Pay. However, the respondents in the age group of 40 or above will not use the WeChat Pay due to the security concern and they do not see the app as a platform for commercial activities like online shopping. Throughout the study, it is recommended WeChat should put more efforts on the security issue and improve the payment technology by adopting the near-field communication terminals instead of requiring users to scan QR codes before they complete the transaction.

Keywords: digital wallet, mobile payment, online purchasing behavior, WeChat Pay

Procedia PDF Downloads 395

Authors: Paula Costa, Ana Picado, Filomena Pinto, Justina Catarino

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Environmental impact associated with large scale shale gas development is of major concern to the public, policy makers and other stakeholders. To assess this impact on the atmosphere, it is important to monitoring ambient air quality prior to and during all shale gas operation stages. Baseline observations can provide a standard of the pre-shale gas development state of the environment. The lack of baseline concentrations was identified as an important knowledge gap to assess the impact of emissions to the air due to shale gas operations. In fact baseline monitoring of air quality are missing in several regions, where there is a strong possibility of future shale gas exploration. This makes it difficult to properly identify, quantify and characterize environmental impacts that may be associated with shale gas development. The implementation of a baseline air monitoring program is imperative to be able to assess the total emissions related with shale gas operations. In fact, any monitoring programme should be designed to provide indicative information on background levels. A baseline air monitoring program should identify and characterize targeted air pollutants, most frequently described from monitoring and emission measurements, as well as those expected from hydraulic fracturing activities, and establish ambient air conditions prior to start-up of potential emission sources from shale gas operations. This program has to be planned for at least one year accounting for ambient variations. In the literature, in addition to GHG emissions of CH4, CO2 and nitrogen oxides (NOx), fugitive emissions from shale gas production can release volatile organic compounds (VOCs), aldehydes (formaldehyde, acetaldehyde) and hazardous air pollutants (HAPs). The VOCs include a.o., benzene, toluene, ethyl benzene, xylenes, hexanes, 2,2,4-trimethylpentane, styrene. The concentrations of six air pollutants (ozone, particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), sulphur oxides (SOx), and lead) whose regional ambient air levels are regulated by the Environmental Protection Agency (EPA), are often discussed. However, the main concern in the emissions to air associated to shale gas operations, seems to be the leakage of methane. Methane is identified as a compound of major concern due to its strong global warming potential. The identification of methane leakage from shale gas activities is complex due to the existence of several other CH4 sources (e.g. landfill, agricultural activity or gas pipeline/compressor station). An integrated monitoring study of methane emissions may be a suitable mean of distinguishing the contribution of different sources of methane to ambient levels. All data analysis needs to be carefully interpreted taking, also, into account the meteorological conditions of the site. This may require the implementation of a more intensive monitoring programme. So, it is essential the development of a low-cost sampling strategy, suitable for establishing pre-operations baseline data as well as an integrated monitoring program to assess the emissions from shale gas operation sites. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640715.

Keywords: air emissions, baseline, green house gases, shale gas

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Authors: Yoftahe Nigussie

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This research explores the implementation of a vapor absorption refrigeration system (VARS) in mini-bus cars to enhance air conditioning efficiency. The conventional vapor compression refrigeration system (VCRS) in vehicles relies on mechanical work from the engine, leading to increased fuel consumption. The proposed VARS aims to utilize waste heat and exhaust gas from the internal combustion engine to cool the mini-bus cabin, thereby reducing fuel consumption and atmospheric pollution. The project involves two models: Model 1, a two-fluid vapor absorption system (VAS), and Model 2, a three-fluid VAS. Model 1 uses ammonia (NH₃) and water (H₂O) as refrigerants, where water absorbs ammonia rapidly, producing a cooling effect. The absorption cycle operates on the principle that absorbing ammonia in water decreases vapor pressure. The ammonia-water solution undergoes cycles of desorption, condensation, expansion, and absorption, facilitated by a generator, condenser, expansion valve, and absorber. The objectives of this research include reducing atmospheric pollution, minimizing air conditioning maintenance costs, lowering capital costs, enhancing fuel economy, and eliminating the need for a compressor. The comparison between vapor absorption and compression systems reveals advantages such as smoother operation, fewer moving parts, and the ability to work at lower evaporator pressures without affecting the Coefficient of Performance (COP). The proposed VARS demonstrates potential benefits for mini-bus air conditioning systems, providing a sustainable and energy-efficient alternative. By utilizing waste heat and exhaust gas, this system contributes to environmental preservation while addressing economic considerations for vehicle owners. Further research and development in this area could lead to the widespread adoption of vapor absorption technology in automotive air conditioning systems.

Keywords: room, zone, space, thermal resistance

Procedia PDF Downloads 77

Authors: Nana Katsitadze, Tamar Atanelishvili, Mariam Kutateladze, Alexandre Tushishvili

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In the modern world, tourism has emerged as one of the most powerful economic sectors, and due to its high economic performance, it is attractive to the countries with various levels of economic development. The purpose of the present paper, dedicated to discussing the current problems of tourism development, is to find ways which will contribute to bringing more benefits to the country from the sector. Georgia has been successfully developing leisure tourism for the last ten years, and at the next stage of development business, tourism gains particular importance for Georgia as a means of mitigating the negative socio-economic effects caused by the seasonality of tourism and as a high-cost tourism market. Therefore, the object of the paper is to study the factors that contribute to the development of business tourism. The paper uses the research methods such as system analysis, synthesis, analogy, as well as historical, comparative, economic, and statistical methods of analysis. The information base for the research is made up of the statistics on the functioning of the tourism market of Georgia and foreign countries as well as official data provided by international organizations in the field of tourism. Based on the experience of business tourism around the world and identifying the successful start of business tourism development in Georgia and its causing factors, a business tourism development model for Georgia has been developed. The model might be useful as a methodological material for developing a business tourism development concept for the countries with limited financial resources but rich in tourism resources like Georgia. On the initial stage of development (in absence of conventional centers), the suggested concept of business tourism development involves organizing small and medium-sized meetings both in large cities and in regions by using high-class hotel infrastructure and event management services. Relocation of small meetings to the regions encourages inclusive development of the sector based on increasing the awareness of these regions as tourist sites as well as the increase in employment and sales of other tourism or consumer products. Business tourism increases the number of hotel visitors in the non-seasonal period and improves hotel performance indicators, which enhances the attractiveness of investing in the hotel business. According to the present concept of business tourism development, at the initial stage, development of business tourism is based on the existing markets, including internal market, neighboring markets and the markets of geographically relatively near countries and at the next stage, the concept involves generating tourists from other relatively distant target markets. As a result, by gaining experience in business tourism, enhancing professionalism, increasing awareness and stimulating infrastructure development, the country will prepare the basis to move to a higher stage of tourism development. In addition, the experience showed that for attracting large customers, peculiarities of the field require activation of state policy and active use of marketing mechanisms and tools of the state.

Keywords: hotel industry development, MICE model, MICE strategy, MICE tourism in Georgia

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Authors: Jennifer Fane, Mike Gray, Melissa Sager

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Children with diagnosed or suspected learning disabilities frequently experience significant skill gaps in foundational learning areas such as reading, writing, and math. Remedial one-to-one instruction is a highly effective means of supporting children with learning differences in building these foundational skills and closing the learning gap between them and their same-age peers. However, due to the learning challenges children with learning disabilities face, and ensuing challenges with self-confidence, many children with learning differences struggle with motivation and self-regulation within remedial one-to-one learning environments - despite the benefits of these sessions. Socially Assistive Robots (SARs) are an innovative educational technology tool that has been trialled in a range of educational settings to support diverse learning needs. Yet, little is known about the impact of SARs on the learning of children with learning differences in a one-to-one remedial instructional setting. This study sought to explore the impact of SARs on the engagement of children (n=9) with learning differences attending one-to-one remedial instruction sessions at a non-profit remedial education provider. The study used a mixed-methods design to explore learner engagement during learning tasks both with and without the use of a SAR to investigate how the use of SARs impacts student learning. The study took place over five weeks, with each session within the study followed the same procedure with the SAR acting as a teaching assistant when in use. Data from the study included analysis of time-sample video segments of the instructional sessions, instructor recorded information about the student’s progress towards their session learning goal and student self-reported mood and energy levels before and after the session. Analysis of the findings indicates that the use of SARs resulted in fewer instances of off-task behaviour and less need for instructor re-direction during learning tasks, allowing students to work in more sustained ways towards their learning goals. This initial research indicates that the use of SARs does have a material and measurable impact on learner engagement for children with learning differences and that further exploration of the impact of SARs during one-to-one remedial instruction is warranted.

Keywords: engagement, learning differences, learning disabilities, instruction, social robotics.

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Authors: Babajide Olufemi Diyaolu

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The opportunity provided by advances in technology as regards sports betting is so numerous that even at one's comfort, with the use of a phone, Nigerian youth are found engaging in all kinds of betting. Today it is more difficult to differentiate a true fan as there are quite a number of them that became fans as a result of betting on live games. This study investigated the influence of online sports events on betting among Nigerian youth. A descriptive survey research design was used, and the population consists of all Nigerian youth that engages in betting and live within the southwest zone of Nigeria. A simple random sampling technique was used to pick three states from the southwest zone of Nigeria. Two thousand five hundred respondents comprising males and female were sampled from the three states. A structured questionnaire on online sports event contribution to sports betting (OSECSB) was used. The Instrument consists of three sections. Section A seeks information on the demographic data of the respondents. Section B seeks information on online sports events, while section C is used to extract information on sports betting. The modified instrument, which consists of 14 items, has a reliability coefficient of 0.74. The hypothesis was tested at 0.05 significance level. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts, percentage and pie chart, and inferential statistics of multiple regressions. The findings of this study revealed that online sports betting is a significant predictor of an increase in sports betting among Nigerian youth. The media and television, as well as globalization and the internet coupled with social media and various online platforms, have all contributed to the immense increase in sports betting. The increase in the advertisement of the betting platform during live matches, especially football, is becoming more alarming. In most organized international events, the media attention, as well as sponsorship right, are now been given to one or two betting platforms. There is a need for all stakeholders to put in place school-based intervention programs to reorientate our youth about the consequences of addiction to betting. Such programs must include meta-analyses and emotional control towards sports betting.

Keywords: betting platform, Nigerian fans, Nigerian youth, sports betting

Procedia PDF Downloads 79

Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

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Unconventional oil reservoirs have the characteristics of strong heterogeneity and poor injectability, and traditional chemical flooding technology is not effective in such reservoirs; polymer flooding in the production of heavy oil reservoirs is difficult to handle produced fluid and easy to block oil wells, etc. Therefore, a viscoelastic fluid flooding system with good adaptability, low interfacial tension, plugging, and diverting capabilities was studied. The viscosity, viscoelasticity, surface/interfacial activity, wettability, emulsification, and oil displacement performance of the anionic Gemini surfactant flooding system were studied, and the adaptability of the system to the reservoir environment was evaluated. The oil displacement effect of the system in low-permeability and high-permeability (heavy oil) reservoirs was investigated, and the mechanism of the system to enhance water flooding recovery was discussed. The results show that the system has temperature resistance and viscosity increasing performance (65℃, 4.12mPa•s), shear resistance and viscoelasticity; at a lower concentration (0.5%), the oil-water interfacial tension can be reduced to ultra-low (10-3mN/m); has good emulsifying ability for heavy oil, and is easy to break demulsification (4.5min); has good adaptability to reservoirs with high salinity (30000mg/L). Oil flooding experiments show that this system can increase the water flooding recovery rate of low-permeability homogeneous and heterogeneous cores by 13% and 15%, respectively, and can increase the water-flooding recovery rate of high-permeability heavy oil reservoirs by 40%. The anionic Gemini surfactant flooding system studied in this paper is a viscoelastic fluid, has good emulsifying and oil washing ability, can effectively improve sweep efficiency, reduce injection pressure, and has broad application in unconventional reservoirs to enhance oil recovery prospect.

Keywords: oil displacement system, recovery factor, rheology, interfacial activity, environmental adaptability

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Authors: Sujosh Nandi, Proshanta Guha

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Synthetic plastics are preferred for food packaging due to high strength, stretch-ability, good water vapor and gas barrier properties, transparency and low cost. However, environmental pollution generated by these synthetic plastics is a major concern of modern human civilization. Therefore, use of biodegradable polymers as a substitute for synthetic non-biodegradable polymers are encouraged to be used even after considering drawbacks related to mechanical and barrier properties of the films. Starch is considered one of the potential raw material for the biodegradable polymer, encounters poor water barrier property and mechanical properties due to its hydrophilic nature. That apart, recrystallization of starch molecules occurs during aging which decreases flexibility and increases elastic modulus of the film. The recrystallization process can be minimized by blending of other hydrocolloids having similar structural compatibility, into the starch matrix. Therefore, incorporation of guar gum having a similar structural backbone, into the starch matrix can introduce a potential film into the realm of biodegradable polymer. However, hydrophilic nature of both starch and guar gum, water barrier property of the film is low. One of the prospective solution to enhance this could be modification of the potato starch/guar gum (PSGG) composite film using cross-linker. Over the years, several cross-linking agents such as phosphorus oxychloride, sodium trimetaphosphate, etc. have been used to improve water vapor permeability (WVP) of the films. However, these chemical cross-linking agents are toxic, expensive and take longer time to degrade. Therefore, naturally available carboxylic acid (tartaric acid, malonic acid, succinic acid, etc.) had been used as a cross-linker and found that water barrier property enhanced substantially. As per our knowledge, no works have been reported with tartaric acid and succinic acid as a cross-linking agent blended with the PSGG films. Therefore, the objective of the present study was to examine the changes in water vapor barrier property and mechanical properties of the PSGG films after cross-linked with tartaric acid (TA) and succinic acid (SA). The cross-linkers were blended with PSGG film-forming solution at four different concentrations (4, 8, 12 & 16%) and cast on teflon plate at 37°C for 20 h. From the fourier-transform infrared spectroscopy (FTIR) study of the developed films, a band at 1720cm-1 was observed which is attributed to the formation of ester group in the developed films. On the other hand, it was observed that tensile strength (TS) of the cross-linked film decreased compared to non-cross linked films, whereas strain at break increased by several folds. Moreover, the results depicted that tensile strength diminished with increasing the concentration of TA or SA and lowest TS (1.62 MPa) was observed for 16% SA. That apart, maximum strain at break was also observed for TA at 16% and the reason behind this could be a lesser degree of crystallinity of the TA cross-linked films compared to SA. However, water vapor permeability of succinic acid cross-linked film was reduced significantly, but it was enhanced significantly by addition of tartaric acid.

Keywords: cross linking agent, guar gum, organic acids, potato starch

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Authors: Hazel Pettifor, Charlie Wilson, David Mccollum, Oreane Edelenbosch

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Vehicle purchase is a technology adoption decision that will strongly influence future energy and emission outcomes. Global integrated assessment models (IAMs) provide valuable insights into the medium and long terms effects of socio-economic development, technological change and climate policy. In this paper we present a unique and transparent approach for improving the behavioural representation of these models by incorporating social influence effects to more accurately represent consumer choice. This work draws together strong conceptual thinking and robust empirical evidence to introduce heterogeneous and interconnected consumers who vary in their aversion to new technologies. Focussing on vehicle choice, we conduct novel empirical research to parameterise consumer risk aversion and how this is shaped by social and cultural influences. We find robust evidence for social influence effects, and variation between countries as a function of cultural differences. We then formulate an approach to modelling social influence which is implementable in both simulation and optimisation-type models. We use two global integrated assessment models (IMAGE and MESSAGE) to analyse four scenarios that introduce social influence and cultural differences between regions. These scenarios allow us to explore the interactions between consumer preferences and social influence. We find that incorporating social influence effects into global models accelerates the early deployment of electric vehicles and stimulates more widespread deployment across adopter groups. Incorporating cultural variation leads to significant differences in deployment between culturally divergent regions such as the USA and China. Our analysis significantly extends the ability of global integrated assessment models to provide policy-relevant analysis grounded in real-world processes.

Keywords: behavioural realism, electric vehicles, social influence, vehicle choice

Procedia PDF Downloads 191

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Abidi Sourour, Ben Salem Hichem, Zoghlemi Aziza, Mezni Mejid, Nasri Saida

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In Tunisia, there is an urgent need to maintain food security by reversing soil degradation and improving crop and livestock productivity. Conservation Agriculture (CA) can be helpful in enhancing crop productivity and soil health. However, the demand for crop residues as animal feed are among the major constraints for the adoption of CA. Thus, the objective of this trial is to test the nutritional value of new forage mixture hays as alternative to cereal residues. Two tri-specific cereal-legume mixture were studied and compared to the classic Vetch-Oat one. They were implemented at farm level in four regions characterized by sub-humi climatic: V70-A15-T15 (Vetch70% - Oat15% -Triticale15%) installed in two sites (Zhir and safasaf), V60-A7-T33 (Vetch60% - Oat7% -Triticale33%) and V70-A30 (Vetch70%-Oat30%). Results revealed a significant variation between mixtures V70-A15-T15 installed at Safsafa, recorded the highest forage yield with 12t DM ha-1 than V60A7T33 and V70A30 installed, respectively in ksar cheikh and Fernana with 11.6 and 11.2.tMSha-1. The same mixture installed in Safsafa gave 22% less yields than the one installed in Safsafa. In fact, the month of March was dry in Z'hir. Moreover, these yields in DM can be comparable to those observed by Yucel and Avci (2009). The CP contents of the samples studied vary significantly between the mixtures (P<0.0003). V70-A15-T15 installed in Safsaf and V70A30 present higher contents of CP (respectively 14.4 and 13.7% DM) compared to the other mixtures. These contents are explained by the high proportion of vetch in the fourth mixture and by the low proportion of weeds in the second. In all cases, the hay produced from these mixtures is significantly richer in protein than that of oats in pure culture (Abdelraheem et al., 2019). The positive correlation between the CP content and the proportion of vetch explains this superior quality. The NDF and ADF contents were similar for all mixtures. These values were similar to those reported in the literature (Abidi and Benyoussef, 2019; Haj-Ayed and al., 2000). In general, the Land Equivalent Ratio (LER) was significantly greater than 1 for the vetch-oat-triticale mixture at Zhiir and Safsafa and also for the vetch-oat a at Fernana, proving that they are more productive in intercropping than in pure culture. For the Ksar Cheikh site, the LER value of the vetch-oat-triticale mixture is maintained at around 1. Proving the absence of the advantage of mixture culture compared to pure culture. This proves the massive presence of weeds interferes with the two partners of the mixture increases. The LER for the vetch-oat mixture reached its maximum in March 13 and decreases in April but remained above 1. This proves that the tutoring power of oats showed itself in a constant way until an advanced stage since the variety used is characterized by very thick stems, protecting it from the risk of lodging. These forages mixture present a promising option, a high nutritional quality that could reduce the use of concentrate and, therefore, the cost of feed. With such feed value, these mixtures allow good animal performance.

Keywords: soybean, lupine, vetch, lamb-ADG, meat

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Authors: Hui Long, Chun Yin Tang, Ping Kwong Cheng, Xin Yu Wang, Wayesh Qarony, Yuen Hong Tsang

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Two dimensional (2D) materials have recently attained substantial research interest since the discovery of graphene. However, the zero-bandgap feature of the graphene limits its nonlinear optical applications, e.g., saturable absorption for these applications require strong light-matter interaction. Nevertheless, the excellent optoelectronic properties, such as broad tunable bandgap energy and high carrier mobility of Group 10 transition metal dichalcogenides 2D materials, e.g., PtS2 introduce new degree of freedoms in the optoelectronic applications. This work reports our recent research findings regarding the saturable absorption property of PtS2 layered 2D material and its possibility to be used as saturable absorber (SA) for ultrafast mode locking fiber laser. The demonstration of mode locking operation by using the fabricated PtS2 as SA will be discussed. The PtS2/PVA SA used in this experiment is made up of some few layered PtS2 nanosheets fabricated via a simple ultrasonic liquid exfoliation. The operational wavelength located at ~1 micron is demonstrated from Yb-doped mode locking fiber laser ring cavity by using the PtS2 SA. The fabricated PtS2 saturable absorber offers strong nonlinear properties, and it is capable of producing regular mode locking laser pulses with pulse to pulse duration matched with the round-trip cavity time. The results confirm successful mode locking operation achieved by the fabricated PtS2 material. This work opens some new opportunities for these PtS2 materials for the ultrafast laser generation. Acknowledgments: This work is financially supported by Shenzhen Science and Technology Innovation Commission (JCYJ20170303160136888) and the Research Grants Council of Hong Kong, China (GRF 152109/16E, PolyU code: B-Q52T).

Keywords: platinum disulfide, PtS2, saturable absorption, saturable absorber, mode locking laser

Procedia PDF Downloads 191

Authors: Cheng Hong YEO

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Introduction: Objective: To evaluate the effectiveness of Spectral Dual Layer CT (DECT) in diagnosing choledocholithiasis, specifically focusing on its accuracy in detecting small biliary stones compared to other imaging modalities. Background: DECT has shown promise in improving the detection and characterization of gallstones in the common bile duct, offering potential advantages over traditional imaging methods like standard CT and ultrasonography. Methodology: Study Design: Single-blinded retrospective study conducted at a teaching hospital. Patient Selection: Reviewed records of patients who underwent DECT for suspected choledocholithiasis and had follow-up MRCP, ERCP, or IOC within 8 weeks. 23 patients with proven choledocholithiasis and 23 controls without biliary filling defects were included. DECT Protocol: Used a Philips IQ 256-slice dual-energy CT scanner with standard protocols including 120 kVp and 40 keV mono-E images. Assessment: Four radiologists, blinded to the study question, evaluated images for the presence of choledocholithiasis. Sensitivity, specificity, PPV, and NPV were calculated based on consensus diagnoses. Results: Diagnostic Performance: DECT showed an overall sensitivity of 47.8% and specificity of 78.3% for detecting choledocholithiasis. The accuracy of the diagnosis ranged from 54% to 63% among observers. Stone Detection: Of the identified stones, 6 were calcified and 17 non-calcified. Detection of calcified stones was more accurate (83.3%) compared to non-calcified stones (35.3%). Differences in signal between stones and bile were noted in certain imaging parameters. Interobserver Agreement: The agreement among radiologists was fair, with a Fleiss Kappa coefficient of 0.30. Conclusion: This is the first study to specifically analyse the performance of spectral CT in choledocholithiasis detection using a control group and blinding of reviewers. Our modest results demonstrating lower overall sensitivity than had been reported previously at 47.8% overall while identifying 40% of non-calcified stones <9 mm. We believe further research and development on advancements in spectral CT technology or newer techniques such as photon counting CT is warranted.

Keywords: dual energy CT, choledocholithiasis, gallstones, body imaging

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Authors: Weixiang Liu, Yukun Qin, Song Liu, Pengcheng Li

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Plant diseases can cause the death of crops with great economic losses. Particularly, those diseases are usually caused by pathogenic fungi. Metal fungicides are a type of pesticide that has advantages of a low-cost, broad antimicrobial spectrum and strong sterilization effect. However, the frequent and wide application of traditional metal fungicides has caused serious problems such as environmental pollution, the outbreak of mites and phytotoxicity. Therefore, it is critically necessary to discover new organic metal fungicides alternatives that have a low metal content, low toxicity, and little influence on mites. Chitosan, the second most abundant natural polysaccharide next to cellulose, was proved to have broad-spectrum antifungal activity against a variety of fungi. However, the use of chitosan was limited due to its poor solubility and weaker antifungal activity compared with commercial fungicide. Therefore, in order to improve the water solubility and antifungal activity, many researchers grafted the active groups onto chitosan. The present work was to combine free metal ions with chitosan, to prepare more potent antifungal chitosan derivatives, thus, based on condensation reaction, chitosan derivative bearing amino pyridine group was prepared and subsequently followed by coordination with cupric ions, zinc ions and nickel ions to synthesize chitosan metal complexes. The calculations by density functional theory (DFT) show that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and all of them are coordinated by the carbon atom in the p-π conjugate group and the oxygen atoms in the acetate ion. The antifungal properties of chitosan metal complexes against Phytophthora capsici (P. capsici), Gibberella zeae (G. zeae), Fusarium oxysporum (F. oxysporum) and Botrytis cinerea (B. cinerea) were also assayed. In addition, a plant toxicity experiment was carried out. The experiments indicated that the derivatives have significantly enhanced antifungal activity after metal ions complexation compared with the original chitosan. It was shown that 0.20 mg/mL of O-CSPX-Cu can 100% inhibit the growth of P. capsici and 0.20 mg/mL of O-CSPX-Ni can 87.5% inhibit the growth of B. cinerea. In general, their activities are better than the positive control oligosaccharides. The combination of the pyridine formyl groups seems to favor biological activity. Additionally, the ligand fashion was precisely analyzed, and the results revealed that the copper ions and nickel ions underwent dsp2 hybridization, the zinc ions underwent sp3 hybridization, and the carbon atoms of the p-π conjugate group and the oxygen atoms of acetate ion are involved in the coordination of metal ions. The phytotoxicity assay of O-CSPX-M was also conducted, unlike the traditional metal fungicides, the metal complexes were not significantly toxic to the leaves of wheat. O-CSPX-Zn can even increase chlorophyll content in wheat leaves at 0.40 mg/mL. This is mainly because chitosan itself promotes plant growth and counteracts the phytotoxicity of metal ions. The chitosan derivative described here may lend themselves to future applicative studies in crop protection.

Keywords: coordination, chitosan, metal complex, antifungal properties

Procedia PDF Downloads 322