Search results for: uses of new technology to manage waste

Authors: Ai Serizawa, Kotaro Mori, Takahiro Ishizaki

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Al alloys have been used as advanced structural materials in automobile and railway industries because of excellent physical and mechanical properties such as low density, good heat conductivity, and high specific strength. Their low corrosion resistance, however, limits their use in the corrosive environment. To improve the corrosion resistance of the Al alloys, the development of a novel coating technology has been highly desirable. Chemical conversion methods using layered double hydroxide (LDH) have attracted much attention because the LDH can suppress corrosion reaction due to their trapping ability of corrosive anions such as Cl- between layers. In this presentation, we report on a novel preparation method of AlOOH film containing Mg-Al layered double hydroxide (LDH) on Al alloy by steam coating. The corrosion resistance of the composite film including LDH was especially focused. Al-Mg-Si alloy was used as the substrate. The substrates were ultrasonically cleaned in ethanol for 10 min. The cleaned substrates were set in the autoclave with a 100 mL capacity. 20 ml of ultrapure water was located at the bottom of the autoclave to produce steam. The autoclave was heated up to a temperature of 100 to 200 °C, and then held at this temperature for up to 48 h, and was subsequently cooled naturally to room temperature, resulting in the formation of anticorrosive films on Al alloys. The resultant films were characterized by XRD, FT-IR, FE-SEM and electrochemical measurements. FE-SEM image of film surface treated at 180 °C for 48 h demonstrated that needle-like nanostructure was densely formed on the surface. XRD patterns revealed that the film formed on the Al alloys by steam coating was composed of crystal AlOOH and Mg-Al LDH. The corrosion resistance of the film was evaluated using electrochemical measurements. The potentiodynamic polarization curves of the film coated and uncoated substrates of Al-Mg-Si alloy after immersion in the 5 wt% NaCl aqueous solution for 30 min revealed that the corrosion current density, jcorr, of the film coated sample decreased by more than two orders of magnitude as compared to the uncoated sample, indicating that the corrosion resistance of the substrates of Al-Mg-Si alloy were improved by the formation of the anticorrosive film via steam coating.

Keywords: aluminum alloy, boehmite, corrosion resistance, steam process

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Authors: Sunglim Lee, Susumu Fujii, Koji Okamura

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Smart grid is a new approach for electric power grid that uses information and communications technology to control the electric power grid. Smart grid provides real-time control of the electric power grid, controlling the direction of power flow or time of the flow. Control devices are installed on the power lines of the electric power grid to implement smart grid. The number of the control devices should be determined, in relation with the area one control device covers and the cost associated with the control devices. One approach to determine the number of the control devices is to use the data on the surplus power generated by home solar generators. In current implementations, the surplus power is sent all the way to the power plant, which may cause power loss. To reduce the power loss, the surplus power may be sent to a control device and sent to where the power is needed from the control device. Under assumption that the control devices are installed on a lattice of equal size squares, our goal is to figure out the optimal spacing between the control devices, where the power sharing area (the area covered by one control device) is kept small to avoid power loss, and at the same time the power sharing area is big enough to have no surplus power wasted. To achieve this goal, a simulation using landscape ecology method is conducted on a sample area. First an aerial photograph of the land of interest is turned into a mosaic map where each area is colored according to the ratio of the amount of power production to the amount of power consumption in the area. The amount of power consumption is estimated according to the characteristics of the buildings in the area. The power production is calculated by the sum of the area of the roofs shown in the aerial photograph and assuming that solar panels are installed on all the roofs. The mosaic map is colored in three colors, each color representing producer, consumer, and neither. We started with a mosaic map with 100 m grid size, and the grid size is grown until there is no red grid. One control device is installed on each grid, so that the grid is the area which the control device covers. As the result of this simulation we got 350 m as the optimal spacing between the control devices that makes effective use of the surplus power for the sample area.

Keywords: landscape ecology, IT, smart grid, aerial photograph, simulation

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Authors: Suresh Lokiah

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The emerging trend of integrating robots into elderly care, particularly for assisting patients with dementia, holds the potential to greatly transform the sector. Assisted living facilities, which house a significant number of elderly individuals and dementia patients, constantly strive to engage their residents in stimulating activities. However, due to staffing shortages, they often rely on volunteers to introduce new activities. Despite the availability of social interaction, these residents, frequently overlooked in society, are in desperate need of additional support. Robots designed for elder care are categorized based on their design and functionality. These categories include companion robots, telepresence robots, health monitoring robots, and rehab robots. However, the integration of such robots raises significant ethical concerns, notably regarding privacy, autonomy, and the risk of dehumanization. Privacy issues arise as these robots may need to continually monitor patient activities. There is also a risk of patients becoming overly dependent on these robots, potentially undermining their autonomy. Furthermore, the replacement of human touch with robotic interaction may lead to the dehumanization of care. This paper delves into the ethical considerations of incorporating robotic assistance in eldercare. It proposes a series of guidelines and strategies to ensure the ethical deployment of these robots. These guidelines suggest involving patients in the design and development process of the robots and emphasize the critical need for human oversight to respect the dignity and rights of the elderly and dementia patients. The paper also recommends implementing robust privacy measures, including secure data transmission and data anonymization. In conclusion, this paper offers a thorough examination of the ethical implications of using robotic assistance in elder care. It provides a strategic roadmap to ensure this technology is utilized ethically, thereby maximizing its potential benefits and minimizing any potential harm.

Keywords: human-robot interaction, robots for eldercare, ethics, health, dementia

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Authors: Raj Chavan

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Currently, there are over 14,500 Water Resource Recovery Facilities (WRRFs) in the United States, with ~35% of them having some type of nutrient limits in place. These WRRFs account for about 1% of overall power demand and 2% of total greenhouse gas emissions (GHG) in the United States and contribute for 10 to 15% of the overall nutrient load to surface rivers in the United States. The evolution of densification technologies toward more compact and energy-efficient nutrient removal processes has been impacted by a number of factors. Existing facilities that require capacity expansion or biomass densification for higher treatability within the same footprint are being subjected to more stringent requirements relating to nutrient removal prior to surface water discharge. Densification of activated sludge has received recent widespread interest as a means for achieving process intensification and nutrient removal at WRRFs. At the core of the technology are the aerobic sludge granules where the biological processes occur. There is considerable interest in the prospect of producing granular sludge in continuous (or traditional) activated sludge processes (CAS) or densification of biomass by moving activated sludge flocs to a denser aggregate of biomass as a highly effective technique of intensification. This presentation will provide a fundamental understanding of densification by presenting insights and practical issues. The topics that will be discussed include methods used to generate and retain densified granules; the mechanisms that allow biological flocs to densify; the role that physical selectors play in the densification of biological flocs; some viable ways for managing biological flocs that have become densified; effects of physical selection design parameters on the retention of densified biological flocs and finally some operational solutions for customizing the flocs and granules required to meet performance and capacity targets. In addition, it will present some case studies where biological and physical parameters were used to generate aerobic granular sludge in the continuous flow system.

Keywords: densification, aerobic granular sludge, nutrient removal, intensification

Procedia PDF Downloads 186

Authors: Vistorina Amputu, Katja Tielboerger, Nichola Knox

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Primary productivity in dry savannahs is constraint by moisture availability and under increasing anthropogenic pressure. Thus, considering climate change and the unprecedented pace and scale of rangeland deterioration, methods for assessing the status of such rangelands should be easy to apply, yield reliable and repeatable results that can be applied over large spatial scales. Global and local scale monitoring of rangelands through satellite data and labor-intensive field measurements respectively, are limited in accurately assessing the spatiotemporal heterogeneity of vegetation dynamics to provide crucial information that detects degradation in its early stages. Fortunately, newly emerging techniques such as unmanned aerial vehicles (UAVs), associated miniaturized sensors and improving digital photogrammetric software provide an opportunity to transcend these limitations. Yet, they have not been extensively calibrated in natural systems to encompass their complexities if they are to be integrated for long-term monitoring. Limited research using drone technology has been conducted in arid savannas, for example to assess the health status of this dynamic two-layer vegetation ecosystem. In our study, we fill this gap by testing the relationship between UAV-estimated cover of rangeland functional attributes and field data collected in discrete sample plots in a Namibian dryland savannah along a degradation gradient. The first results are based on a supervised classification performed on the ultra-high resolution multispectral imagery to distinguish between rangeland functional attributes (bare, non-woody, and woody), with a relatively good match to the field observations. Integrating UAV-based observations to improve rangeland monitoring could greatly assist in climate-adapted rangeland management.

Keywords: arid savannah, degradation gradient, field observations, narrow-band sensor, supervised classification

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Authors: Desmond Okorie, Emmanuel Prince

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Availability of portable water has been a global challenge especially to the developing continents/nations such as Africa/Nigeria. The World Health Organization WHO has produced the guideline for drinking water quality GDWQ which aims at ensuring water safety from source to consumer. Portable water parameters test include physical (colour, odour, temperature, turbidity), chemical (PH, dissolved solids) biological (algae, plytoplankton). This paper discusses the use of wireless sensor networks to monitor water quality using efficient and effective sensors that have the ability to sense, process and transmit sensed data. The integration of wireless sensor network to a portable sensing device offers the feasibility of sensing distribution capability, on site data measurements and remote sensing abilities. The current water quality tests that are performed in government water quality institutions in Benue State Nigeria are carried out in problematic locations that require taking manual water samples to the institution laboratory for examination, to automate the entire process based on wireless sensor network, a system was designed. The system consists of sensor node containing one PH sensor, one temperature sensor, a microcontroller, a zigbee radio and a base station composed by a zigbee radio and a PC. Due to the advancement of wireless sensor network technology, unexpected contamination events in water environments can be observed continuously. local area network (LAN) wireless local area network (WLAN) and internet web-based also commonly used as a gateway unit for data communication via local base computer using standard global system for mobile communication (GSM). The improvement made on this development show a water quality monitoring system and prospect for more robust and reliable system in the future.

Keywords: local area network, Ph measurement, wireless sensor network, zigbee

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Authors: G. Alex Ambrose, Melissa Paulsen, Abrar Fitwi, Masud Akbari

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In 2016, a U.S. business college was awarded a sub grant to work with FHI360, a nonprofit human development organization, to support a university in Afghanistan funded by the State Department’s U.S. Agency for International Development (USAID). A newly designed Master’s Degree in Finance and Accounting is being implemented to support Afghanistan’s goal of 20% females in higher education and industry by 2020 and to use finance and accounting international standards to attract capital investment for economic development. This paper will present a case study to describe the co-construction of an approach to an International Flipped Faculty Development Model grounded in blended learning theory. Like education in general, faculty development is also evolving from the traditional face to face environment and interactions to the fully online and now to a best of both blends. Flipped faculty development is both a means and a model for careful integration of the strengths of the synchronous and asynchronous dynamics and technologies with the combination of intentional sequencing to pre-online interactions that prepares and enhances the face to face faculty development and mentorship residencies with follow-up post-online support. Initial benefits from this model include giving the Afghan faculty an opportunity to experience and apply modern teaching and learning strategies with technology in their own classroom. Furthermore, beyond the technological and pedagogical affordances, the reciprocal benefits gained from the mentor-mentee, face-to-face relationship will be explored. Evidence to support this model includes: empirical findings from pre- and post-Faculty Mentor/ Mentee survey results, Faculty Mentorship group debriefs, Faculty Mentorship contact logs, and student early/end of semester feedback. In addition to presenting and evaluating this model, practical challenges and recommendations for replicating international flipped faculty development partnerships will be provided.

Keywords: educational development, faculty development, international development, flipped learning

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Authors: Abdul Nasir Zamir

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After the downfall of Ottoman Caliphate, it scattered into different small Muslim states. Muslim leaders, intellectuals, revivalists as well as modernists started trying to boost up their nation. Some Muslims are also trying to establish the caliphate. Every Muslim country has its own political system, i.e., kingship, dictatorship or democracy, etc. But these are not in their original forms as the historian or political science discussed in their studies. The laws and their practice are mixed, i.e., others with Islamic laws, e.g., Saudi Arabia (K.S.A) and the Islamic Republic of Pakistan, etc. There is great conflict among the revivalist Muslim parties (groups) and governments about political systems. The question is that the subject matter is Sharia or political system? Leaders of Modern Muslim states are alleged as disbelievers due to neglecting the revelation in their laws and decisions. There are two types of laws; Islamic laws and management laws. The conflict is that the non-Islamic laws are in practice in Muslim states. Non-Islamic laws can be gradually changed with Islamic laws with a legal and peaceful process according to the practice of former Muslim leaders and scholars. The bloodshed of Muslims is not allowed in any case. Weak Muslim state is a blessing than nothing. The political system after Muhammad and guided caliphs is considered as kingship. But during this period Muslims not only developed in science and technology but conquered many territories also. If the original aim is in practice, then the Modern Muslim states can be stabled with different political systems. Modern Muslim states are the hope of survival, stability, and development of Muslim Ummah. Islam does not allow arm clash with Muslim army or Muslim civilians. The caliphate is based on believing in one Allah Almighty and good deeds according to Quran and Sunnah. As faith became weak and good deeds became less from its standard level, caliphate automatically became weak and even ended. The last weak caliphate was Ottoman Caliphate which was a hope of all the Muslims of the world. There is no caliphate or caliph present in the world. But every Muslim country or state is like an Amarat (a part of caliphate or small and alternate form of the caliphate) of Muslims. It is the duty of all Muslims to stable these modern Muslim states with tolerance.

Keywords: caliphate, conflict resolution, modern Muslim state, political conflicts, political systems, tolerance

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Authors: Mohammad Mirwais Yusufi

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Skillful management is one of the most important success factors for today’s farms. When a farm is well managed, it can generate funds for its sustainability. Grape is one of the most diffused fruits in the world and one of the most important cash crops with high potential of production in Afghanistan as well. While there are several organizations intervening for improvement of this cash crop, the quality and quantity are still not satisfactory for producers and external markets. The situation has not changed over the years. Therefore, a survey was conducted in 2017 with 60 grape growers, supported by questionnaires in Mirbachakot, Kalakan and Shakardara districts of Kabul province. The purpose was to get an understanding of the current socio-demographic characteristics of farmers, management methods, constraints, farm size, yield and contribution of grape farming to household income. Findings indicate that grape farming was predominant 83.3% male, 16.6% female and small-scale farmers were the main grape producers, 60% < 1 ha of land under grape production. Likewise, 50% had more than > 10 years and 33.3% between 1-5 years’ experience in grape farming. The high level of illiteracy and diseases had significant digit effect on growth, yield and quality of grapes. The results showed that vineyard management operations to protect grapes from mechanical damage are very poor or completely absent. Comparing developed countries, table grape is one of the fruits with the highest input of technology, while in developing countries the cost of labor is low but the purchase of the equipment is very high due to financial situation. Hence the low quality and quantity of grape are influenced by poor management methods, such as non-availability of experts and lack of technical guidance in the study site. Thereby, the study suggested that improved agricultural extension services and managerial skills could contribute to addressing the problems.

Keywords: constraints, effect, management, Kabul

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Authors: Didarul Islam Manik

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The study was conducted to determine social media usage by the Millennial/young-adult generation in the U.S. and Bangladesh. It investigated what types of social media Millennials/young-adults use in their everyday lives; for what purpose they use social media; what are the significant differences between the two cultures in terms of social media use; and how the age of the respondents correlates with differences in social media use. Among the 409 respondents, 200 were selected from the University of South Dakota and 209 from the University of Dhaka, Bangladesh. The convenience sampling method was used to select the samples. A four-page questionnaire instrument was constructed with 19 closed-ended questions that collected 87 data points. The study considered the uses and gratifications and domestication of technology models as theoretical frameworks. The study found that the Millennials spend an average of 4.5 hours on the Internet daily. They spend an average of 134 minutes on social media every day. However, the U.S. Millennials spend more time (141 minutes) on social media than the Bangladeshis (127 minutes). The U.S. Millennials use various types of social media including Facebook, Twitter, YouTube, Instagram, Pinterest, SnapChat, Reddit, Imgur, etc. In contrast, Bangladeshis use Facebook, YouTube, and Google plus+. The Bangladeshis tended to spend more time on Facebook (107 minutes) than the Americans (57 minutes). The study found that the Millennials of the two countries use Facebook to fill their free time, acquire information, seek entertainment, and maintain existing relationships. However, Bangladeshis are more likely to use Facebook for the acquisition of information, entertainment, educational purposes, and connecting with the people closest to them. Millennials also use Twitter to fill their free time, acquire information, and for entertainment. The study found a statistically significant difference between female and male social media use. It also found a significant correlation between age and using Facebook for educational purposes; age and discussing and posting religious issues; and age and meeting with new people. There is also a correlation between age and the use of Twitter for spending time and seeking entertainment.

Keywords: American study, social media, millennial generation, South Asian studies

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Nattapol Pourprasert

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This research is to study qualitative research having two objectives: 1. to study comparison of private sector of government to compare with ASEAN Member States, 2. to study trend of private enterprise administration of ASEAN Member States. The results are: (1) Thai people focus on personal resource administrative system, (2) Indonesia focuses on official system by good administrative principles, (3) Malaysia focuses on technology development to service people, (4) Philippines focuses on operation system development, (5) Singapore focuses on public service development, (6) Brunei Darussalam focuses on equality in government service of people, (7) Vietnam focuses on creating government labor base and develop testing and administration of operation test, (8) Myanmar focuses on human resources development, (9) Laos focuses on form of local administration, (10) Cambodia focuses on policy revolution in personal resources. The result of the second part of the study are: (1) Thailand created government personnel to be power under qualitative official structural event, (2) Indonesia has Bureaucracy Reform Roadmap of Bureaucracy Reform and National Development Plan Medium Term, (3) Malaysia has database for people service, (4) Philippines follows up control of units operation by government policy, (5) Singapore created reliability, participation of people to set government policy people’s demand, (6) Brunei Darussalam has social welfare to people, (7) Vietnam revolved testing system and administration including manpower base construction of government effectively, (8) Myanmar creates high rank administrators to develop country, (9) Laos distributes power to locality, and (10) Cambodia revolved personnel resource policy.

Keywords: public administration development, ASEAN member states, private sector, government

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Authors: Ignatius Madu

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The study aims at assessing the environmental and socioeconomic determinants of climate change resilience in rural Nigeria. This is necessary because researches and development efforts on building climate change resilience of rural areas in developing countries are usually made without the knowledge of the impacts of the inherent rural characteristics that determine resilient capacities of the households. This has, in many cases, led to costly mistakes, delayed responses, inaccurate outcomes, and other difficulties. Consequently, this assessment becomes crucial not only to policymakers and people living in risk-prone environments in rural areas but also to fill the research gap. To achieve the aim, secondary data were obtained from the Annual Abstract of Statistics 2017, LSMS-Integrated Surveys on Agriculture and General Household Survey Panel 2015/2016, and National Agriculture Sample Survey (NASS), 2010/2011.Resilience was calculated by weighting and adding the adaptive, absorptive and anticipatory measures of households variables aggregated at state levels and then regressed against rural environmental and socioeconomic characteristics influencing it. From the regression, the coefficients of the variables were used to compute the impacts of the variables using the Stochastic Regression of Impacts on Population, Affluence and Technology (STIRPAT) Model. The results showed that the northern States are generally low in resilient indices and are impacted less by the development indicators. The major determining factors are percentage of non-poor, environmental protection, road transport development, landholding, agricultural input, population density, dependency ratio (inverse), household asserts, education and maternal care. The paper concludes that any effort to a successful resilient building in rural areas of the country should first address these key factors that enhance rural development and wellbeing since it is better to take action before shocks take place.

Keywords: climate change resilience; spatial impacts; STIRPAT model; Nigeria

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Authors: Joseph Udofia, Isaac Olufadewa

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Everyday, the size of Electronic Health Records data keeps increasing as new patients visit health practitioner and returning patients fulfil their appointments. As these data grow, so is their susceptibility to cyber-attacks from criminals waiting to exploit this data. In the US, the damages for cyberattacks were estimated at $8 billion (2018), $11.5 billion (2019) and $20 billion (2021). These attacks usually involve the exposure of PII. Health data is considered PII, and its exposure carry significant impact. To this end, an enhancement of Health Policy and Standards in relation to data security, especially among patients and their clinical providers, is critical to ensure ethical practices, confidentiality, and trust in the healthcare system. As Clinical accelerators and applications that contain user data are used, it is expedient to have a review and revamp of policies like the Payment Card Industry Data Security Standard (PCI DSS), the Health Insurance Portability and Accountability Act (HIPAA), the Fast Healthcare Interoperability Resources (FHIR), all aimed to ensure data protection and security in healthcare. FHIR caters for healthcare data interoperability, FHIR caters to healthcare data interoperability, as data is being shared across different systems from customers to health insurance and care providers. The astronomical cost of implementation has deterred players in the space from ensuring compliance, leading to susceptibility to data exfiltration and data loss on the security accuracy of protected health information (PHI). Though HIPAA hones in on the security accuracy of protected health information (PHI) and PCI DSS on the security of payment card data, they intersect with the shared goal of protecting sensitive information in line with industry standards. With advancements in tech and the emergence of new technology, it is necessary to revamp these policies to address the complexity and ambiguity, cost barrier, and ever-increasing threats in cyberspace. Healthcare data in the wrong hands is a recipe for disaster, and we must enhance its protection and security to protect the mental health of the current and future generations.

Keywords: cloud security, healthcare, cybersecurity, policy and standard

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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: 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: 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: 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

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Authors: W. Assaad, D. Wilmink, H. R. Pasaribu, H. J. M. Geijselaers

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Shell has developed a mono-diameter well concept for oil and gas wells as opposed to the traditional telescopic well design. A Mono-diameter well design allows well to have a single inner diameter from the surface all the way down to reservoir to increase production capacity, reduce material cost and reduce environmental footprint. This is achieved by expansion of liners (casing string) concerned using an expansion tool (e.g. a cone). Since the well is drilled in stages and liners are inserted to support the borehole, overlap sections between consecutive liners exist which should be expanded. At overlap, the previously inserted casing which can be expanded or unexpanded is called the host casing and the newly inserted casing is called the expandable casing. When the cone enters the overlap section, an expandable casing is expanded against a host casing, a cured cement layer and formation. In overlap expansion, ironing or lengthening may appear instead of shortening in the expandable casing when the pressure exerted by the host casing, cured cement layer and formation exceeds a certain limit. This pressure is related to cement strength, thickness of cement layer, host casing material mechanical properties, host casing thickness, formation type and formation strength. Ironing can cause implications that hinder the deployment of the technology. Therefore, the understanding of ironing becomes essential. A physical model is built in-house to calculate expansion forces, stresses, strains and post expansion casing dimensions under different conditions. In this study, only free casing and overlap expansion of two casings are addressed while the cement and formation will be incorporated in future study. Since the axial strain can be predicted by the physical model, the onset of ironing can be confirmed. In addition, this model helps in understanding ironing and the parameters influencing it. Finally, the physical model is validated with Finite Element (FE) simulations and small-scale experiments. The results of the study confirm that high pressure leads to ironing when the casing is expanded in tension mode.

Keywords: casing expansion, cement, formation, metal forming, plasticity, well design

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Authors: Santimoy Khilari, Debabrata Pradhan

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Ever−increasing energy demand and growing energy crisis along with environmental issues emphasize the research on sustainable energy conversion and storage systems. Recently, supercapacitors or electrochemical capacitors emerge as a promising energy storage technology for future generation. The activity of supercapacitors generally depends on the efficiency of its electrode materials. So, the development of cost−effective efficient electrode materials for supercapacitors is one of the challenges to the scientific community. Transition metal oxides with spinel crystal structure receive much attention for different electrochemical applications in energy storage/conversion devices because of their improved performance as compared to simple oxides. In the present study, we have synthesized polypyrrole (PPy) supported manganese cobaltite nanorods (MnCo2O4 NRs) hybrid electrode material for supercapacitor application. The MnCo2O4 NRs were synthesized by a simple hydrothermal and calcination approach. The MnCo2O4 NRs/PPy hybrid was prepared by in situ impregnation of MnCo2O4 NRs during polymerization of pyrrole. The surface morphology and microstructure of as−synthesized samples was characterized by scanning electron microscopy and transmission electron microscopy, respectively. The crystallographic phase of MnCo2O4 NRs, PPy and hybrid was determined by X-ray diffraction. Electrochemical charge storage activity of MnCo2O4 NRs, PPy and MnCo2O4 NRs/PPy hybrid was evaluated from cyclic voltammetry, chronopotentiometry and electrochemical impedance spectroscopy. Significant improvement of specific capacitance was achieved in MnCo2O4 NRs/PPy hybrid as compared to the individual components. Furthermore, the mechanically mixed MnCo2O4 NRs, and PPy shows lower specific capacitance as compared to MnCo2O4 NRs/PPy hybrid suggesting the importance of in situ hybrid preparation. The stability of as prepared electrode materials was tested by cyclic charge-discharge measurement for 1000 cycles. Maximum 94% capacitance was retained with MnCo2O4 NRs/PPy hybrid electrode. This study suggests that MnCo2O4 NRs/PPy hybrid can be used as a low cost electrode material for charge storage in supercapacitors.

Keywords: supercapacitors, nanorods, spinel, MnCo2O4, polypyrrole

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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

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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

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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: César Coelho, Nikolai Wiegand

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The advancement of nanosatellite technology has opened new avenues for cost-effective and faster space missions. The NanoSat MO Framework (NMF) from the European Space Agency (ESA) provides a modular and simpler approach to the development of flight software and operations of small satellites. This paper presents a methodology using the NMF together with Docker for simulating constellations of satellites. By leveraging Docker containers, the software environment of individual satellites can be easily replicated within a simulated constellation. This containerized approach allows for rapid deployment, isolation, and management of satellite instances, facilitating comprehensive testing and development in a controlled setting. By integrating the NMF lightweight simulator in the container, a comprehensive simulation environment was achieved. A significant advantage of using Docker containers is their inherent scalability, enabling the simulation of hundreds or even thousands of satellites with minimal overhead. Docker's lightweight nature ensures efficient resource utilization, allowing for deployment on a single host or across a cluster of hosts. This capability is crucial for large-scale simulations, such as in the case of mega-constellations, where multiple traditional virtual machines would be impractical due to their higher resource demands. This ability for easy horizontal scaling based on the number of simulated satellites provides tremendous flexibility to different mission scenarios. Our results demonstrate that leveraging Docker containers with the NanoSat MO Framework provides a highly efficient and scalable solution for simulating satellite constellations, offering not only significant benefits in terms of resource utilization and operational flexibility but also enabling testing and validation of ground software for constellations. The findings underscore the importance of taking advantage of already existing technologies in computer science to create new solutions for future satellite constellations in space.

Keywords: containerization, docker containers, NanoSat MO framework, satellite constellation simulation, scalability, small satellites

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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 187