Search results for: artificial intelligent

Authors: Helena Bolini, Erick Esmerino, Adriano Cruz, Juliana Paixao

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The currently concern for health has increased demand for low-calorie ingredients and functional foods as probiotics. Understand the reasons that infer on food choice, besides a challenging task, it is important step for development and/or reformulation of existing food products. The use of appropriate multivariate statistical techniques, such as External Preference Map (PrefMap), associated with regression by Partial Least Squares (PLS) can help in determining those factors. Thus, this study aimed to determine, through PLS regression analysis, the sensory attributes considered drivers of liking in probiotic petit suisse cheeses, strawberry flavor, sweetened with different sweeteners. Five samples in same equivalent sweetness: PROB1 (Sucralose 0.0243%), PROB2 (Stevia 0.1520%), PROB3 (Aspartame 0.0877%), PROB4 (Neotame 0.0025%) and PROB5 (Sucrose 15.2%) determined by just-about-right and magnitude estimation methods, and three commercial samples COM1, COM2 and COM3, were studied. Analysis was done over data coming from QDA, performed by 12 expert (highly trained assessors) on 20 descriptor terms, correlated with data from assessment of overall liking in acceptance test, carried out by 125 consumers, on all samples. Sequentially, results were submitted to PLS regression using XLSTAT software from Byossistemes. As shown in results, it was possible determine, that three sensory descriptor terms might be considered drivers of liking of probiotic petit suisse cheese samples added with sweeteners (p<0.05). The milk flavor was noticed as a sensory characteristic with positive impact on acceptance, while descriptors bitter taste and sweet aftertaste were perceived as descriptor terms with negative impact on acceptance of petit suisse probiotic cheeses. It was possible conclude that PLS regression analysis is a practical and useful tool in determining drivers of liking of probiotic petit suisse cheeses sweetened with artificial and natural sweeteners, allowing food industry to understand and improve their formulations maximizing the acceptability of their products.

Keywords: acceptance, consumer, quantitative descriptive analysis, sweetener

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Authors: Mirzet SeHo, Alaa Alaabed, Mansur Masih

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In theory, risk-sharing-based financing (RSF) is considered a corner stone of Islamic finance. It is argued to render Islamic banks more resilient to shocks. In practice, however, this feature of Islamic financial products is almost negligible. Instead, debt-based instruments, with conventional like features, have overwhelmed the nascent industry. In addition, the framework of present-day economic, regulatory and financial reality inevitably exposes Islamic banks in dual banking systems to problems of conventional banks. This includes, but is not limited to, interest rate risk. Empirical evidence has, thus far, confirmed such exposures, despite Islamic banks’ interest-free operations. This study applies system GMM in modeling the determinants of RSF, and finds that RSF is insensitive to changes in interest rates. Hence, our results provide support to the “stability” view of risk-sharing-based financing. This suggests RSF as the way forward for risk management at Islamic banks, in the absence of widely acceptable Shariah compliant hedging instruments. Further support to the stability view is given by evidence of counter-cyclicality. Unlike debt-based lending that inflates artificial asset bubbles through credit expansion during the upswing of business cycles, RSF is negatively related to GDP growth. Our results also imply a significantly strong relationship between risk-sharing deposits and RSF. However, the pass-through of these deposits to RSF is economically low. Only about 40% of risk-sharing deposits are channeled to risk-sharing financing. This raises questions on the validity of the industry’s claim that depositors accustomed to conventional banking shun away from risk sharing and signals potential for better balance sheet management at Islamic banks. Overall, our findings suggest that, on the one hand, Islamic banks can gain ‘independence’ from conventional banks and interest rates through risk-sharing products, the potential for which is enormous. On the other hand, RSF could enable policy makers to improve systemic stability and restrain excessive credit expansion through its countercyclical features.

Keywords: Islamic banks, risk-sharing, financing, interest rate, dynamic system GMM

Procedia PDF Downloads 294

Authors: Keroles Akram Saed Ghatas

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The near future will bring significant changes in modern organizations and management due to the growing role of intangible assets and knowledge workers. The area of copyright, intellectual property, digital (intangible) assets and media redistribution appears to be one of the greatest challenges facing business and society in general and management sciences and organizations in particular. The proposed article examines the views and perceptions of fairness in digital media sharing among Harvard Law School's LL.M.s. Students, based on 50 qualitative interviews and 100 surveys. The researcher took an ethnographic approach to her research and entered the Harvard LL.M. in 2016. at, a Face book group that allows people to connect naturally and attend in-person and private events more easily. After listening to numerous students, the researcher conducted a quantitative survey among 100 respondents to assess respondents' perceptions of fairness in digital file sharing in various contexts (based on media price, its availability, regional licenses, copyright holder status, etc.). to understand better . .). Based on the survey results, the researcher conducted long-term, open-ended and loosely structured ethnographic interviews (50 interviews) to further deepen the understanding of the results. The most important finding of the study is that Harvard lawyers generally support digital piracy in certain contexts, despite having the best possible legal and professional knowledge. Interestingly, they are also more accepting of working for the government than the private sector. The results of this study provide a better understanding of how “fairness” is perceived by the younger generation of lawyers and pave the way for a more rational application of licensing laws.

Keywords: cognitive impairments, communication disorders, death penalty, executive function communication disorders, cognitive disorders, capital murder, executive function death penalty, egyptian law absence, justice, political cases piracy, digital sharing, perception of fairness, legal profession

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Authors: Jessica BrodeFrank, Beka Bryer, Lacey Wilson, Sierra Van Ryck deGroot

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Museums are enjoying quite the moment in pop culture. From discussions of labor in Bob’s Burger to introducing cultural repatriation in The Black Panther, discussions of various museum issues are making their way to popular media. “Talking Back to Hollywood” analyzes the impact museums have on movies and television. The paper will highlight a series of cultural cameos and discuss what each reveals about critical themes in museums: repatriation, labor, obfuscated histories, institutional legacies, artificial intelligence, and holograms. Using a mixed methods approach to include surveys, descriptive research, thematic analysis, and context analysis, the authors of this paper will explore how we, as the museum staff, might begin to cite museums and movies together as texts. Drawing from their experience working in museums and public history, this contingent of mid-career professionals will highlight the impact museums have had on movies and television and the didactic lessons these portrayals can provide back to cultural heritage professionals. From tackling critical themes in museums such as repatriation, labor conditions/inequities, obfuscated histories, curatorial choice and control, institutional legacies, and more, this paper is grounded in the cultural zeitgeist of the 2000s and the message these media portrayals send to the public and the cultural heritage sector. In particular, the paper will examine how portrayals of AI, holograms, and more technology can be used as entry points for necessary discussions with the public on mistrust, misinformation, and emerging technologies. This paper will not only expose the legacy and cultural understanding of the museum field within popular culture but also will discuss actionable ways that public historians can use these portrayals as an entry point for discussions with the public, citing literature reviews and quantitative and qualitative analysis of survey results. As Hollywood is talking about museums, museums can use that to better connect to the audiences who feel comfortable at the cinema but are excluded from the museum.

Keywords: museums, public memory, representation, popular culture

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Authors: Vidar Hepsø

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The energy and oil companies on the Norwegian Continental shelf come from a situation where each asset control and manage their energy supply (island mode) and move towards a situation where the assets need to collaborate and coordinate energy use with others due to increased cost and scarcity of electric energy sharing the energy that is provided. Currently, several areas are electrified either with an onshore grid cable or are receiving intermittent energy from offshore wind-parks. While the onshore grid in Norway is well regulated, the offshore grid is still in the making, with several oil and gas electrification projects and offshore wind development just started. The paper will describe the shift in the mindset that comes with operating this new offshore grid. This transition process heralds an increase in collaboration across boundaries and integration of energy management across companies, businesses, technical disciplines, and engagement with stakeholders in the larger society. This transition will be described as a function of the new challenges with increased complexity of the energy mix (wind, oil/gas, hydrogen and others) coupled with increased technical and organization complexity in energy management. Organizational complexity denotes an increasing integration across boundaries, whether these boundaries are company, vendors, professional disciplines, regulatory regimes/bodies, businesses, and across numerous societal stakeholders. New practices must be developed, made legitimate and institutionalized across these boundaries. Only parts of this complexity can be mitigated technically, e.g.: by use of batteries, mixing energy systems and simulation/ forecasting tools. Many challenges must be mitigated with legitimated societal and institutionalized governance practices on many levels. Offshore electrification supports Norway’s 2030 climate targets but is also controversial since it is exploiting the larger society’s energy resources. This means that new systems and practices must also be transparent, not only for the industry and the authorities, but must also be acceptable and just for the larger society. The paper report from ongoing work in Norway, participant observation and interviews in projects and people working with offshore grid development in Norway. One case presented is the development of an offshore floating windfarm connected to two offshore installations and the second case is an offshore grid development initiative providing six installations electric energy via an onshore cable. The development of the offshore grid is analyzed using a capability platform framework, that describes the technical, competence, work process and governance capabilities that are under development in Norway. A capability platform is a ‘stack’ with the following layers: intelligent infrastructure, information and collaboration, knowledge sharing & analytics and finally business operations. The need for better collaboration and energy forecasting tools/capabilities in this stack will be given a special attention in the two use cases that are presented.

Keywords: capability platform, electrification, carbon footprint, control rooms, energy forecsting, operational model

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Authors: Mao Huasong, Tang Siqi, Cheng Yu

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The cognition and practice of Chinese landscapes have distinct uniqueness. The intergenerational inheritance of urban and rural landscapes is a common objective fact which has created a unique type of heritage in China - scenic heritage. The current generalization of the concept of scenic heritage has affected the lack of innovation in corresponding protection practices. Therefore, clarifying the concepts and connotations of scenery and scenic heritage, clarifying the protection objects of scenic heritage and the methods and approaches in intergenerational inheritance can provide theoretical support for the practice of Chinese scenic heritage and contribute Chinese wisdom to the transformation of world heritage sites. Taking ancient Shaoxing, which has a long time span and rich descriptions of scenic types and quantities, as the research object and using local chronicles as the basic research material, based on text analysis, word frequency analysis, case statistics, and historical, geographical spatial annotation methods, this study traces back to ancient scenic practices and conducts in-depth descriptions in both text and space. it have constructed a scenic heritage identification method based on the basic connotation characteristics and morphological representation characteristics of natural and cultural correlations, combined with the intergenerational and representative characteristics of scenic heritage; Summarized the bidirectional integration of "scenic spots" and "form scenic spots", "outstanding people" and "local spirits" in the formation process of scenic heritage; In inheritance, guided by Confucian values of education; In communication, the cultural interpretation constructed by scenery and the way of landscape life are used to strengthen the intergenerational inheritance of natural, artificial material elements, and intangible spirits. As a unique type of heritage in China, scenic heritage should improve its standards, values, and connotations in current protection practices and actively absorb historical experience.

Keywords: scenic heritage, heritage protection, cultural landscape, shaoxing, chinese landscape

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

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Authors: Apichaya Aneksampant, Xuefei Tu, Masami Fukushima, Mitsuo Yamamoto

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The restoration of seaweed beds recovery has been developed using a fertilization technique for supplying dissolved iron to barren coastal areas. The fertilizer is composed of iron oxides as a source of iron and compost as humic substance (HS) source, which can serve as chelator of iron to stabilize the dissolved species under oxic seawater condition. However, elution mechanisms of iron from iron oxide surfaces have not sufficiently elucidated. In particular, roles of microbial activities in the elution of iron from the fertilizer are not sufficiently understood. In the present study, a fertilizer (iron oxide/compost = 1/1, v/v) was incubated in a water tank at Mashike coast, Hokkaido Japan. Microorganisms in the 6-month fertilizer were isolated and identified as Exiguobacterium oxidotolerans sp. (T-2-2). The identified bacteria were inoculated to perform iron elution test in a postgate B medium, prepared in artificial seawater. Hematite was used as a model iron oxide and anthraquinone-2,7-disolfonate (AQDS) as a model for HSs. The elution test performed in presence and absence of bacteria inoculation. ICP-AES was used to analyze total iron and a colorimetric technique using ferrozine employed for the determination of ferrous ion. During the incubation period, sample contained hematite and T-2-2 in both presence and absence of AQDS continuously showed the iron elution and reached at the highest concentration after 9 days of incubation and then slightly decrease to stabilize within 20 days. Comparison to the sample without T-2-2, trace amount of iron was observed, suggesting that iron elution to seawater can be attributed to bacterial activities. The levels of total organic carbon (TOC) in the culture solution with hematite decreased. This may be to the adsorption of organic compound, AQDS, to hematite surfaces. The decrease in UV-vis absorption of AQDS in the culture solution also support the results of TOC that AQDS was adsorbed to hematite surfaces. AQDS can enhance the iron elution, while the adsorption of organic matter suppresses the iron elution from hematite.

Keywords: anthraquinone-2, 7-disolfonate, barren ground, E.oxidotolerans sp., hematite, humic substances, iron elution

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Authors: Nicolas M. Beleski, Gustavo A. G. Lugo

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Robotic agents are taking more and increasingly important roles in society. In order to make these robots and agents more autonomous and efficient, their systems have grown to be considerably complex and convoluted. This growth in complexity has led recent researchers to investigate forms to explain the AI behavior behind these systems in search for more trustworthy interactions. A current problem in explainable AI is the inner workings with the logic inference process and how to conduct a sensibility analysis of the process of valuation and alteration of beliefs. In a social HRI (human-robot interaction) setup, theory of mind is crucial to ease the intentionality gap and to achieve that we should be able to infer over observed human behaviors, such as cases of cognitive dissonance. One specific case inspired in human cognition is the role emotions play on our belief system and the effects caused when observed behavior does not match the expected outcome. In such scenarios emotions can make a person wrongly assume the antecedent P for an observed consequent Q, and as a result, incorrectly assert that P is true. This form of cognitive dissonance where an unproven cause is taken as truth induces changes in the belief base which can directly affect future decisions and actions. If we aim to be inspired by human thoughts in order to apply levels of theory of mind to these artificial agents, we must find the conditions to replicate these observable cognitive mechanisms. To achieve this, a computational architecture is proposed to model the modulation effect emotions have on the belief system and how it affects logic inference process and consequently the decision making of an agent. To validate the model, an experiment based on the prisoner's dilemma is currently under development. The hypothesis to be tested involves two main points: how emotions, modeled as internal argument strength modulators, can alter inference outcomes, and how can explainable outcomes be produced under specific forms of cognitive dissonance.

Keywords: cognitive architecture, cognitive dissonance, explainable ai, sensitivity analysis, theory of mind

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Authors: Magdalena Wilk-Kozubek, Magdalena Rowińska, Krzysztof Rola, Joanna Cybińska

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Leuco dye-based thermochromic systems are classified as intelligent materials because they exhibit thermally induced color changes. Thanks to this feature, they are mainly used as temperature sensors in many industrial sectors. For example, placing a thermochromic material on a chemical reactor may warn about exceeding the maximum permitted temperature for a chemical process. Usually two components, a color former and a developer are needed to produce a system with irreversible color change. The color former is an electron donating (proton accepting) compound such as fluoran leuco dye. The developer is an electron accepting (proton donating) compound such as organic carboxylic acid. When the developer melts, the color former - developer complex is created and the termochromic system becomes colored. Typically, the melting point of the applied developer determines the temperature at which the color change occurs. When the lactone ring of the color former is closed, then the dye is in its colorless state. The ring opening, induced by the addition of a proton, causes the dye to turn into its colored state. Since the color former and the developer are often solid, they can be incorporated into polymer films to facilitate their practical use in industry. The objective of this research was to fabricate a leuco dye-based termochromic system that will irreversibly change color after reaching the temperature of 100°C. For this purpose, benzofluoran leuco dye (as color former) and phenoxyacetic acid (as developer with a melting point of 100°C) were introduced into the polymer films during the drop casting process. The film preparation process was optimized in order to obtain thin films with appropriate properties such as transparency, flexibility and homogeneity. Among the optimized factors were the concentration of benzofluoran leuco dye and phenoxyacetic acid, the type, average molecular weight and concentration of the polymer, and the type and concentration of the surfactant. The selected films, containing benzofluoran leuco dye and phenoxyacetic acid, were combined by mild heat treatment. Structural characterization of single and combined films was carried out by FTIR spectroscopy, morphological analysis was performed by optical microscopy and SEM, phase transitions were examined by DSC, color changes were investigated by digital photography and UV-Vis spectroscopy, while emission changes were studied by photoluminescence spectroscopy. The resulting thermochromic system is colorless at room temperature, but after reaching 100°C the developer melts and it turns irreversibly pink. Therefore, it could be used as an additional sensor to warn against boiling of water in power plants using water cooling. Currently used electronic temperature indicators are prone to faults and unwanted third-party actions. The sensor constructed in this work is transparent, thanks to which it can be unnoticed by an outsider and constitute a reliable reference for the person responsible for the apparatus.

Keywords: color developer, leuco dye, thin film, thermochromism

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Raymond Chi Fai Si Tou, Jacey Ja Young Choe, Amy Siu Ian So

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Smart hotels can be defined as the hotel which has an intelligent system, through digitalization and networking which achieve hotel management and service information. In addition, smart hotels include high-end designs that integrate information and communication technology with hotel management fulfilling the guests’ needs and improving the quality, efficiency and satisfaction of hotel management. The purpose of this study is to identify appropriate factors that may influence guests’ satisfaction and intention to revisit Smart Hotels based on service quality measurement of lodging quality index and extended UTAUT theory. Unified Theory of Acceptance and Use of Technology (UTAUT) is adopted as a framework to explain technology acceptance and use. Since smart hotels are technology-based infrastructure hotels, UTATU theory could be as the theoretical background to examine the guests’ acceptance and use after staying in smart hotels. The UTAUT identifies four key drivers of the adoption of information systems: performance expectancy, effort expectancy, social influence, and facilitating conditions. The extended UTAUT modifies the definitions of the seven constructs for consideration; the four previously cited constructs of the UTAUT model together with three new additional constructs, which including hedonic motivation, price value and habit. Thus, the seven constructs from the extended UTAUT theory could be adopted to understand their intention to revisit smart hotels. The service quality model will also be adopted and integrated into the framework to understand the guests’ intention of smart hotels. There are rare studies to examine the service quality on guests’ satisfaction and intention to revisit in smart hotels. In this study, Lodging Quality Index (LQI) will be adopted to measure the service quality in smart hotels. Using integrated UTAUT theory and service quality model because technological applications and services require using more than one model to understand the complicated situation for customers’ acceptance of new technology. Moreover, an integrated model could provide more perspective insights to explain the relationships of the constructs that could not be obtained from only one model. For this research, ten in-depth interviews are planned to recruit this study. In order to confirm the applicability of the proposed framework and gain an overview of the guest experience of smart hotels from the hospitality industry, in-depth interviews with the hotel guests and industry practitioners will be accomplished. In terms of the theoretical contribution, it predicts that the integrated models from the UTAUT theory and the service quality will provide new insights to understand factors that influence the guests’ satisfaction and intention to revisit smart hotels. After this study identifies influential factors, smart hotel practitioners could understand which factors may significantly influence smart hotel guests’ satisfaction and intention to revisit. In addition, smart hotel practitioners could also provide outstanding guests experience by improving their service quality based on the identified dimensions from the service quality measurement. Thus, it will be beneficial to the sustainability of the smart hotels business.

Keywords: intention to revisit, guest satisfaction, qualitative interviews, smart hotels

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Authors: Maria A. Castillo H., Andrés R. Leandro C.

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During the last decades, agricultural productivity in Latin America has increased with precision agriculture and more efficient agricultural technologies. The use of automated systems, satellite images, geographic information systems, and tools for data analysis, and artificial intelligence have contributed to making more effective strategic decisions. Twenty years ago, the state of Mérida, located in the Venezuelan Andes, reported the largest area covered by greenhouses in the country, where certified seeds of potatoes, vegetables, ornamentals, and flowers were produced for export and consumption in the central region of the country. In recent years, it is estimated that production under greenhouses has changed, and the area covered has decreased due to different factors, but there are few historical statistical data in sufficient quantity and quality to support this estimate or to be used for analysis and decision making. The objective of this study is to compare data collected about geoposition, use, and covered areas of the greenhouses in 2007 to data available in 2021, as support for the analysis of the current situation of horticultural production in the main municipalities of the state of Mérida. The document presents the development of the work in the diagnosis and integration of geographic coordinates in GIS and data analysis phases. As a result, an evaluation of the process is made, a dashboard is presented with the most relevant data along with the geographical coordinates integrated into GIS, and an analysis of the obtained information is made. Finally, some recommendations for actions are added, and works that expand the information obtained and its geographical traceability over time are proposed. This study contributes to granting greater certainty in the supporting data for the evaluation of social, environmental, and economic sustainability indicators and to make better decisions according to the sustainable development goals in the area under review. At the same time, the methodology provides improvements to the agricultural data collection process that can be extended to other study areas and crops.

Keywords: greenhouses, geographic information system, protected agriculture, data analysis, Venezuela

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Authors: H. Aljabiry, L. Bailey, S. Young

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Qatar is a desert with an average temperature 37⁰C, reaching over 40⁰C during summer. Precipitation is uncommon and mostly in winter. Qatar depends on desalination for drinking water and on groundwater and recycled water for irrigation. Water consumption and network leakage per capita in Qatar are amongst the highest in the world; re-use of treated wastewater is extremely limited with only 14% of treated wastewater being used for irrigation. This has led to the country disposing of unwanted water from various sources in lagoons situated around the country, causing concern over the possibility of environmental pollution. Accordingly, our hypothesis underpinning this research is that the quality and quantity of water in lagoons is having an impact on the groundwater reservoirs in Qatar. Lagoons (n = 14) and wells (n = 55) were sampled for both summer and winter in 2018 (summer and winter). Water, adjoining soil and plant samples were analysed for multiple elements by Inductively Coupled Plasma Mass Spectrometry. Organic and inorganic carbon were measured (CN analyser) and the major anions were determined by ion chromatography. Salinization in both the lagoon and the wells was seen with good correlations between Cl⁻, Na⁺, Li, SO₄, S, Sr, Ca, Ti (p-value < 0.05). Association of heavy metals was observed of Ni, Cu, Ag, and V, Cr, Mo, Cd which is due to contamination from anthropological activities such as wastewater disposal or spread of contaminated dust. However, looking at each elements none of them exceeds the Qatari regulation. Moreover, gypsum saturation in the system was observed in both the lagoon and wells water samples. Lagoons and the water of the well are found to be of a saline type as well as Ca²⁺, Cl⁻, SO₄²⁻ type evidencing both gypsum dissolution and salinization in the system. Moreover, Maps produced by Inverse distance weighting showed an increasing level of Nitrate in the groundwater in winter, and decrease chloride and sulphate level, indicating recharge effect after winter rain events. While E. coli and faecal bacteria were found in most of the lagoons, biological analysis for wells needs to be conducted to understand the biological contamination from lagoon water infiltration. As a conclusion, while both the lagoon and the well showed the same results, more sampling is needed to understand the impact of the lagoons on the groundwater.

Keywords: groundwater quality, lagoon, treated wastewater, water management, wastewater treatment, wetlands

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Authors: Kristine Nore, Alexander Severnisen, Petter Arnestad, Dimitris Kraniotis, Roy Rossebø

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Natural materials like wood, absorb and release moisture. Thus wood can buffer indoor climate. When used wisely, this buffer potential can be used to counteract the outer climate influence on the building. The mass of moisture used in the buffer is defined as the potential hygrothermal mass, which can be an energy storage in a building. This works like a natural heat pump, where the moisture is active in damping the diurnal changes. In Norway, the ability of wood as a material used for climate buffering is tested in several buildings with the extensive use of wood, including supermarkets. This paper defines the potential of hygrothermal mass in a supermarket building. This includes the chosen ventilation strategy, and how the climate impact of the building is reduced. The building is located above the arctic circle, 50m from the coastline, in Valnesfjord. It was built in 2015, has a shopping area, including toilet and entrance, of 975 m². The climate of the area is polar according to the Köppen classification, but the supermarket still needs cooling on hot summer days. In order to contribute to the total energy balance, wood needs dynamic influence to activate its hygrothermal mass. Drying and moistening of the wood are energy intensive, and this energy potential can be exploited. Examples are to use solar heat for drying instead of heating the indoor air, and raw air with high enthalpy that allow dry wooden surfaces to absorb moisture and release latent heat. Weather forecasts are used to define the need for future cooling or heating. Thus, the potential energy buffering of the wood can be optimized with intelligent ventilation control. The ventilation control in Valnesfjord includes the weather forecast and historical data. That is a five-day forecast and a two-day history. This is to prevent adjustments to smaller weather changes. The ventilation control has three zones. During summer, the moisture is retained to dampen for solar radiation through drying. In the winter time, moist air let into the shopping area to contribute to the heating. When letting the temperature down during the night, the moisture absorbed in the wood slow down the cooling. The ventilation system is shut down during closing hours of the supermarket in this period. During the autumn and spring, a regime of either storing the moisture or drying out to according to the weather prognoses is defined. To ensure indoor climate quality, measurements of CO₂ and VOC overrule the low energy control if needed. Verified simulations of the Valnesfjord building will build a basic model for investigating wood as a climate regulating material also in other climates. Future knowledge on hygrothermal mass potential in materials is promising. When including the time-dependent buffer capacity of materials, building operators can achieve optimal efficiency of their ventilation systems. The use of wood as a climate regulating material, through its potential hygrothermal mass and connected to weather prognoses, may provide up to 25% energy savings related to heating, cooling, and ventilation of a building.

Keywords: climate buffer, energy, hygrothermal mass, ventilation, wood, weather forecast

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Authors: Fatih Frank Alparslan

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The aviation industry is at a crucial turning point due to modern technologies, environmental concerns, and changing ways of transporting people and goods globally. The paper examines these challenges and opportunities comprehensively. It emphasizes the role of innovative management and advanced technology in shaping the future of air travel. This study begins with an overview of the current state of the aviation industry, identifying key areas where innovation and technology could be highly beneficial. It explores the latest advancements in airplane design, propulsion, and materials. These technological advancements are shown to enhance aircraft performance and environmental sustainability. The paper also discusses the use of artificial intelligence and machine learning in improving air traffic control, enhancing safety, and making flight operations more efficient. The management of these technologies is critically important. Therefore, the research delves into necessary changes in organization, culture, and operations to support innovation. It proposes a management approach that aligns with these modern technologies, underlining the importance of forward-thinking leaders who collaborate across disciplines and embrace innovative ideas. The paper addresses challenges in adopting these innovations, such as regulatory barriers, the need for industry-wide standards, and the impact of technological changes on jobs and society. It recommends that governments, aviation businesses, and educational institutions collaborate to address these challenges effectively, paving the way for a more innovative and eco-friendly aviation industry. In conclusion, the paper argues that the future of aviation relies on integrating new management practices with innovative technologies. It urges a collective effort to push beyond current capabilities, envisioning an aviation industry that is safer, more efficient, and environmentally responsible. By adopting a broad approach, this research contributes to the ongoing discussion about resolving the complex issues facing today's aviation sector, offering insights and guidance to prepare for future advancements.

Keywords: aviation innovation, technology integration, environmental sustainability, management strategies, multidisciplinary approach

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Authors: M. Y. Abubakar, Ipinjolu J. K., Yuzine B. Esa, Magawata I., Hassan W. A., Turaki A. A.

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Catfish (Heterobranchus spp.) is a major freshwater fish that are widely distributed in Nigeria waters and are gaining rapid aquaculture expansion. However, indiscriminate artificial crossbreeding of the species with others poses a threat to their biodiversity. There is a paucity of information about the genetic variability, hence this insight on the genetic variability is badly needed, not only for the species conservation but for aquaculture expansion. In this study, we tested the level of Genetic diversity, population differentiation and phylogenetic relationship analysis on 35 individuals of two populations of Heterobranchus bidorsalis and 29 individuals of three populations of Heterobranchus longifilis using the mitochondrial cytochrome c oxidase subunit I (mtDNA COI) gene sequence. Nucleotide sequences of 650 bp fragment of the COI gene of the two species were compared. In the whole 4 and 5 haplotypes were distinguished in the populations of H. bidorsalis & H. longifilis with accession numbers (MG334168 - MG334171 & MG334172 to MG334176) respectively. Haplotypes diversity indices revealed a range of 0.59 ± 0.08 to 0.57 ± 0.09 in H. bidorsalis and 0.000 to 0.001051 ± 0.000945 in H. longifilis population, respectively. Analysis of molecular variance (AMOVA) revealed no significant variation among H. bidorsalis population of the Niger & Benue Rivers, detected significant genetic variation was between the Rivers of Niger, Kaduna and Benue population of H. longifilis. Two main clades were recovered, showing a clear separation between H. bidorsalis and H. longifilis in the phylogenetic tree. The mtDNA COI genes studied revealed high gene flow between populations with no distinct genetic differentiation between the populations as measured by the fixation index (FST) statistic. However, a proportion of population-specific haplotypes was observed in the two species studied, suggesting a substantial degree of genetic distinctiveness for each of the population investigated. These findings present the description of the species character and accessions of the fish’s genetic resources, through gene sequence submitted in Genetic database. The data will help to protect their valuable wild resource and contribute to their recovery and selective breeding in Nigeria.

Keywords: AMOVA, genetic diversity, Heterobranchus spp., mtDNA COI, phylogenetic tree

Procedia PDF Downloads 117

Authors: Joseph Falzon, Margaret Nelson

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Background: Regeneration and re-use of abandoned historic buildings present a continuous challenge for policy makers and stakeholders in the tourism and leisure industry. Obsolete historic buildings provide great potential for tourism and leisure accommodation, presenting unique heritage experiences to travellers and host communities. Contemporary demands in the hospitality industry continuously require higher standards, some of which are in conflict with heritage conservation principles. Objective: The aim of this research paper is to critically discuss regeneration policies with stakeholders of the tourism and leisure industry and to examine current practices in policy development and the resultant impact of policies on the Maltese tourism and leisure industry. Research Design: Six semi-structured interviews with stakeholders involved in the tourism and leisure industry participated in the research. A number of measures were taken to reduce bias and thus improve trustworthiness. Clear statements of the purpose of the research study were provided at the start of each interview to reduce expectancy bias. The interviews were semi-structured to minimise interviewer bias. Interviewees were allowed to expand and elaborate as necessary, with only necessary probing questions, to allow free expression of opinion and practices. Interview guide was submitted to participants at least two weeks before the interview to allow participants to prepare for the interview and prevent recall bias during the interview as much as possible. Interview questions and probes contained both positive and negative aspects to prevent interviewer bias. Policy documents were available during the interview to prevent recall bias. Interview recordings were transcribed ‘intelligent’ verbatim. Analysis was carried out using thematic analysis with the coding frame developed independently by two researchers. All phases of the study were governed by research ethics. Findings: Findings were grouped in main themes: financing of regeneration, governance, legislation and policies. Other key issues included value of historic buildings and approaches for regeneration. Whist regeneration of historic buildings was noted, participants discussed a number of barriers that hindered regeneration. Stakeholders identified gaps in policies and gaps at policy implementation stages. European Union funding policies facilitated regeneration initiatives but funding criteria based on economic deliverables presented the intangible heritage gap. Stakeholders identified niche markets for heritage tourism accommodation. Lack of research-based policies was also identified. Conclusion: Potential of regeneration is hindered by inadequate legal framework that supports contemporary needs of the tourism industry. Policies should be developed by active stakeholder participation. Adequate funding schemes have to support the tangible and intangible components of the built heritage.

Keywords: governance, historic buildings, policy, tourism

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Authors: G. Rajapakse, S. Jayasinghe, A. Fleming

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This paper aims to experimentally validate the control strategy used for electrical power converters in grid integrated oscillating water column (OWC) wave energy converter (WEC). The particular OWC’s unidirectional air turbine-generator output power results in discrete large power pulses. Therefore, the system requires power conditioning prior to integrating to the grid. This is achieved by using a back to back power converter with an energy storage system. A Li-Ion battery energy storage is connected to the dc-link of the back-to-back converter using a bidirectional dc-dc converter. This arrangement decouples the system dynamics and mitigates the mismatch between supply and demand powers. All three electrical power converters used in the arrangement are controlled using finite control set-model predictive control (FCS-MPC) strategy. The rectifier controller is to regulate the speed of the turbine at a set rotational speed to uphold the air turbine at a desirable speed range under varying wave conditions. The inverter controller is to maintain the output power to the grid adhering to grid codes. The dc-dc bidirectional converter controller is to set the dc-link voltage at its reference value. The software modeling of the OWC system and FCS-MPC is carried out in the MATLAB/Simulink software using actual data and parameters obtained from a prototype unidirectional air-turbine OWC developed at Australian Maritime College (AMC). The hardware development and experimental validations are being carried out at AMC Electronic laboratory. The designed FCS-MPC for the power converters are separately coded in Code Composer Studio V8 and downloaded into separate Texas Instrument’s TIVA C Series EK-TM4C123GXL Launchpad Evaluation Boards with TM4C123GH6PMI microcontrollers (real-time control processors). Each microcontroller is used to drive 2kW 3-phase STEVAL-IHM028V2 evaluation board with an intelligent power module (STGIPS20C60). The power module consists of a 3-phase inverter bridge with 600V insulated gate bipolar transistors. Delta standard (ASDA-B2 series) servo drive/motor coupled to a 2kW permanent magnet synchronous generator is served as the turbine-generator. This lab-scale setup is used to obtain experimental results. The validation of the FCS-MPC is done by comparing these experimental results to the results obtained by MATLAB/Simulink software results in similar scenarios. The results show that under the proposed control scheme, the regulated variables follow their references accurately. This research confirms that FCS-MPC fits well into the power converter control of the OWC-WEC system with a Li-Ion battery energy storage.

Keywords: dc-dc bidirectional converter, finite control set-model predictive control, Li-ion battery energy storage, oscillating water column, wave energy converter

Procedia PDF Downloads 90

Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Shalaka Kadam, Dinesh Apte, Sagar Mainkar

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The life cycle of products is becoming shorter and shorter due to increased competition in market, shorter product development time and increased product diversity. Short life cycles are normal in retail industry, style business, entertainment media, and telecom and semiconductor industry. The subject of accurate forecasting for demand of short lifecycle products is of special enthusiasm for many researchers and organizations. Due to short life cycle of products the amount of historical data that is available for forecasting is very minimal or even absent when new or modified products are launched in market. The companies dealing with such products want to increase the accuracy in demand forecasting so that they can utilize the full potential of the market at the same time do not oversupply. This provides the challenge to develop a forecasting model that can forecast accurately while handling large variations in data and consider the complex relationships between various parameters of data. Many statistical models have been proposed in literature for forecasting time series data. Traditional time series forecasting models do not work well for short life cycles due to lack of historical data. Also artificial neural networks (ANN) models are very time consuming to perform forecasting. We have studied the existing models that are used for forecasting and their limitations. This work proposes an effective and powerful forecasting approach for short life cycle time series forecasting. We have proposed an approach which takes into consideration different scenarios related to data availability for short lifecycle products. We then suggest a methodology which combines statistical analysis with structured judgement. Also the defined approach can be applied across domains. We then describe the method of creating a profile from analogous products. This profile can then be used for forecasting products with historical data of analogous products. We have designed an application which combines data, analytics and domain knowledge using point-and-click technology. The forecasting results generated are compared using MAPE, MSE and RMSE error scores. Conclusion: Based on the results it is observed that no one approach is sufficient for short life-cycle forecasting and we need to combine two or more approaches for achieving the desired accuracy.

Keywords: forecast, short life cycle product, structured judgement, time series

Procedia PDF Downloads 326

Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

Procedia PDF Downloads 87

Authors: Kremena Ivanona, Bistra Kunovska, Jana Djunova, Desislava Djunakova, Zdenka Stojanovska

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In recent decades, the general public has become increasingly interested in the impact of air pollutions on their health. Currently, numerous studies are aimed at identifying pollutants in the indoor environment where they carry out daily activities. Internal pollutants can be of both natural and artificial origin. With regard to natural pollutants, special attention is paid to natural radioactivity. In recent years, radon has been one of the most studied indoor pollutants because it has the greatest contribution to human exposure to natural radionuclides. It is a known fact that lung cancer can be caused by radon radiation and it is the second risk factor after smoking for the onset of the disease. The main objective of the study under the National Science Fund of Bulgaria, in the framework of grant No КП-06-Н23/1/07.12.2018 is to evaluate the indoor radon as an important air pollutant in school buildings in order to reduce the exposure to children. The measurements were performed in 48 schools located in 55 buildings in one Bulgarian administrative district (Kardjaly). The nuclear track detectors (CR-39) were used for measurements. The arithmetic and geometric means of radon concentrations are AM = 140 Bq/m3, and GM = 117 Bq/m3 respectively. In 51 school rooms, the radon levels were greater than 200 Bq/m3, and in 28 rooms, located in 17 school buildings, it exceeded the national reference level of 300 Bq/m3, defined in the Bulgarian ordinance on radiation protection (or 30% of the investigated buildings). The statistically significant difference in the values of radon concentration by municipalities (KW, р < 0.001) obtained showed that the most likely reason for the differences between the groups is the geographical location of the buildings and the possible influence of the geological composition. The combined effect of the year of construction (technical condition of the buildings) and the energy efficiency measures was considered. The values of the radon concentration in the buildings where energy efficiency measures have been implemented are higher than those in buildings where they have not been performed. This result confirms the need for investigation of radon levels before conducting the energy efficiency measures in buildings. Corrective measures for reducing the radon levels have been recommended in school buildings with high radon levels in order to decrease the children's exposure.

Keywords: air pollution, indoor radon, children exposure, schools

Procedia PDF Downloads 148

Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

Procedia PDF Downloads 232

Authors: Sayed M. Ahmed, Sawsan S. Darwish, Nagib A. Elmarzugi, Mohammad A. Al-Dosari, Mahmoud A. Adam, Nadia A. Al-Mouallimi

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The preservation of cultural heritage is a worldwide problem. Stone monuments represent an important part of this heritage, but due to their prevalently outdoor location, they are generally subject to a complex series of weathering and decay processes, in addition to physical and chemical factors, also biological agents usually play an important role in deterioration phenomena. The aim of this paper is to experimentally verify applicability and feasibility of titanium dioxide (TiO2) nanoparticles for the preservation of historical (architectural, monumental, archaeological) stone surfaces which enables to reduce the deterioration behaviors mentioned above. TiO2 nanoparticles dispersed in an aqueous colloidal suspension were applied directly on travertine (Marble and limestone often used in historical and monumental buildings) by spray-coating in order to obtain a nanometric film on stone samples. SEM, coupled with EDX microanalysis. (SEM-EDX), in order to obtain information oncoating homogeneity, surface morphology before and after aging and penetration depth of the TiO2 within the samples. Activity of the coated surface was evaluated with UV accelerated aging test. Capillary water absorption, thermal aging and colorimetric measurements have been performed on on coated and uncoated samples to evaluate their properties and estimate change of appearance with colour variation. Results show Tio2 nanoparticles good candidate for coating applications on calcareous stone, good water-repellence was observed on the samples after treatment; analyses were carried out on both untreated and freshly treated samples as well as after artificial aging. Colour change showed negligible variations on the coated or uncoated stone as well as after aging. Results showed that treated stone surfaces seem to be not affected after 1000 hours of exposure to UV radiation, no alteration of the original features.

Keywords: architectural and archaeological heritage, calcareous stone, photocatalysis TiO2, self-cleaning, thermal aging

Procedia PDF Downloads 257

Authors: Sungpil Ha, Ju Yong Kang, Sangbaek Park, Seung-Ju Lee, Soo-Won Chae

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The growing number of obese patients in aging societies has led to an increase in the number of patients with knee medial osteoarthritis (OA). Artificial joint insertion is the most common treatment for knee medial OA. Surgery is effective for patients with serious arthritic symptoms, but it is costly and dangerous. It is also inappropriate way to prevent a disease as an early stage. Therefore Non-operative treatments such as toe-in gait are proposed recently. Toe-in gait is one of non-surgical interventions, which restrain the progression of arthritis and relieves pain by reducing knee adduction moment (KAM) to facilitate lateral distribution of load on to knee medial cartilage. Numerous studies have measured KAM in various foot progression angle (FPA), and KAM data could be obtained by motion analysis. However, variations in stress at knee cartilage could not be directly observed or evaluated by these experiments of measuring KAM. Therefore, this study applied motion analysis to major gait points (1st peak, mid –stance, 2nd peak) with regard to FPA, and to evaluate the effects of FPA on the human lower extremity, the finite element (FE) method was employed. Three types of gait analysis (toe-in, toe-out, baseline gait) were performed with markers placed at the lower extremity. Ground reaction forces (GRF) were obtained by the force plates. The forces associated with the major muscles were computed using GRF and marker trajectory data. MRI data provided by the Visible Human Project were used to develop a human lower extremity FE model. FE analyses for three types of gait simulations were performed based on the calculated muscle force and GRF. We observed the maximum stress point during toe-in gait was lower than the other types, by comparing the results of FE analyses at the 1st peak across gait types. This is the same as the trend exhibited by KAM, measured through motion analysis in other papers. This indicates that the progression of knee medial OA could be suppressed by adopting toe-in gait. This study integrated motion analysis with FE analysis. One advantage of this method is that re-modeling is not required even with changes in posture. Therefore another type of gait simulation or various motions of lower extremity can be easily analyzed using this method.

Keywords: finite element analysis, gait analysis, human model, motion capture

Procedia PDF Downloads 314

Authors: Carmen Sica, Elena M. Scalisi, Sara Ignoto, Ludovica Palmeri, Martina Contino, Greta Ferruggia, Antonio Salvaggio, Santi C. Pavone, Gino Sorbello, Loreto Di Donato, Roberta Pecoraro, Maria V. Brundo

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Recently, a rise in the use of wireless internet technologies such as Wi-Fi and 5G routers/modems have been demonstrated. These devices emit a considerable amount of electromagnetic radiation (EMR), which could interact with the male reproductive system either by thermal or non-thermal mechanisms. The aim of this study was to investigate the direct in vitro influence of 5G radiation on sperm quality in Mytilus galloprovincialis, considered an excellent model for reproduction studies. The experiments at 27 GHz were conducted by using a no commercial high gain pyramidal horn antenna. To evaluate the specific absorption rate (SAR), a numerical simulation has been performed. The resulting incident power density was significantly lower than the power density limit of 10 mW/cm2 set by the international guidelines as a limit for nonthermal effects above 6 GHz. However, regarding temperature measurements of the aqueous sample, it has been verified an increase of 0.2°C, compared to the control samples. This very low-temperature increase couldn’t interfere with experiments. For experiments, sperm samples taken from sexually mature males of Mytilus galloprovincialis were placed in artificial seawater, salinity 30 + 1% and pH 8.3 filtered with a 0.2 m filter. After evaluating the number and quality of spermatozoa, sperm cells were exposed to electromagnetic fields a 27GHz. The effect of exposure on sperm motility and quality was evaluated after 10, 20, 30 and 40 minutes with a light microscope and also using the Eosin test to verify the vitality of the gametes. All the samples were performed in triplicate and statistical analysis was carried out using one-way analysis of variance (ANOVA) with Turkey test for multiple comparations of means to determine differences of sperm motility. A significant decrease (30%) in sperm motility was observed after 10 minutes of exposure and after 30 minutes, all sperms were immobile and not vital. Due to little literature data about this topic, these results could be useful for further studies concerning a great diffusion of these new technologies.

Keywords: mussel, spermatozoa, sperm motility, millimeter waves

Procedia PDF Downloads 133