Search results for: future trends

Authors: Guilherme Henrique Gabriel, Lucí Hidalgo Nunes

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An important feature of rainfall regimes is the variability, which is subject to the atmosphere’s general and regional dynamics, geographical position and relief. Despite being inherent to the climate system, it can harshly impact virtually all human activities. In turn, global climate change has the ability to significantly affect smaller-scale rainfall regimes by altering their current variability patterns. In this regard, it is useful to know if regional climates are changing over time and whether it is possible to link these variations to climate change trends observed globally. This study is part of an international project (Metropole-FAPESP, Proc. 2012/51876-0 and Proc. 2015/11035-5) and the objective was to identify and evaluate possible changes in rainfall behavior in the state of São Paulo, southeastern Brazil, using rainfall data from 79 rain gauges for the last forty years. Cluster analysis and gamma distribution parameters were used for evaluating spatial and temporal trends, and the outcomes are presented by means of geographic information systems tools. Results show remarkable changes in rainfall distribution patterns in São Paulo over the years: changes in shape and scale parameters of gamma distribution indicate both an increase in the irregularity of rainfall distribution and the probability of occurrence of extreme events. Additionally, the spatial outcome of cluster analysis along with the gamma distribution parameters suggest that changes occurred simultaneously over the whole area, indicating that they could be related to remote causes beyond the local and regional ones, especially in a current global climate change scenario.

Keywords: climate change, cluster analysis, gamma distribution, rainfall

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Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Bin Su

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The draft Auckland Unitary Plan outlines the future land used for new housing and businesses with Auckland population growth over the next thirty years. According to Auckland Unitary Plan, over the next 30 years, the population of Auckland is projected to increase by one million, and up to 70% of total new dwellings occur within the existing urban area. Intensification will not only increase the number of median or higher density houses such as terrace house, apartment building, etc. within the existing urban area but also change mean housing design data that can impact building thermal performance under the local climate. Based on mean energy consumption and building design data, and their relationships of a number of Auckland sample houses, this study is to estimate the future mean housing energy consumption associated with the change of mean housing design data and evaluate housing energy efficiency with the Auckland Unitary Plan.

Keywords: Auckland Unitary Plan, building thermal design, housing design, housing energy efficiency

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Authors: Eugene Mashapa

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The age of information has witnessed countless unprecedented technological developments, which signal the articulation of succinct technological capabilities that can match these cutting-edge technological trends. These changes have impacted patterns in the production, distribution, and consumption of media content, a space that the Film and Publication Board (FPB) is concerned with. Consequently, the FPB is keen to understand the nature and impact of these technological changes on media content regulation. This exploratory study sought to investigate how content regulators in high and middle-income economies have adapted to the changes in this space, seeking insights into innovations, technological and operational, that facilitate continued relevance during this fast-changing environment. The study is aimed at developing recommendations that could assist and inform the organisation in regulating media content as it evolves. Thus, the overall research strategy in this analysis is applied research, and the analytical model adopted is a mixed research design guided by both qualitative and quantitative research instruments. It was revealed in the study that the FPB was significantly impacted by the unprecedented technological advancements in the media regulation space. Additionally, there exists a need for the FPB to understand the current and future penetrations of 4IR technology in the industry and its impact on media governance and policy implementation. This will range from reskilling officials to align with the technological skills to developing technological innovations as well as adopting co-regulatory or self-regulatory arrangements together with content distributors, where more content is distributed in higher volumes and with increased frequency. Importantly, initiating an interactive learning process for both FPB employees and the general public can assist the regulator and improve FPB’s operational efficiency and effectiveness.

Keywords: media, regulation, technology, film and publications board

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Authors: Maximilian A. Richter

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The public authority needs to understand the role and impacts of autonomous vehicle (AV) on the mobility system. At present, however, research shows that the impact of AV on cities varies. As a consequence, it is difficult to make recommendations to policymakers on how they should prepare for the future when so much remains unknown about this technology. The study aims to provide an overview of the literature on how autonomous vehicles will affect the cities and traffic of the future. To this purpose, the most important studies are first selected, and their results summarized. Further on, it will be clarified which advantages AV have for cities and how it can lead to an improvement in the current problems/challenges of cities. To achieve the research aim and objectives, this paper approaches a literature review. For this purpose, in a first step, the most important studies are extracted. This is limited to studies that are peer-reviewed and have been published in high-ranked journals such as the Journal of Transportation: Part A. In step 2, the most important key performance indicator (KPIs) (such as traffic volume or energy consumption) are selected from the literature research. Due to the fact that different terms are used in the literature for similar statements/KPIs, these must first be clustered. Furthermore, for each cluster, the changes from the respective studies are compiled, as well as their survey methodology. In step 3, a sensitivity analysis per cluster is made. Here, it will be analyzed how the different studies come to their findings and on which assumptions, scenarios, and methods these calculations are based. From the results of the sensitivity analysis, the success factors for the implementation of autonomous vehicles are drawn, and statements are made under which conditions AVs can be successful.

Keywords: autonomous vehicles, city of the future, literature review, traffic simulations

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Authors: Riktesh Srivastava

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Online Shopping have established an astonishing evolution in the last few years. And it is now apparent that B2C architecture is becoming progressively imperative channel for even traditional brick and mortar type traders as well. In this completion knowing customers and predicting behavior are extremely important. More important, when any customer logs onto the B2C architecture, the traces of their buying patterns can be stored and used for future predictions. Such a prediction is called Customer Lifetime Value (CLV). Earlier, we used Net Present Value to do so, however, it ignores two important aspects of B2C architecture, “market risks” and “big amount of customer data”. Now, we use RFM- Recency, Frequency and Monetary Value to estimate the CLV, and as the term exemplifies, market risks, is well sheltered. Big Data Analysis is also roofed in RFM, which gives real exploration of the Big Data and lead to a better estimation for future cash flow from customers. In the present paper, 6 factors (collected from varied sources) are used to determine as to what attracts the customers to the B2C architecture. For these 6 factors, RFM is computed for 3 years (2013, 2014 and 2015) respectively. CLV and Revenue are the two parameters defined using RFM analysis, which gives the clear picture of the future predictions.

Keywords: CLV, RFM, revenue, recency, frequency, monetary value

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Authors: Abewardhana Arachchi Bandula Dimuthu Priyadarshana Abewardhana, Rasika Nirosh Gonapinuwala Vithanage, Karawe Thanthreege Amila Madusanka Perera, Asanka Sanjeewa Karunarathne, Navullage Mayuri Radhika Perera

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The phenomenon of irregular migration and human trafficking presents multifaceted challenges to Sri Lanka, with specific focus on the migration routes to the United Arab Emirates (UAE), the Sultanate of Oman, and Malaysia. This research critically assesses the efficacy of a pilot project instituted at Bandaranaike International Airport aimed at the identification and deterrence of potential irregular migrants. Additionally, the study conducts a nuanced analysis of the geographical tendencies pertaining to passengers who revise their migration intentions at the airport. Pertinently, the findings indicate that Colombo and Gampaha Districts emerge as the most susceptible to human trafficking, with Galle, Nuwaraeliya, Rathnapura, and Polonnaruwa Districts following as areas of elevated concern, particularly within the framework of the 'visit visa' scenario. These insights emanate from an extensive data collection period spanning 50 days of the pilot project, encompassing 1,479 passengers, of which 46 returnees reported to the Safe Migration Promotion Unit. The research is founded on the twin objectives of comprehending the motivations of passengers and evaluating the effectiveness of interventions, with a view to devising precision-targeted prevention strategies. Through this endeavor, the study actively contributes to the safeguarding of the rights and welfare of migrants, significantly advancing the ongoing battle against irregular migration.

Keywords: irregular migration, human trafficking, airport interventions, geographic trends

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Authors: M. Saba, A. Iaaly, E. Carlier, N. Georges

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This research focuses on assessing the ground water quality of Northern Lebanon affected by saline water intrusion. The chemical, physical and microbiological parameters were collected in various seasons spanning over the period of two years. Results were assessed using Geographic Information System (GIS) due to its visual capabilities in presenting the pollution extent in the studied region. Future projections of the excessive pumping were also simulated using GIS in order to assess the extent of the problem of saline intrusion in the near future.

Keywords: GIS, saline water, quality control, drinkable water quality standards, pumping

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Authors: Shukri Dughman, Anthony Rossiter

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This paper builds on earlier work which demonstrated that Model Predictive Control (MPC) may give a poor choice of default feed forward compensator. By first demonstrating the impact of future information of target changes on the performance, this paper proposes a pragmatic method for identifying the amount of future information on the target that can be utilised effectively in both finite and infinite horizon algorithms. Numerical illustrations in MATLAB give evidence of the efficacy of the proposal.

Keywords: model predictive control, tracking control, advance knowledge, feed forward

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Authors: Mogens Frank Mikkelsen

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Special Relativity Theory (SRT) includes only one characteristic of light, the speed is equal to all observers, and by excluding other relevant characteristics of light, the common interpretation of SRT should be regarded as merely an approximative theory. By rethinking the iconic double light cones, a revised version of SRT can be developed. The revised concept of light cones acknowledges an asymmetry of past and future light cones and introduced a concept of the extended past to explain the predictions as something other than the future. Combining this with the concept of photon-paired events, led to the inference that Special Relativity theory can support the existence of Now.

Keywords: relativity, light cone, Minkowski, time

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Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: I. Turk Cakir, B. Hacisahinoglu, S. Kartal, A. Yilmaz, A. Yilmaz, Z. Uysal, O. Cakir

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In the search for new physics beyond the Standard Model, Flavour Changing Neutral Current (FCNC) is a good research field in terms of the observability at future colliders. Increased Higgs production with higher energy and luminosity in colliders is essential for verification or falsification of our knowledge of physics and predictions, and the search for new physics. Prospective electron-proton collider constituent of the Future Circular Collider project is FCC-eh. It offers great sensitivity due to its high luminosity and low interference. In this work, thq FCNC interaction vertex with off-shell top quark decay at electron-proton colliders is studied. By using MadGraph5_aMC@NLO multi-purpose event generator, observability of tuh and tch couplings are obtained with equal coupling scenario. Upper limit on branching ratio of tree level top quark FCNC decay is determined as 0.012% at FCC-eh with 1 ab ^−1 luminosity.

Keywords: FCC, FCNC, Higgs Boson, Top Quark

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Authors: Sarah Ledoux

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This paper analyses the quantitative effects of political content consumption in social media platforms on self-reported ideological preference across the Latin American region. Initially praising the democratic potential of the internet and its social networking websites, digital politics scholars have transitioned their discourse to warning against the undemocratic side-effects it cultivates, such as hate speech, filter bubbles, and ideological polarisation. Holding technology solely responsible for political trends worldwide is an oversimplification of the factors influencing social change. Nonetheless, widespread use of social media in new democracies raises questions on the reproduction of recent trends that have been observed in the US and Western Europe. Through the analysis of ordered logistic regressions on data from the 2018 AmericasBarometer survey, this study examines the extent to which the relationship between the consumption of political content on social media is related to ideological polarisation in Latin America. The findings indicate that there is a close link between consumption of political information on social media, specifically on Facebook and WhatsApp, and ideological positioning on the extremes of the political left- and right-wings. This relation holds when controlling for individual-level demographic and attitudinal factors, as well as country-level effects. These results demonstrate with empirical evidence that viewing political content on social media has a significant positive effect on the likelihood that citizens position themselves on the extreme ends of the left-right ideological spectrum and implies that political polarisation is a phenomenon that accompanies politically driven social media use.

Keywords: Latin America, polarisation, political consumption, political ideology, social media, survey

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Authors: Irfan Nazir Wani, Pushpendra Kumar Shukla, Manoj Kumar

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Debris, also called waste or junk, present in orbit of Earth or orbital debris, offers a substantial challenge to space exploration. Satellite operations and other space-based activities. This research paper delves into the causes and effects of space debris accumulation, explores current mitigation techniques, and presents a hopeful outlook on the potential for future sustainable space activities. The paper emphasizes the necessity of addressing planetary fragments to ensure durable sustainability in universe exploration and utilization. It examines various strategies for mitigating space debris, including debris removal technologies, spacecraft design improvements, and international collaboration efforts. Additionally, the paper highlights the importance of space debris monitoring and tracking systems in preventing collisions and minimizing the growth of orbital debris. By comprehending the complexities of space debris and implementing effective mitigation measures, the space industry can work towards a future where sustainable space activities are achievable.

Keywords: space shuttle, debris, space junk, satellite, fragments, orbit

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Authors: Domenico Carmelo Mongelli, Laura Carnieletto, Michele De Carli, Filippo Busato

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Starting from the current context in which the Russian invasion in Ukraine has highlighted Europe's dependence on natural gas imports for heating buildings, this study proposes solutions to resolve this dependency and evaluates related scenarios in the near future. In the first part of this work the methodologies and results of the economic impact are indicated by simulating a massive replacement of boilers powered by fossil fuels with electrically powered hightemperature air-water heat pumps for heating residential buildings in different European climates, without changing the current energy mix. For each individual European region, the costs for the purchase and installation of heat pumps for all residential buildings have been determined. Again for each individual European region, the economic savings during the operation phase that would be obtained in this future scenario of energy transition from fossil fuels to the electrification of domestic heating were calculated. For the European regions for which the economic savings were identified as positive, the payback times of the economic investments were analysed. In the second part of the work, hypothesizing different scenarios for a possible greater use of renewable energy sources and therefore with different possible future scenarios of the energy mix, the methodologies and results of the simulations on the economic analysis and on the environmental analysis are reported which have allowed us to evaluate the future effects of the energy transition from boilers to heat pumps for each European region. In the third part, assuming a rapid short-term diffusion of cooling for European residential buildings, the penetration shares in the cooling market and future projections of energy needs for cooling for each European region have been identified. A database was created where the results of this research relating to 38 European Nations divided into 179 regions were reported. Other previous works on the topics covered were limited to analyzing individual European nations, without ever going into detail about the individual regions within each nation, while the original contribution of the present work lies in the fact that the results achieved allow a specific numerical analysis and punctual for every single European region.

Keywords: buildings, energy, Europe, future

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Authors: Rajneekant Bachan, Dhanush Vijay

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The visualization of operating systems has refined the Turing machine, and current trends suggest that the emulation of 32 bit architectures will soon emerge. After years of technical research into Web services, we demonstrate the synthesis of gigabit switches, which embodies the robust principles of theory. Loam, our new algorithm for forward-error correction, is the solution to all of these challenges.

Keywords: software engineering, architectures, introspective models, operating systems

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Authors: I. Agboola Julius, Christopher A. Kumolu-Johnson, O. Kolade Rafiu, A. Saba Abdulwakil

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This work elucidates on mangrove diversity, trends of change, factors responsible for loss over the years and implications for sustainable livelihoods of locals in four villages (Ajido (L1), Tarkwa bay (L2), University of Lagos (L3), and Ikosi (L4)) along the coast of Lagos, Nigeria. Primary data were collected through field survey, questionnaires, interviews, and review of existing literature. Field observation and data analysis reveals mangrove diversity as low and varied on a spatial scale, where Margalef’s Diversity Index (D) was 0.368, 0.269, 0.326, and 0.333, respectively for L1, L2, L3, and L4. Shannon Weiner’s Index (H) was estimated to be 1.003, 1.460, 1.160, 1.046, and Specie Richness (E) 0.913, 0.907, 0.858, and 0.015, respectively, for the four villages. Also, The Simpson’s index of diversity was analyzed to be 0.632, 0. 731, 0.647, 0.667, and Simpson’s reciprocal index 2.717, 3.717, 3.060, and 3.003, respectively, for the four villages. Chi-square test was used to analyze the impact of mangrove loss on the sustainable livelihood of coastal communities. Calculated Chi-square (X2) value (5) was higher than tabulated value (4.30), suggesting that loss of mangrove wetlands impacted on local communities’ livelihood at the four villages. Analyses of causes and trends of mangrove wetland loss over the years suggest that urbanization, fuel wood and agricultural activities are major causes. Current degradation observed in mangrove wetlands on the Lagos coast suggest a reduction in mangroves biodiversity and associated fauna with potential cascading effects on higher trophic levels such as fisheries. Low yield in fish catch, reduction in income and increasing cases of natural disaster has culminated in threats to sustainable livelihoods of local communities along the coast of Lagos.

Keywords: Mangroves, lagos coast, fisheries, management

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Authors: Jared Oluoch

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Connected vehicles are equipped with wireless sensors that aid in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication. These vehicles will in the near future provide road safety, improve transport efficiency, and reduce traffic congestion. One of the challenges for connected vehicles is how to ensure that information sent across the network is secure. If security of the network is not guaranteed, several attacks can occur, thereby compromising the robustness, reliability, and efficiency of the network. This paper discusses existing security mechanisms and unique properties of connected vehicles. The methodology employed in this work is exploratory. The paper reviews existing security solutions for connected vehicles. More concretely, it discusses various cryptographic mechanisms available, and suggests areas of improvement. The study proposes a combination of symmetric key encryption and public key cryptography to improve security. The study further proposes message aggregation as a technique to overcome message redundancy. This paper offers a comprehensive overview of connected vehicles technology, its applications, its security mechanisms, open challenges, and potential areas of future research.

Keywords: VANET, connected vehicles, 802.11p, WAVE, DSRC, trust, security, cryptography

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Authors: Sakkaphat T. Ngamake, Arunya Tuicomepee, Panrapee Suttiwan, Rewadee Watakakosol, Sompoch Iamsupasit

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Generally, 'positive' emotion regulation strategies such as cognitive reappraisal have linked to desirable outcomes while 'negative' strategies such as behavioral suppression have linked to undesirable outcomes. These trends have been found in both the elderly and professional practitioners. Hence, this study sought to investigate these trends further by examining the relationship between two dominant emotion regulation strategies in the literature (i.e., cognitive reappraisal and behavioral suppression) and well-being outcomes among the elderly (i.e., successful aging) and their caregivers (i.e., satisfaction with life), using the actor-partner interdependence model. A total of 150 elderly-caregiver dyads participated in the study. The elderly responded to two measures assessing the two emotion regulation strategies and successful aging while their caregivers responded to the same emotion regulation measure and a measure of satisfaction with life. Two criterion variables (i.e., successful aging and satisfaction with life) were specified as latent variables whereas four predictors (i.e., two strategies for the elderly and two strategies for their caregivers) were specified as observed variables in the model. Results have shown that, for the actor effect, the cognitive reappraisal strategy yielded positive relationships with the well-being outcomes for both the elderly and their caregivers. For the partner effect, a positive relationship between caregivers’ cognitive reappraisal strategy and the elderly’s successful aging was observed. The behavioral suppression strategy has not related to any well-being outcomes, within and across individual agents. This study has contributed to the literature by empirically showing that the mental activity of the elderly’s immediate environment such as their family members or close friends could affect their quality of life.

Keywords: emotion regulation, caregiver, older adult, well-being

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Authors: M. Rodionov, N. Sharapova, Z. Dedovets

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The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.

Keywords: education, methodological approaches, teacher, secondary school

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

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Authors: O. D. Adegbehingbe, S. D. Eyono Obono

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The education sector is constantly faced with rapid changes in technologies in terms of ensuring that the curriculum is up to date and in terms of making sure that students are aware of these technological changes. This challenge can be seen as the motivation for this study, which is to examine the factors affecting computing students’ awareness of the latest Information Technologies (ICTs). The aim of this study is divided into two sub-objectives which are: the selection of relevant theories and the design of a conceptual model to support it as well as the empirical testing of the designed model. The first objective is achieved by a review of existing literature on technology adoption theories and models. The second objective is achieved using a survey of computing students in the four universities of the KwaZulu-Natal province of South Africa. Data collected from this survey is analyzed using Statistical package for the Social Science (SPSS) using descriptive statistics, ANOVA and Pearson correlations. The main hypothesis of this study is that there is a relationship between the demographics and the prior conditions of the computing students and their awareness of general ICT trends and of Digital Switch Over (DSO) a new technology which involves the change from analog to digital television broadcasting in order to achieve improved spectrum efficiency. The prior conditions of the computing students that were considered in this study are students’ perceived exposure to career guidance and students’ perceived curriculum currency. The results of this study confirm that gender, ethnicity, and high school computing course affect students’ perceived curriculum currency while high school location affects students’ awareness of DSO. The results of this study also confirm that there is a relationship between students prior conditions and their awareness of general ICT trends and DSO in particular.

Keywords: education, information technologies, IDT, awareness

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Authors: Enido Fabiano de Ramos, Ieda Kanashiro Makiya, Francisco I. Giocondo Cesar

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This study investigates the application of Digital Twins (DT) in Smart Hospital Environments (SHE), through a bibliometric study and literature review, including comparison with the principles of Industry 4.0. It aims to analyze the current state of the implementation of digital twins in clinical and non-clinical operations in healthcare settings, identifying trends and challenges, comparing these practices with Industry 4.0 concepts and technologies, in order to present a basic framework including stages and maturity levels. The bibliometric methodology will allow mapping the existing scientific production on the theme, while the literature review will synthesize and critically analyze the relevant studies, highlighting pertinent methodologies and results, additionally the comparison with Industry 4.0 will provide insights on how the principles of automation, interconnectivity and digitalization can be applied in healthcare environments/operations, aiming at improvements in operational efficiency and quality of care. The results of this study will contribute to a deeper understanding of the potential of Digital Twins in Smart Hospitals, in addition to the future potential from the effective integration of Industry 4.0 concepts in this specific environment, presented through the practical framework, after all, the urgent need for changes addressed in this article is undeniable, as well as all their value contribution to human sustainability, designed in SDG3 – Health and well-being: ensuring that all citizens have a healthy life and well-being, at all ages and in all situations. We know that the validity of these relationships will be constantly discussed, and technology can always change the rules of the game.

Keywords: digital twin, smart hospital, healthcare operations, industry 4.0, SDG3, technology

Procedia PDF Downloads 48

Authors: Rigved Chandrashekhar Nimkhedkar, Rajat Agrawal, Vinay Sharma

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Architects need help with a demand for an expanded skill set to effectively navigate a landscape of evolving opportunities and challenges in the dynamic realm of the architectural profession. This literature and survey-based study investigates the reasons behind architects’ choices of careers, as well as the effects of the evolving architectural scenario. The traditional role of architects in construction projects evolves as they explore diverse career motivations, face financial constraints due to an oversupply of professionals, and experience specialisation and upskilling trends. Architects inherently derive numerous value chains as more and more disciplines have been introduced into the design-construction-operation supply chain. This insight emphasizes the importance of integrating management and entrepreneurial education into architectural education rather than keeping them separate entities. The study reveals the complex nature of the entrepreneurially challenging architectural profession, including cash flow management, market competition, environmental sustainability, and innovation opportunities. Loyal to their professional identity, architects express dissatisfaction while envisioning a future in which they play a more significant role in shaping reputable brands and contributing to education. The study emphasizes the importance of dovetailing management and entrepreneurial education in architecture education in preparing graduates for the industry’s changing nature, emphasising the need for real-world skills. This research contributes insights into the architectural profession’s transformative trajectory, emphasising adaptability, upskilling, and educational enhancements as critical success factors.

Keywords: architects, career path, education, management, specialisation

Procedia PDF Downloads 57

Authors: David Blaine, George Raschbaum

Abstract:

The evaluation of DHCP has synthesized SCSI disks, and current trends suggest that the exploration of e-business that would allow for further study into robots will soon emerge. Given the current status of embedded algorithms, hackers worldwide obviously desire the exploration of replication, which embodies the confusing principles of programming languages. In our research we concentrate our efforts on arguing that erasure coding can be made "fuzzy", encrypted, and game-theoretic.

Keywords: SCHI disks, robot, algorithm, hacking, programming language

Procedia PDF Downloads 416

Authors: Richard Grant, Landolf Rhode-Barbarigos, Shouraseni Sen Roy, Lucas Brittan, Change Li, Aiden Rowe

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Ports are critical for the US economy, connecting farmers, manufacturers, retailers, consumers and an array of transport and storage operators. Port facilities vary widely in terms of their productivity, footprint, specializations, and governance. In this context, Port Miami is considered as one of the busiest ports providing both cargo and cruise services in connecting the wider region of the Caribbean and Mesoamerica to the global networks. It is considered as the “Cruise Capital of the World and Global Gateway of the Americas” and “leading container port in Florida.” Furthermore, it has also been ranked as one of the top container ports in the world and the second most efficient port in North America. In this regard, Port Miami has made significant investments in the strategic and capital infrastructure of about US$1 billion, including increasing the channel depth and other onshore infrastructural enhancements. Therefore, this study involves a detailed analysis of Port Miami’s network, using publicly available multiple years of data about marine vessel traffic, cargo, and connectivity and performance indices from 2015-2021. Through the analysis of cargo and cruise vessels to and from Port Miami and its relative performance at the global scale from 2015 to 2021, this study examines the port’s long-term resilience and future growth potential. The main results of the analyses indicate that the top category for both inbound and outbound cargo is manufactured products and textiles. In addition, there are a lot of fresh fruits, vegetables, and produce for inbound and processed food for outbound cargo. Furthermore, the top ten port connections for Port Miami are all located in the Caribbean region, the Gulf of Mexico, and the Southeast USA. About half of the inbound cargo comes from Savannah, Saint Thomas, and Puerto Plata, while outbound cargo is from Puerto Corte, Freeport, and Kingston. Additionally, for cruise vessels, a significantly large number of vessels originate from Nassau, followed by Freeport. The number of passenger's vessels pre-COVID was almost 1,000 per year, which dropped substantially in 2020 and 2021 to around 300 vessels. Finally, the resilience and competitiveness of Port Miami were also assessed in terms of its network connectivity by examining the inbound and outbound maritime vessel traffic. It is noteworthy that the most frequent port connections for Port Miami were Freeport and Savannah, followed by Kingston, Nassau, and New Orleans. However, several of these ports, Puerto Corte, Veracruz, Puerto Plata, and Santo Thomas, have low resilience and are highly vulnerable, which needs to be taken into consideration for the long-term resilience of Port Miami in the future.

Keywords: port, Miami, network, cargo, cruise

Procedia PDF Downloads 75

Authors: Alonso-Cañadas J., Galán-Valdivieso F., Saraite-Sariene L., García-Tabuyo M., Alonso-Morales N.

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Green Public Procurement (GPP) has recently gained attention in the academic and policy arenas since climate change has shown the need to be addressed by both private companies and public entities. Such growing interest motivates this article, aiming to explore the most influential journals, publishers, categories, and topics, as well as the recent trends and future research lines in GPP. Based on the Web of Science database, 578 articles from 2004 to February 2022 devoted to GPP are analyzed using Bibliometrix, an R-tool to perform bibliometric analysis, and Google’s Big Query and Data Studio. This article introduces a variety of findings. First, the most influential journals by far are “Journal of Cleaner Production” and “Sustainability,” differing in that the latter is open access while the former publishes via traditional subscription. This result also occurs regarding the main publishers (Elsevier and MDPI). These features lead us to split the sample into open-access journals and traditional journals to deepen into the similarities and differences between them, confirming that traditional journals exhibit a higher degree of influence in the literature than their open-access counterparts in terms of the number of documents, number of citations and impact (according to the H index). Second, this research also highlights the recent emergence of green-related terms (sustainable, environment) and, parallelly, the increase in categorizing GPP papers in “green” WoS categories, particularly since 2019. Finally, a number of related topics are emerging and will lead the research, such as food security, infrastructures, and implementation barriers of GPP.

Keywords: bibliometric analysis, green public procurement, open access, traditional journals

Procedia PDF Downloads 97

Authors: Selim M. Khan, Dustin D. Pearson, Tryggve Rönnqvist, Markus E. Nielsen, Joshua M. Taron, Aaron A. Goodarzi

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Accumulation of radioactive radon gas in indoor air poses a serious risk to human health by increasing the lifetime risk of lung cancer and is classified by IARC as a category one carcinogen. Radon exposure risks are a function of geologic, geographic, design, and human behavioural variables and can change over time. Using time series and deep machine learning modelling, we analyzed long-term radon test outcomes as a function of building metrics from 25,489 Canadian and 38,596 Swedish residential properties constructed between 1945 to 2020. While Canadian and Swedish properties built between 1970 and 1980 are comparable (96–103 Bq/m³), innate radon risks subsequently diverge, rising in Canada and falling in Sweden such that 21st Century Canadian houses show 467% greater average radon (131 Bq/m³) relative to Swedish equivalents (28 Bq/m³). These trends are consistent across housing types and regions within each country. The introduction of energy efficiency measures within Canadian and Swedish building codes coincided with opposing radon level trajectories in each nation. Deep machine learning modelling predicts that, without intervention, average Canadian residential radon levels will increase to 176 Bq/m³ by 2050, emphasizing the importance and urgency of future building code intervention to achieve systemic radon reduction in Canada.

Keywords: radon health risk, time-series, deep machine learning, lung cancer, Canada, Sweden

Procedia PDF Downloads 80

Authors: Kuribachew Gizaw Tohiye, Monica Garfield

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Personal knowledge management is the aspect of knowledge management that relates to the way in which individuals organize and manage their own set of knowledge. While in that respect, there has been research in this area for the past 25 years, it is at present necessary to speculate upon what research has been done and what we have discovered about this arena of knowledge management. In contrast to organizational knowledge management, which focuses on a firm’s profitability and competitiveness, personal knowledge management (PKM) is concerned with the person’s self-effectiveness, competence and success. People are concerned in managing their knowledge in order to become more efficient in a variety of personal and organizational interests. This study presents a systematic review of PKM studies. Articles with PKM concepts are reviewed with the objective of clearly defining PKM, identifying the benefits of PKM, classifying the tools that enable PKM and finding the research gaps to indicate future research directions in the area. Consequently, we have developed a definition of PKM and identified the benefits of PKM, including an understanding of who seeks PKM and for what. Tools enabling PKM are identified and classified under three categories Web 1.0, 2.0 and 3.0 and finally the research gap and future directions are suggested. Research which facilitates collaboration by using semantic technologies is suggested to be studied further to improve PKM effectiveness.

Keywords: personal knowledge management, knowledge management, organizational knowledge management, systematic review

Procedia PDF Downloads 318