Search results for: stochastic preferences

Authors: Sharon Jackson, Lynn Kelly

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This paper proposes a conceptual review of the interdisciplinary literature which has theorised the concept of ‘children’s voices’. The primary aim is to identify and consider the theoretical relevance of conceptual thought on ‘children’s voices’ for research and practice in child protection contexts. Attending to the ‘voice of the child’ has become a core principle of social work practice in contemporary child protection contexts. Discourses of voice permeate the legislative, policy and practice frameworks of child protection practices within the UK and internationally. Voice is positioned within a ‘child-centred’ moral imperative to ‘hear the voices’ of children and take their preferences and perspectives into account. This practice is now considered to be central to working in a child-centered way. The genesis of this call to voice is revealed through sociological analysis of twentieth-century child welfare reform as rooted inter alia in intersecting political, social and cultural discourses which have situated children and childhood as cites of state intervention as enshrined in the 1989 United Nations Convention on the Rights of the Child ratified by the UK government in 1991 and more specifically Article 12 of the convention. From a policy and practice perspective, the professional ‘capturing’ of children’s voices has come to saturate child protection practice. This has incited a stream of directives, resources, advisory publications and ‘how-to’ guides which attempt to articulate practice methods to ‘listen’, ‘hear’ and above all – ‘capture’ the ‘voice of the child’. The idiom ‘capturing the voice of the child’ is frequently invoked within the literature to express the requirements of the child-centered practice task to be accomplished. Despite the centrality of voice, and an obsession with ‘capturing’ voices, evidence from research, inspection processes, serious case reviews, child abuse and death inquires has consistently highlighted professional neglect of ‘the voice of the child’. Notable research studies have highlighted the relative absence of the child’s voice in social work assessment practices, a troubling lack of meaningful engagement with children and the need to more thoroughly examine communicative practices in child protection contexts. As a consequence, the project of capturing ‘the voice of the child’ has intensified, and there has been an increasing focus on developing methods and professional skills to attend to voice. This has been guided by a recognition that professionals often lack the skills and training to engage with children in age-appropriate ways. We argue however that the problem with ‘capturing’ and [re]representing ‘voice’ in child protection contexts is, more fundamentally, a failure to adequately theorise the concept of ‘voice’ in the ‘voice of the child’. For the most part, ‘The voice of the child’ incorporates psychological conceptions of child development. While these concepts are useful in the context of direct work with children, they fail to consider other strands of sociological thought, which position ‘the voice of the child’ within an agentic paradigm to emphasise the active agency of the child.

Keywords: child-centered, child protection, views of the child, voice of the child

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Authors: Roberto M. G. Velásquez, Jonas R. Gazoli, Nelson Ponce Jr, Valério L. Borges, Alessandro Sete, Fernanda M. C. Tomé, Julian D. Hunt, Heitor C. Lira, Cristiano L. de Souza, Fabio T. Bindemann, Wilmar Wounnsoscky

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Nowadays, society is working toward reducing energy losses and greenhouse gas emissions, as well as seeking clean energy sources, as a result of the constant increase in energy demand and emissions. Energy loss occurs in the gas pressure reduction stations at the delivery points in natural gas distribution systems (city gates). Installing pressure reduction turbines (PRT) parallel to the static reduction valves at the city gates enhances the energy efficiency of the system by recovering the enthalpy of the pressurized natural gas, obtaining in the pressure-lowering process shaft work and generating electrical power. Currently, the Brazilian natural gas transportation network has 9,409 km in extension, while the system has 16 national and 3 international natural gas processing plants, including more than 143 delivery points to final consumers. Thus, the potential of installing PRT in Brazil is 66 MW of power, which could yearly avoid the emission of 235,800 tons of CO2 and generate 333 GWh/year of electricity. On the other hand, an economic viability analysis of these energy efficiency projects is commonly carried out based on estimates of the project's cash flow obtained from several variables forecast. Usually, the cash flow analysis is performed using representative values of these variables, obtaining a deterministic set of financial indicators associated with the project. However, in most cases, these variables cannot be predicted with sufficient accuracy, resulting in the need to consider, to a greater or lesser degree, the risk associated with the calculated financial return. This paper presents an approach applied to the technical-economic viability analysis of PRTs projects that explicitly considers the uncertainties associated with the input parameters for the financial model, such as gas pressure at the delivery point, amount of energy generated by TRP, the future price of energy, among others, using sensitivity analysis techniques, scenario analysis, and Monte Carlo methods. In the latter case, estimates of several financial risk indicators, as well as their empirical probability distributions, can be obtained. This is a methodology for the financial risk analysis of PRT projects. The results of this paper allow a more accurate assessment of the potential PRT project's financial feasibility in Brazil. This methodology will be tested at the Cuiabá thermoelectric plant, located in the state of Mato Grosso, Brazil, and can be applied to study the potential in other countries.

Keywords: pressure reduction turbine, natural gas pressure drop station, energy efficiency, electricity generation, monte carlo methods

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Authors: Zhe Wang

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The fashion week, as a critical international fashion event in shaping world fashion cities, is one of the most significant world events that serves as the core medium for designers to stage new collections. However, its role in bringing about and shaping design ideologies of major fashion cities have long been neglected from a fashion ecosystem perspective. With the expanding scale of international fashion weeks in terms of culture and commerce, the organizational structures of these fashion weeks are becoming more complex. In the emerging fashion city, typified by Shanghai, a newly-formed 'hodgepodge' transforming the current global fashion ecosystem. A city’s legitimate fashion institutions, typically the organizers of international fashion weeks, have cultivated various cultural characteristics via rules and regulations pertaining to international fashion weeks. Under these circumstances, designers’ participatory behaviors, specifically show design and production, are influenced by the cultural ideologies of official organizers and institutions. This research compares international based Chinese (IBC) independent designers’ participatory behavior in London and Shanghai Fashion Weeks: specifically, the way designers present their clothing and show production. both of which are found to be profoundly influenced by cultural and design ideologies of fashion weeks. They are, to a large degree, manipulated by domestic institutions and organizers. Shanghai fashion week has given rise to a multiple, mass-ended entertainment carnival design and cultural ideology in Shanghai, thereby impacting the explicit cultural codes or intangible rules that IBC designers must adhere to when designing and producing fashion shows. Therefore, influenced by various cultural characteristics in the two cities, IBC designers’ show design and productions, in turn, play an increasingly vital role in shaping the design characteristic of an international fashion week. Through researching the organizational systems and design preferences of organizers of London and Shanghai fashion weeks, this paper demonstrates the embeddedness of design systems in the forming of design ideologies under various cultural and institutional contexts. The core methodology utilized in this research is ethnography. As a crucial part of a Ph.D. project on innovations in fashion shows under a cross-cultural context run by Edinburgh College of Art, School of Design, the fashion week’s organizational culture in various cultural contexts is investigated in London and Shanghai for approximately six months respectively. Two IBC designers, Angel Chen and Xuzhi Chen were followed during their participation of London and Shanghai Fashion Weeks from September 2016 to June 2017, during which two consecutive seasons were researched in order to verify the consistency of design ideologies’ associations with organizational system and culture.

Keywords: institutional ideologies, international fashion weeks, IBC independent designers; fashion show

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Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

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Authors: Fabrizio Ascione, Martina Borrelli, Rosa Francesca De Masi, Silvia Ruggiero, Giuseppe Peter Vanoli

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The refurbishment of public buildings is one of the key factors of energy efficiency policy of European States. Educational buildings account for the largest share of the oldest edifice with interesting potentialities for demonstrating best practice with regards to high performance and low and zero-carbon design and for becoming exemplar cases within the community. In this context, this paper discusses the critical issue of dealing the energy refurbishment of a university building in heating dominated climate of South Italy. More in detail, the importance of using validated models will be examined exhaustively by proposing an analysis on uncertainties due to modelling assumptions mainly referring to the adoption of stochastic schedules for occupant behavior and equipment or lighting usage. Indeed, today, the great part of commercial tools provides to designers a library of possible schedules with which thermal zones can be described. Very often, the users do not pay close attention to diversify thermal zones and to modify or to adapt predefined profiles, and results of designing are affected positively or negatively without any alarm about it. Data such as occupancy schedules, internal loads and the interaction between people and windows or plant systems, represent some of the largest variables during the energy modelling and to understand calibration results. This is mainly due to the adoption of discrete standardized and conventional schedules with important consequences on the prevision of the energy consumptions. The problem is surely difficult to examine and to solve. In this paper, a sensitivity analysis is presented, to understand what is the order of magnitude of error that is committed by varying the deterministic schedules used for occupation, internal load, and lighting system. This could be a typical uncertainty for a case study as the presented one where there is not a regulation system for the HVAC system thus the occupant cannot interact with it. More in detail, starting from adopted schedules, created according to questioner’ s responses and that has allowed a good calibration of energy simulation model, several different scenarios are tested. Two type of analysis are presented: the reference building is compared with these scenarios in term of percentage difference on the projected total electric energy need and natural gas request. Then the different entries of consumption are analyzed and for more interesting cases also the comparison between calibration indexes. Moreover, for the optimal refurbishment solution, the same simulations are done. The variation on the provision of energy saving and global cost reduction is evidenced. This parametric study wants to underline the effect on performance indexes evaluation of the modelling assumptions during the description of thermal zones.

Keywords: energy simulation, modelling calibration, occupant behavior, university building

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Tereza Hruskova

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200 million people globally experience serious mental health problems, and only one third seek professional help, and help-seeking is described as a last resort. Adolescents and young adults have a high prevalence of mental illness. Mental stigma is a key element in the decision to seek help and is divided into (i) self-stigma (self-stigmatization), including internal beliefs, low self-esteem, and lower quality of life, and (ii) public stigma (social stigma) containing stereotypes, beliefs and society's disapproval of help-seeking having a negative effect on help-seeking and our attitudes. Previous research has mainly focused on examining the construct of help seeking, avoidance, and delaying separately and trying to find out why people do not seek help in time and what obstacles stand in the way. Barriers are not static and may change over time and the stage of help-seeking. Attitudes are closely related to self-stigma and social stigma and predict whether a person will seek help. Barriers (stigmatization, a sense of humiliation, insufficient recognition of the problem, preferences, solving it alone, and distrust of a professional) and facilitators (previous experience with mental problems, social support, and help from others) are factors influencing help-seeking. The current research on the Czech population of young adults responds to the gap between a person with mental health problems and actually seeking professional help. The aim of the study is to describe in detail the individual constructs and factors, to understand the person seeking help, and to define possible obstacles on this path of seeking help. A sample of approximately 250 participants (age 18-35) would take part in the online questionnaire, conducted in May-June 2023, and would be administered a demographic questionnaire and four scales measuring attitudes (Attitudes Toward Seeking Professional Psychological Help – Short form), barriers (Barrier to Help Seeking Scale), self-stigma (Self Stigma of Seeking Help) and stigmatization (Perceptions of Stigmatization by Others for seeking help). Firstly, all four scales would be translated into the Czech language. The aim is (I) to determine the validity and reliability of the Czech translation of the scales, (II) to examine the factors of the scales on the Czech population and compare them retrospectively with the results of reliability and validity from the original language of the scales and (III) to examine the connections between attitudes towards seeking, avoidance or delaying the search for professional psychological help due to the demographic and individual differences of the participants, barriers, self-stigmatization and social stigmatization. We expect to carry out the first study on the given topic in the Czech Republic, to identify and better understand the factors leading to the avoidance of seeking professional help and to reveal the relationships between stigmatization, attitudes and barriers leading to the avoidance or postponement of seeking professional help. The belief is to find out whether the Czech population of young adults differs from the data found on the foreign population in individual constructs, as cultural differences in individual countries were found.

Keywords: mental health, stigma, problems, seeking psychological help

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Authors: Maja Martinovic, Valentina Zarkovic, Hrvoje Maljak

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Europe is one of the most popular tourist destinations in the world, in which tourism occupies a significant place among the most relevant economic activities, and this applies to the Republic of Croatia as well. Based on this study, the authors intended to encourage and support the creation of an effective tourism policy in Croatia that would be based on the profiling of certain target groups. Another objective was to compare the results obtained from the customer analysis with the market analysis of the tourism industry in Croatia. The objective is to adapt the current tourist offer according to the identified needs and expectations of a particular tourist group in order to increase the attractiveness of Croatia as a tourist destination and motivate greater attendance of the targeted tourist groups. The current research was oriented towards the Russian market as the target group. Therefore, the authors wanted to encourage a discussion on how to attract more Russian guests. Consequently, the intention of the research was a detailed analysis of Russian tourists, in order to gain a better understanding of their travelling motives and tendencies. Furthermore, attention was paid to the expectations of Russian customers and to compare them with the Croatian tourist offer, and to determine whether there is a possibility for an overlap. The method used to obtain the information required was a survey conducted among Russian citizens about their travelling habits. The research was carried out on the basis of 166 participants of different age, gender, profession and income group. The sampling and distribution of the survey took place between May and July 2016. The results provided from the research indicate that Croatian tourism has certain unrealized potential considering the popularization of Croatia as a tourist destination, and there is a capacity for increasing the revenues within the group of Russian tourists. Such a conclusion is based on the fact that the Croatian tourist offer and the preferences of the Russian guests are compatible, i.e. they overlap in many aspects. The results demonstrate that beautiful nature, cultural and historical heritage as well as the sun and sea, play a leading role in attracting more Russian tourists. It is precisely these elements that form the three pillars of the Croatian tourist offer. On the other hand, the profiling revealed that the most desirable destinations for the Russian guests are Italy and Spain, both of which provide the same main tourist attractions as Croatia. Therefore, the focus of the strategic ideas given in the paper shifted to other tourism segments, such as type of accommodation, sales channels, travel motives, additional offer and seasonality etc., in order to gain advantage in the Russian market, the Mediterranean region and tourism in general. The purpose of the research is to serve as a foundation for analysing the attractiveness of the other tourist destinations in the Russian market, as well as to be a general basis for a more detailed profiling of the various specific target groups of the Russian and other tourist groups.

Keywords: Croatia, Russian market, target groups, tourism, tourist destination

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Authors: Archil Undilashvili, Ketevan Stvilia, Dustin Gilbreath, Giorgi Dzneladze, Gordon Charchward

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Introduction: In recent years, diverse types of wheelchairs, both local production and imported, have been made available on the Georgian market for wheelchair users. Some types of wheelchairs are sold together with a service package, while the others, including the State Program, Supported locally-produced ones, don’t provide adjustment and maintenance service packages to users. Within the USAID Physical Rehabilitation Project in Georgia, a study was conducted to assess the impact of the wheelchair service provision in line with the WHO guidelines on the health and overall satisfaction of wheelchair users in Georgia. Methodology: A cross-sectional survey was conducted in May 2021. A structured questionnaire was used for telephone interviews that, along with socio-demographic characteristics, included questions for assessment of accessibility, availability, timeliness, cost and quality of wheelchair services received. Out of 1060 individuals listed in the census of wheelchair users, 752 were available for interview, with an actual response rate of 73.4%. 552 wheelchair users (31%) or their caregivers (69%) agreed to participate in the survey. In addition to using descriptive statistics, the study used multivariate matching of wheelchair users who received wheelchair services and who did not (control group). In addition, to evaluate satisfaction with service provision, respondents were asked to assess services. Findings: The majority (67%) of wheelchair users included in the survey were male. The average age of participants was 43. The three most frequently named reasons for using a wheelchair were cerebral palsy (29%), followed by stroke (18%), and amputation (12%). Users have had their current chair for four years on average. Overall, 60% of respondents reported that they were assessed before providing a wheelchair, but only half of them reported that their preferences and needs were considered. Only 13% of respondents had services in line with WHO guidelines and only 22% of wheelchair users had training when they received their current chair. 16% of participants said they had follow-up services, and 41% received adjustment services after receiving the chair. A slight majority (56%) of participants were satisfied with the quality of service provision and the service provision overall. Similarly, 55% were satisfied with the accessibility of service provision. A slightly larger majority (61%) were satisfied with the timeliness of service provision. The matching analysis suggests that users that received services in line with WHO guidelines were more satisfied with their chairs (the difference 17 point/0-100 scale) and they were four percentage points less likely to have health problems attributed to the chair. The regression analysis provides a similar finding of a 21 point increase in satisfaction attributable to services. Conclusion: The provision of wheelchair services in line with WHO guidelines and with follow-up services is likely to have a positive impact on the daily lives of wheelchair users in Georgia. Wheelchair services should be institutionalized as a standard component of wheelchair provision in Georgia.

Keywords: physical rehabilitation, wheelchair users, persons with disabilities, wheelchair production

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Authors: Shiau-Fang Chao, Yu-Chih Chen

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Owing to physical limitations and restrained lifestyle, older long-term care (LTC) residents are more likely to be affected by their environment than their community-dwelling counterparts. They also participate fewer activities and experience worse mental health than healthy older adults. This study adopts the ICF model to determine the extent to which the clustered patterns of LTC environment and activity participation are associated with older residents’ mental health. Method: Data were collected from a stratified equal probability sample of 634 older residents in 155 LTC institutions in Taiwan. Latent profile analysis (LPA) and latent class analysis (LCA) were conducted to explore the profiles for environment and activity participation. Multilevel modeling was performed to elucidate the relationships among environment profiles, activity profiles, and mental health. Results: LPA identified three mutually exclusive environment profiles (Low-, Moderate-, and High-Support Environment) based on the physical, social, and attitudinal environmental domains, consolidated from 12 environmental measures. LCA constructed two distinct activity profiles (Low- and High-Activity Participation) across seven activity domains (outdoor, volunteer-led leisure, spiritual, household chores, interpersonal exchange, social, and sedentary activity) that were factored from 20 activities. Compared to the Low-Support Environment class, older adults in the Moderate- and High-Support Environment classes had better mental health. Older residents in the Moderate- and High-Support Environment classes were more likely to be in the “High Activity” class, which in turn, exhibited better mental health. Conclusion: This study advances the current knowledge through rigorous methods and study design. The study findings lead to several conclusions. First, this study supports the use of ICF framework to institutionalized older individuals with functional limitations and demonstrates that both measures of environment and activity participation can be refined from multiple indicators. Second, environmental measures that encompass the physical, social, and attitudinal domains would provide a more comprehensive assessment on the place where an older individual embeds. Third, simply counting activities in which an older individual participates or considering a certain type of activity may not capture his or her way of life. Practitioners should not only focus on group or leisure activities within the institutions; rather, more efforts should be made to consider residents’ preferences for everyday life and support their remaining ability by encouraging continuous participation in activities they still willing and capable to perform. Fourth, environment and activity participation are modifiable factors which have greater potential to strengthen older LTC residents’ mental health, and activity participation should be considered in the link between environment and mental health. A combination of enhanced physical, social, and attitudinal environments, and continual engagement in various activities may optimize older LTC residents’ mental health.

Keywords: activity, environment, mental health, older LTC residents

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Authors: Jean-Eric Pelet, Erhard Lick, Basma Taieb

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Purpose This research bridges the gap between sensory marketing and the use of the Internet of Things (IoT) in luxury hotels. We investigated how stimulating guests’ senses through IoT devices influenced their emotions, affective experiences, eudaimonism (well-being), and, ultimately, guest behavior. We examined potential moderating effects of gender. Design/methodology/approach We adopted a mixed method approach, combining qualitative research (semi-structured interviews) to explore hotel managers’ perspectives on the potential use of IoT in luxury hotels and quantitative research (surveying hotel guests; n=357). Findings The results showed that while the senses of smell, hearing, and sight had an impact on guests’ emotions, the senses of touch, hearing, and sight impacted guests’ affective experiences. The senses of smell and taste influenced guests’ eudaimonism. The sense of smell had a greater effect on eudaimonism and behavioral intentions among women compared to men. Originality IoT can be applied in creating customized multi-sensory hotel experiences. For example, hotels may offer unique and diverse ambiences in their rooms and suites to improve guest experiences. Research limitations/implications This study concentrated on luxury hotels located in Europe. Further research may explore the generalizability of the findings (e.g., in other cultures, comparison between high-end and low-end hotels). Practical implications Context awareness and hyper-personalization, through intensive and continuous data collection (hyper-connectivity) and real time processing, are key trends in the service industry. Therefore, big data plays a crucial role in the collection of information since it allows hoteliers to retrieve, analyze, and visualize data to provide personalized services in real time. Together with their guests, hotels may co-create customized sensory experiences. For instance, if the hotel knows about the guest’s music preferences based on social media as well as their age and gender, etc. and considers the temperature and size (standard, suite, etc.) of the guest room, this may determine the playlist of the concierge-tablet made available in the guest room. Furthermore, one may record the guest’s voice to use it for voice command purposes once the guest arrives at the hotel. Based on our finding that the sense of smell has a greater impact on eudaimonism and behavioral intentions among women than men, hotels may deploy subtler scents with lower intensities, or even different scents, for female guests in comparison to male guests.

Keywords: affective experience, emotional value, eudaimonism, hospitality industry, Internet of Things, sensory marketing

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Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

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Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

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Authors: D. Scarpanti, M. Brondino, M. Pasini

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Background: the present study explores the role of light and restorativeness on work. According with the Attention Restoration Theory (ART) and a Model of Work Environment, the main idea is that some features of environment, i.e., lighting, influences the direct attention, and so, the performance. Restorativeness refers to the presence/absence level of all the characteristics of physical environment that help to regenerate direct attention. Specifically, lighting can affect level of fascination and attention in one hand; and in other hand promotes several biological functions via pineal gland. Different reviews on this topic show controversial results. In order to bring light on this topic, the hypotheses of this study are that lighting can affect the construct of restorativeness and, in the second time, the restorativeness can affect the performance. Method: the participants are 30 workers of a mechatronic company in the North Italy. Every subject answered to a questionnaire valuing their subjective perceptions of environment in a different way: some objective features of environment, like lighting, temperature and air quality; some subjective perceptions of this environment; finally, the participants answered about their perceived performance. The main attention is on the features of light and his components: visual comfort, general preferences and pleasantness; and the dimensions of the construct of restorativeness; fascination, coherence and being away. The construct of performance per se is conceptualized in three level: individual, team membership and organizational membership; and in three different components: proficiency, adaptability, and proactivity, for a total of 9 subcomponents. Findings: path analysis showed that some characteristics of lighting respectively affected the dimension of fascination; and, as expected, the dimension of fascination affected work performance. Conclusions: The present study is a first pilot step of a wide research. These first results can be summarized with the statement that lighting and restorativeness contribute to explain work performance variability: in details perceptions of visual comfort, satisfaction and pleasantness, and fascination respectively. Results related to fascination are particularly interesting because fascination is conceptualized as the opposite of the construct of direct attention. The main idea is, in order to regenerate attentional capacity, it’s necessary to provide a lacking of attention (fascination). The sample size did not permit to test simultaneously the role of the perceived characteristics of light to see how they differently contribute to predict fascination of the work environment. However, the results highlighted the important role that light could have in predicting restorativeness dimensions and probably with a larger sample we could find larger effects also on work performance. Furthermore, longitudinal data will contribute to better analyze the causal model along time. Applicative implications: the present pilot study highlights the relevant role of lighting and perceived restorativeness in the work environment and the importance to focus attention on light features and the restorative characteristics in the design of work environments.

Keywords: lighting, performance, restorativeness, workplace

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

Procedia PDF Downloads 305

Authors: Jo Parsons, Cath Grimley, Debra Bick, Sarah Hillman, Louise Clarke, Helen Atherton

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The problem: Vaccinations are routinely offered to pregnant women in the UK for influenza (flu), pertussis (whooping cough), and COVID-19, yet the uptake of these vaccinations in pregnancy remains low. Pregnant women are at increased risk of hospitalisation, morbidity, and mortality from these preventable illnesses, which can also expose their unborn babies to an increased risk of serious complications, including in utero death. This research aims to explore how pregnant women feel about vaccinations offered during pregnancy (flu, whooping cough, and COVID-19), particularly following the COVID-19 pandemic. It also aims to examine factors influencing women’s decisions about vaccinations during pregnancy and how they feel about their health and vulnerabilities to illness arising from the COVID-19 pandemic. The approach: This is a qualitative study involving semi-structured interviews with pregnant women and midwives in the UK. Interviews with pregnant women explored their views since the COVID-19 pandemic about vaccinations offered during pregnancy and whether the pandemic has influenced perceptions of vulnerability to illness in pregnant women. Interviews with midwives explored vaccination discussions they routinely have with pregnant women and identified some of the barriers to vaccination that pregnant women discuss with them. Pregnant women were recruited via participating hospitals and community groups. Midwives were recruited via participating hospitals and midwife-specific social media groups. All interviews were conducted remotely (using telephone or Microsoft Teams) and analysed using thematic analysis. Findings: 43 pregnant women and 16 midwives were recruited and interviewed. The findings presented will focus on data from pregnant women. Pregnant women reported a wide range of views and vaccination behaviour, and identified several factors influencing their decision whether to accept vaccinations or not. These included internal factors (comprised of beliefs about susceptibility to illness, perceptions of immunity, fear, and feelings of responsibility), other influences (including visibility of illness and external influences such as healthcare professional recommendations), vaccination-related factors (comprised of beliefs about effectiveness and safety of vaccinations, availability and accessibility of vaccinations and preferences for alternative forms of protection to vaccination) and COVID-19 specific factors (including COVID-19 vaccinations and COVID-19 specific influences). Implications: Findings identified some of the factors that affect pregnant women’s decisions when deciding to have a vaccination or not and how these decisions have been influenced by COVID-19. Findings highlight areas where healthcare professional advice needs to focus, such as the provision of information about the increased vulnerability to illnesses during pregnancy and consideration of opportunistic vaccination at hospital appointments to maximise uptake of vaccinations during pregnancy. Findings of this study will inform the development of an intervention to increase vaccination uptake amongst pregnant women.

Keywords: vaccination, pregnancy, qualitative, interviews, COVID-19

Procedia PDF Downloads 65

Authors: Nasser Koleini Mamaghani, Sara Mostowfi

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The complexity of public space design makes it difficult for designers to simultaneously consider all issues for thorough decision-making. Among public spaces, the public space around people’s house is the most prominent space that affects and impacts people’s daily life. Considering recreational public spaces in cities, their main purpose would be to design for experiences that enable a deep feeling of peace and a moment of being away from the hectic daily life. Respecting human emotions and restoring natural environments, although difficult and to some extent out of reach, are key issues for designing such spaces. In this paper we propose to analyse the structure of recreational public spaces and the related emotional impressions. Furthermore, we suggest investigating how these structures influence people’s choice for public spaces by using differential semantics. According to Kansei methodology, in order to evaluate a situation appropriately, the assessment variables must be adapted to the user’s mental scheme. This means that the first step would have to be the identification of a space’s conceptual scheme. In our case study, 32 Kansei words and 4 different locations, each with a different sensual experience, were selected. The 4 locations were all parks in the city of Tehran (Iran), each with a unique structure and artifacts such as a fountain, lighting, sculptures, and music. It should be noted that each of these parks has different combination and structure of environmental and artificial elements like: fountain, lightning, sculpture, music (sound) and so forth. The first one was park No.1, a park with natural environment, the selected space was a fountain with motion light and sculpture. The second park was park No.2, in which there are different styles of park construction: ways from different countries, the selected space was traditional Iranian architecture with a fountain and trees. The third one was park No.3, the park with modern environment and spaces, and included a fountain that moved according to music and lighting. The fourth park was park No.4, the park with combination of four elements: water, fire, earth, wind, the selected space was fountains squirting water from the ground up. 80 participant (55 males and 25 females) aged from 20-60 years participated in this experiment. Each person filled the questionnaire in the park he/she was in. Five-point semantic differential scale was considered to determine the relation between space details and adjectives (kansei words). Received data were analyzed by multivariate statistical technique (factor analysis using SPSS statics). Finally the results of this analysis are criteria as inspiration which can be used in future space designing for creating pleasant feeling in users.

Keywords: environmental design, differential semantics, Kansei engineering, subjective preferences, space

Procedia PDF Downloads 384

Authors: Kirsi Snellman, Johannes Gartner, , Katja Upadaya

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A transition towards a future where the economy serves society so that it evolves within the safe operating space of the planet calls for fundamental changes in the way managers think, feel and act, and make decisions that relate to social and environmental issues. Sustainable decision-making in organizations are often challenging tasks characterized by trade-offs between environmental, social and financial aspects, thus often bringing forth ethical concerns. Although there have been significant developments in incorporating uncertainty into environmental decision-making and measuring constructs and dimensions in ethical behavior in organizations, the majority of sustainable decision-making models are rationalist-based. Moreover, research in psychology indicates that one’s readiness to make a decision depends on the individual’s state of mind, the feasibility of the implied change, and the compatibility of strategies and tactics of implementation. Although very informative, most of this extant research is limited in the sense that it often directs attention towards the rational instead of the emotional. Hence, little is known about the role of emotions in sustainable decision making, especially in situations where decision-makers evaluate a variety of options and use their feelings as a source of information in tackling the uncertainty. To fill this lacuna, and to embrace the uncertainty and perceived risk involved in decisions that touch upon social and environmental aspects, it is important to add emotion to the evaluation when aiming to reach the one right and good ethical decision outcome. This analysis builds on recent findings in moral psychology that associate feelings and intuitions with ethical decisions and suggests that emotions can sensitize the manager to evaluate the rightness or wrongness of alternatives if ethical concerns are present in sustainable decision making. Capturing such sensitive evaluation as triggered by intuitions, we suggest that rational justification can be complemented by using emotions as a tool to tune in to what feels right in making sustainable decisions. This analysis integrates ethical decision-making theories with recent advancements in emotion theories. It determines the conditions under which emotions play a role in sustainability decisions by contributing to a personal equilibrium in which intuition and rationality are both activated and in accord. It complements the rationalist ethics view according to which nothing fogs the mind in decision making so thoroughly as emotion, and the concept of cheater’s high that links unethical behavior with positive affect. This analysis contributes to theory with a novel theoretical model that specifies when and why managers, who are more emotional, are, in fact, more likely to make ethical decisions than those managers who are more rational. It also proposes practical advice on how emotions can convert the manager’s preferences into choices that benefit both common good and one’s own good throughout the transition towards a more sustainable future.

Keywords: emotion, ethical decision making, intuition, sustainability

Procedia PDF Downloads 109

Authors: M. Cardenas-Garcia, P. P. Gonzalez-Perez

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Intercellular communication is a necessary condition for cellular functions and it allows a group of cells to survive as a population. Throughout this interaction, the cells work in a coordinated and collaborative way which facilitates their survival. In the case of cancerous cells, these take advantage of intercellular communication to preserve their malignancy, since through these physical unions they can send signs of malignancy. The Wnt/β-catenin signaling pathway plays an important role in the formation of intercellular communications, being also involved in a large number of cellular processes such as proliferation, differentiation, adhesion, cell survival, and cell death. The modeling and simulation of cellular signaling systems have found valuable support in a wide range of modeling approaches, which cover a wide spectrum ranging from mathematical models; e.g., ordinary differential equations, statistical methods, and numerical methods– to computational models; e.g., process algebra for modeling behavior and variation in molecular systems. Based on these models, different simulation tools have been developed from mathematical ones to computational ones. Regarding cellular and molecular processes in cancer, its study has also found a valuable support in different simulation tools that, covering a spectrum as mentioned above, have allowed the in silico experimentation of this phenomenon at the cellular and molecular level. In this work, we simulate and explore the complex interaction patterns of intercellular communication in cancer cells using the Cellulat bioinformatics tool, a computational simulation tool developed by us and motivated by two key elements: 1) a biochemically inspired model of self-organizing coordination in tuple spaces, and 2) the Gillespie’s algorithm, a stochastic simulation algorithm typically used to mimic systems of chemical/biochemical reactions in an efficient and accurate way. The main idea behind the Cellulat simulation tool is to provide an in silico experimentation environment that complements and guides in vitro experimentation in intra and intercellular signaling networks. Unlike most of the cell signaling simulation tools, such as E-Cell, BetaWB and Cell Illustrator which provides abstractions to model only intracellular behavior, Cellulat is appropriate for modeling both intracellular signaling and intercellular communication, providing the abstractions required to model –and as a result, simulate– the interaction mechanisms that involve two or more cells, that is essential in the scenario discussed in this work. During the development of this work we made evident the application of our computational simulation tool (Cellulat) for the modeling and simulation of intercellular communication between normal and cancerous cells, and in this way, propose key molecules that may prevent the arrival of malignant signals to the cells that surround the tumor cells. In this manner, we could identify the significant role that has the Wnt/β-catenin signaling pathway in cellular communication, and therefore, in the dissemination of cancer cells. We verified, using in silico experiments, how the inhibition of this signaling pathway prevents that the cells that surround a cancerous cell are transformed.

Keywords: cancer cells, in silico approach, intercellular communication, key molecules, modeling and simulation

Procedia PDF Downloads 230

Authors: A. Kavita Murugkar, B. Anurag Kashyap

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With the Rights for Persons with Disabilities Act (RPWD Act) 2016, the Indian government has made it mandatory for all establishments, including Heritage Sites, to be accessible for People with Disabilities. However, recent access audit surveys done under the Accessible India Campaign by Ministry of Culture indicate that there are very few accessibility measures provided in the Heritage sites for people with disabilities. Though there are some measures for the mobility impaired, surveys brought out that there are almost no provisions for people with vision impairment (PwVI) in heritage sites thus depriving them of a reasonable physical & intellectual access that facilitates an enjoyable experience and enriching interpretation of the Heritage Site. There is a growing need to develop multisensory interpretative tools that can help the PwVI in perceiving heritage sites in the absence of vision. The purpose of this research was to examine the usability of an audio-tactile model as a haptic and sound-based strategy for augmenting the perception and experience of PwVI in a heritage site. The first phase of the project was a multi-stage phenomenological experimental study with visually impaired users to investigate the design parameters for developing an audio-tactile model for PwVI. The findings from this phase included user preferences related to the physical design of the model such as the size, scale, materials, details, etc., and the information that it will carry such as braille, audio output, tactile text, etc. This was followed by the second phase in which a working prototype of an audio-tactile model is designed and developed for a heritage site based on the findings from the first phase of the study. A nationally listed heritage site from the author’s city was selected for making the model. The model was lastly tested by visually impaired users for final refinements and validation. The prototype developed empowers People with Vision Impairment to navigate independently in heritage sites. Such a model if installed in every heritage site, can serve as a technological guide for the Person with Vision Impairment, giving information of the architecture, details, planning & scale of the buildings, the entrances, location of important features, lifts, staircases, and available, accessible facilities. The model was constructed using 3D modeling and digital printing technology. Though designed for the Indian context, this assistive technology for the blind can be explored for wider applications across the globe. Such an accessible solution can change the otherwise “incomplete’’ perception of the disabled visitor, in this case, a visually impaired visitor and augment the quality of their experience in heritage sites.

Keywords: accessibility, architectural perception, audio tactile model , inclusive heritage, multi-sensory perception, visual impairment, visitor experience

Procedia PDF Downloads 83

Authors: Inbal Zuriely, Yonit Weiss, Hilla Zaharoni, Hadas Lewkowicz, Tatiana Vander, Tarif Bader

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early active movement, along with adjusting optimal nutrition, prevents aggravation of muscle degeneracy and functional decline. Eating is a basic activity of daily life, which reflects the patient's independence. When eating and feeding are experienced successfully, they lead to a sense of pleasure and satisfaction. However, when they are experienced as a difficulty, they might evoke feelings of helplessness and frustration. This stresses the essential process of gradual weaning off the enteral feeding tube. the work describes the collaboration of a dietitian, determining the nutritional needs of patients undergoing enteral tube weaning as part of the rehabilitation process, with the suited treatment of an occupational therapist. Occupational therapy intervention regarding eating capabilities focuses on improving the required motor and cognitive components, along with environmental adjustments and aids, imparting eating strategies and training to patients and their families. The project was conducted in the long-term, ventilated patients’ department at the Herzfeld Rehabilitation Geriatric Medical Center on patients undergoing enteral tube weaning with the staff’s assistance. Establishing continuous collaboration between the dietician and the occupational therapist, starting from the beginning of the feeding-tube weaning process: 1.The dietician updates the occupational therapist about the start of the process and the approved diet. 2.The occupational therapist performs cognitive, motor, and functional assessments and treatments regarding the patient’s eating capabilities and recommends the required adjustments for independent eating according to the FIM (Functional Independence Measure) scale. 3.The occupational therapist closely follows up on the patient’s degree of independence in eating and provides a repeated update to the dietician. 4.The dietician accordingly guides the ward staff on whether and how to feed the patient or allow independent eating. The project aimed to promote patients toward independent feeding, which leads to a sense of empowerment, enjoyment of the eating experience, and progress of functional ability, along with performing active movements that will motivate mobilization. From the beginning of 2022, 26 patients participated in the project. 79% of all patients who started the weaning process from tube feeding achieved different levels of independence in feeding (independence levels ranged from supervision (FIM-5) to complete independence (FIM-7). The integration of occupational therapy and dietary treatment is based on a patient-centered approach while considering the patient’s personal needs, preferences, and goals. This interdisciplinary partnership is essential for meeting the complex needs of prolonged mechanically ventilated patients and promotes independent functioning and quality of life.

Keywords: dietary, mechanical ventilation, occupational therapy, tube feeding weaning

Procedia PDF Downloads 52

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

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

Procedia PDF Downloads 13

Authors: Wafa Al Jabri

Abstract:

Background: In Middle Eastern Countries (MECs), there is a high prevalence of genetic blood disorders (GBDs), particularly sickle cell disease and thalassemia. The GBDs are considered a major public health concern that place a huge burden to individuals, families, communities, and health care systems. The high rates of consanguineous marriages, along with the unacceptable termination of at-risk pregnancy in MECs, reduce the possible solutions to control the high prevalence of GBDs. Since the early 1970s, most of MECs have started introducing premarital screening services (PSS) as a preventive measure to identify the asymptomatic carriers of GBDs and to provide genetic counseling to help couples plan for healthy families; yet, the success rate of PSS is very low. Purpose: This paper aims to highlight the factors that affect the success of PSS in MECs. Methods: An integrative review of articles located in CINAHL, PubMed, SCOPUS, and MedLine was carried out using the following terms: “premarital screening,” “success,” “effectiveness,” and “ genetic blood disorders”. Second, a hand search of the reference lists and Google searches were conducted to find studies that did not exist in the primary database searches. Only studies which are conducted in MECs and published after 2010 were included. Studies that were not published in English were excluded. Results: Eighteen articles were included in the review. The results showed that PSS in most of the MECs was successful in achieving its objective of identifying high-risk marriages; however, the service failed to meet its ultimate goal of reducing the prevalence of GBDs. Various factors seem to hinder the success of PSS, including poor public awareness, late timing of the screening, culture and social stigma, lack of prenatal diagnosis services and therapeutic abortion, emotional factors, religious beliefs, and lack of genetic counseling services. However, poor public awareness, late timing of the screening, religious misbeliefs, and the lack of adequate counseling services were the most common barriers identified. Conclusion and Implications: The review help in providing a framework for an effective preventive measure to reduce the prevalence of GBDs in MECS. This framework focuses primarily in overcoming the identified barriers by providing effective health education programs in collaboration with religious leaders, offering the screening test to young adults at an earlier stage, and tailoring the genetic counseling to consider people’s values, beliefs, and preferences.

Keywords: premarital screening, middle east, genetic blood disorders, factors

Procedia PDF Downloads 60

Authors: Min-Hsun Liao

Abstract:

Since the outbreak of war between Russia and Ukraine in February 2022, universities around the world have extended their helping hands to welcome Ukrainian students whose academic careers have been unexpectedly interrupted. Tunghai University (THU) in Taiwan and Mykolas Romeris University (MRU) in Lithuania are among the many other universities offering short- and long-term scholarships to host Ukrainian students in the midst of the war crisis. This mixed-methods study examines the cross-cultural adjustment processes of Ukrainian students in Taiwan. The research team at MRU will also conduct a parallel study with their Ukrainian students. Both institutions are committed to gaining insights into the adjustment processes of these students through cross-institutional collaboration. Studies show that while international students come from different cultural backgrounds, the difficulties they face while studying abroad are comparable and vary in intensity. These difficulties range from learning the language of the host country, adopting cultural customs, and adapting culinary preferences to the sociocultural shock of being separated from family and friends. These problems have been the subject of numerous studies. Study findings indicate that these challenges, if not properly addressed, can lead to significant stress, despair, and failure in academics or other endeavors for international students, not to mention those who have had to leave home involuntarily and settle into a completely new environment. Among these challenges, the language of the host country is foremost. The issue of international students' adjustment, particularly language acquisition, is critical to the psychological, academic, and sociocultural well-being of individuals. Both quantitative and qualitative data will be collected: 1) the International Student Cross-cultural Adaptation Survey (ISCAS) will be distributed to all Ukrainian students in both institutions; 2) one-on-one interviews will be conducted to gain a deeper understanding of their adaptations; and 3) t-tests or ANOVA will be calculated to determine significant differences between the languages used and the adaptation patterns of Ukrainian students. The significance of this study is consistent with three SDGs, namely quality education, peace/justice, and strong institutions and partnerships for the goals. The THU and MRU research teams believe that through partnership, both institutions can benefit exponentially from sharing the data, avoiding fixed interpretation, and sharing contextual insights, which will help improve the overall quality of education for international students and promote peace/justice through strong institutions. The impact of host country language proficiency on academic and sociocultural adjustments remains inconclusive. Therefore, the outcome of the study will shed new light on the relationship between language and various adjustments. In addition, the feedback from Ukrainian students will help other host countries better serve international students who must flee their home countries for an undisturbed education.

Keywords: international students, ukrainian students, cross-cultural adaptation, host country language, acculturation theory

Procedia PDF Downloads 50

Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

Procedia PDF Downloads 120

Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

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The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

Procedia PDF Downloads 25

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

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

Procedia PDF Downloads 18

Authors: Maria R. Mula-Molina, Juan A. Ferriz-Papi

Abstract:

Environmental concerns are increasingly obtaining higher priority in sustainability agenda of educational establishments. This is important not only for its environmental performance in its own right as an organization, but also to present a model for its students. On the other hand, universities play an important role on research and innovative solutions for measuring, analyzing and reducing environmental impacts for different activities. The assessment and decision-making process during the activity of educational establishments is linked to the application of robust indicators. In this way, the carbon footprint is a developing indicator for sustainability that helps understand the direct impact on climate change. But it is not easy to implement. There is a large amount of considering factors involved that increases its complexity, such as different uses at the same time (research, lecturing, administration), different users (students, staff) or different levels of activity (lecturing, exam or holidays periods). The aim of this research is to develop a simplified methodology for calculating and comparing carbon emissions per user at university campus considering two main aspects for carbon accountings: Building operations and transport. Different methodologies applied in other Spanish university campuses are analyzed and compared to obtain a final proposal to be developed in this type of establishments. First, building operation calculation considers the different uses and energy sources consumed. Second, for transport calculation, the different users and working hours are calculated separately, as well as their origin and traveling preferences. For every transport, a different conversion factor is used depending on carbon emissions produced. The final result is obtained as an average of carbon emissions produced per user. A case study is applied to the University of Alicante campus in San Vicente del Raspeig (Spain), where the carbon footprint is calculated. While the building operation consumptions are known per building and month, it does not happen with transport. Only one survey about the habit of transport for users was developed in 2009/2010, so no evolution of results can be shown in this case. Besides, building operations are not split per use, as building services are not monitored separately. These results are analyzed in depth considering all factors and limitations. Besides, they are compared to other estimations in other campuses. Finally, the application of the presented methodology is also studied. The recommendations concluded in this study try to enhance carbon emission monitoring and control. A Carbon Action Plan is then a primary solution to be developed. On the other hand, the application developed in the University of Alicante campus cannot only further enhance the methodology itself, but also render the adoption by other educational establishments more readily possible and yet with a considerable degree of flexibility to cater for their specific requirements.

Keywords: building operations, built environment, carbon footprint, climate change, transport

Procedia PDF Downloads 261

Authors: Jamil Lane, Jason Freeman

Abstract:

Background: The role of interpersonal relationships is vital predictors of adolescents’ eating habits, exercise activity, and health problems including obesity. The effect of interpersonal relationships (i.e. family, friends, and intimate partners) on individual health behaviors and development have gained considerable attention during the past 10 years. Teenagers eating habits and exercise activities are established through a dynamic course involving internal and external factors such as food preferences, body weight perception, and parental and peer influence. When conceptualizing one’s interpersonal relationships, it is important to understand that how one relates to others is shaped by their culture. East-Asian culture has been characterized as collectivistic, which describes the significant role intergroup relationships play in their construction of the self. Cultures found in North America, on the other hand, can be characterized as individualistic, meaning that these cultures encourage individuals to prioritize their interest over the needs and want of their compatriots. Individuals from collectivistic cultures typically have stronger boundaries between in-group and out-group membership, whereas those from individualistic cultures see themselves as distinct and separate from strangers as well as family or friends. Objective: The purpose of this study is to examine the effect of collectivism and individualism on interpersonal relationships that shapes eating patterns and physical activity among Asian-American and European-American adolescents. Design/Methods: Analyses were based on data from the National Longitudinal Study of Adolescent Health, a nationally representative sample of adolescents in the United States who were surveyed from 1994 through 2008. This data will be used to examine interpersonal relationship factors that shape dietary intake and physical activity patterns within the Asian-American and European-American population in the United States. Factors relating to relationship strength, eating, and exercise behaviors were reported by participants in this first wave of data collection (1995). We plan to analyze our data using intragroup comparisons among those who identified as 'Asian-American' (n = 270) and 'White or European American' (n = 4,294) among the domains of positivity of peer influence and level of physical activity / healthy eating. Further, intergroup comparisons of these relationships will be made to extricate how the role positive peer influence in maintaining healthy eating and exercise habits differs with cultural variation. Results: We hypothesize that East-Asian participants with a higher degree of positivity in their peer and family relationships will experience a significantly greater rise in healthy eating and exercise behaviors than European-American participants with similar degrees of relationship positivity.

Keywords: interpersonal relationships, eating patterns, physical activity, adolescent health

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Authors: Francesca Marsili

Abstract:

The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

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Authors: Olivia Garcia, Sandra Tullio-Pow

Abstract:

The purpose of this study was to understand what design attributes make the most ideal (wearable and memorable) national soccer jersey. The research probed Canadian soccer enthusiasts to better understand their jersey-purchasing rationale. The research questions framing this study were: how do consumers feel about their jerseys? How do these feelings influence their choices? There has been limited research on soccer jerseys from a material culture perspective, and it is not inclusive of national soccer jerseys. The results of this study may be used for product developers and advertisers who are looking to better understand the consumer base for national soccer jersey design. A mixed methods approach informed the research. To begin, a content analysis of all the home jerseys from the 2018 World Cup was done. Information such as size range, main colour, fibre content, brand, collar details, availability, sleeve length, place of manufacturing, pattern, price, fabric as per company, neckline, availability on company website, jersey inspiration, and badge/crest details were noted. Following the content analysis, wardrobe interviews were conducted with six consumers/fans. Participants brought two or more jerseys to the interviews, where the jerseys acted as clothing probes to recount information. Interview questions were semi-structured and focused on the participants’ relationship with the sport, their personal background, who they cheered for, why they bought the jerseys, and fit preferences. The goal of the inquiry was to pull out information on how participants feel about their jerseys and why. Finally, an interview with an industry professional was done. This interview was semi-structured, focusing on basic questions regarding sportswear design, sales, the popularity of soccer, and the manufacturing and marketing process. The findings proved that national soccer jerseys are an integral part of material culture. Women liked more fitted jerseys, and men liked more comfortable jerseys. Jerseys should be made with a cooling, comfortable fabric and should always prevent peeling. The symbols on jerseys are there to convey a team’s history and are most typically placed on the left chest. Jerseys should always represent the flag and/or the country’s colours and should use designs that are both fashionable and innovative. Jersey design should always consider the opinions of the consumers to help influence the design process. Jerseys should always use concepts surrounding culture, as consumers feel connected to the jerseys that represent the culture and/or family they have grown up with. Jerseys should use a team’s history, as well as the nostalgia associated with the team, as consumers prefer jerseys that reflect important moments in soccer. Jerseys must also sit at a reasonable price point for consumers, with an experience to go along with the jersey purchase. In conclusion, national soccer jerseys are considered sites of attachment and memories and play an integral part in the study of material culture.

Keywords: Design, Fashion, Material Culture, Sport

Procedia PDF Downloads 76