Search results for: natural intelligence

Authors: Lien Fa Lin, Yung Ming Li, Hsin Chen Hsieh

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The rise of smartphones brings new concept So-Lo-Mo (social-local-mobile) in mobile commerce area in recent years. However, current So-Lo-Mo services only focus on individual users but not a group of users, and the development of group commerce is not enough to satisfy the demand of real-time group buying and less to think about the social relationship between customers. In this research, we integrate mobile intelligence with group commerce and consider customers' preference, real-time context, and social influence as components in the mechanism. With the support of this mechanism, customers are able to gather near customers with the same potential purchase willingness through mobile devices when he/she wants to purchase products or services to have a real-time group-buying. By matching the demand and supply of mobile group-buying market, this research improves the business value of mobile commerce and group commerce further.

Keywords: group formation, group commerce, mobile commerce, So-Lo-Mo, social influence

Procedia PDF Downloads 415

Authors: Walid Moudani, Ahmad Shahin

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This research presents a study to handle the recruitment services system. It aims to enhance a business intelligence system by embedding data mining in its core engine and to facilitate the link between job searchers and recruiters companies. The purpose of this study is to present an intelligent management system for supporting recruitment services based on data mining methods. It consists to apply segmentation on the extracted job postings offered by the different recruiters. The details of the job postings are associated to a set of relevant features that are extracted from the web and which are based on critical criterion in order to define consistent clusters. Thereafter, we assign the job searchers to the best cluster while providing a ranking according to the job postings of the selected cluster. The performance of the proposed model used is analyzed, based on a real case study, with the clustered job postings dataset and classified job searchers dataset by using some metrics.

Keywords: job postings, job searchers, clustering, genetic algorithms, business intelligence

Procedia PDF Downloads 329

Authors: Abdulmalek Ahmed

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Formation pressure is the main function that affects drilling operation economically and efficiently. Knowing the pore pressure and the parameters that affect it will help to reduce the cost of drilling process. Many empirical models reported in the literature were used to calculate the formation pressure based on different parameters. Some of these models used only drilling parameters to estimate pore pressure. Other models predicted the formation pressure based on log data. All of these models required different trends such as normal or abnormal to predict the pore pressure. Few researchers applied artificial intelligence (AI) techniques to predict the formation pressure by only one method or a maximum of two methods of AI. The objective of this research is to predict the pore pressure based on both drilling parameters and log data namely; weight on bit, rotary speed, rate of penetration, mud weight, bulk density, porosity and delta sonic time. A real field data is used to predict the formation pressure using five different artificial intelligence (AI) methods such as; artificial neural networks (ANN), radial basis function (RBF), fuzzy logic (FL), support vector machine (SVM) and functional networks (FN). All AI tools were compared with different empirical models. AI methods estimated the formation pressure by a high accuracy (high correlation coefficient and low average absolute percentage error) and outperformed all previous. The advantage of the new technique is its simplicity, which represented from its estimation of pore pressure without the need of different trends as compared to other models which require a two different trend (normal or abnormal pressure). Moreover, by comparing the AI tools with each other, the results indicate that SVM has the advantage of pore pressure prediction by its fast processing speed and high performance (a high correlation coefficient of 0.997 and a low average absolute percentage error of 0.14%). In the end, a new empirical correlation for formation pressure was developed using ANN method that can estimate pore pressure with a high precision (correlation coefficient of 0.998 and average absolute percentage error of 0.17%).

Keywords: Artificial Intelligence (AI), Formation pressure, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Support Vector Machine (SVM), Functional Networks (FN), Radial Basis Function (RBF)

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

Procedia PDF Downloads 83

Authors: Wendy de Gomez

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Standardization is a critical element in the ability of a society to reduce uncertainty, subjectivity, misrepresentation, and interpretation while simultaneously contributing to innovation. Technological standardization is critical to codify specific operationalization through legal instruments that provide rules of development, expectation, and use. In the current emerging technology landscape Artificial Intelligence (AI) hardware as a general use technology has seen incredible growth as evidenced from AI technology patents between 2012 and 2018 in the United States Patent Trademark Office (USPTO) AI dataset. However, as outlined in the 2023 United States Government National Standards Strategy for Critical and Emerging Technology the codification through standardization of emerging technologies such as AI has not kept pace with its actual technological proliferation. This gap has the potential to cause significant divergent possibilities for the downstream outcomes of AI in both the short and long term. This original empirical research provides an overview of the standardization efforts around AI in different geographies and provides a background to standardization law. It quantifies the longitudinal trend of Artificial Intelligence hardware patents through the USPTO AI dataset. It seeks evidence of existing Standard Essential Patents from these AI hardware patents through a text analysis of the Statement of patent history and the Field of the invention of these patents in Patent Vector and examines their determination as a Standard Essential Patent and their inclusion in existing AI technology standards across the four main AI standards bodies- European Telecommunications Standards Institute (ETSI); International Telecommunication Union (ITU)/ Telecommunication Standardization Sector (-T); Institute of Electrical and Electronics Engineers (IEEE); and the International Organization for Standardization (ISO). Once the analysis is complete the paper will discuss both the theoretical and operational implications of F/Rand Licensing Agreements for the owners of these Standard Essential Patents in the United States Court and Administrative system. It will conclude with an evaluation of how Standard Setting Organizations (SSOs) can work with SEP owners more effectively through various forms of Intellectual Property mechanisms such as patent pools.

Keywords: patents, artifical intelligence, standards, F/Rand agreements

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Authors: Bahar Basturk, Secil Celik Erbas, Sevket Can Sarikaya

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Composites combining the particulates and polymer components have attracted great interest in various application areas such as packaging, furniture, electronics and automotive industries. For strengthening the plastic matrices, the utilization of natural fillers instead of traditional reinforcement materials has received increased attention. The properties of natural filler based polymer composites (NFPC) may be improved by applying proper surface modification techniques to the powder phase of the structures. In this study, acorn powder-epoxy and pine corn powder-epoxy composites containing up to 45% weight percent particulates were prepared by casting method. Alkali treatment and acetylation techniques were carried out to the natural particulates for investigating their influences under mechanical forces. The effects of filler type and content on the tensile properties of the composites were compared with neat epoxy. According to the quasi-static tensile tests, the pine cone based composites showed slightly higher rigidity and strength properties compared to the acorn reinforced samples. Furthermore, the structures independent of powder type and surface modification technique, showed higher tensile properties with increasing the particle content.

Keywords: natural fillers, polymer composites, surface modifications, tensile properties

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Authors: Serge Lacroix

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The proposed study looks at the psychoeducational assessment of bilingual students, in English and French in this case. It will be the opportunity to look at language of assessment and specifically how certain tests can be administered in one language and others in another language. It is also a look into the questioning of the validity of the test scores that are obtained as well as the quality and generalizability of the conclusions that can be drawn. Bilingualism and multiculturalism, although in constant expansion, is not considered in norms development and remains a poorly understood factor when it is at play in the context of a psychoeducational assessment. Student placement, diagnoses, accurate measures of intelligence and achievement are all impacted by the quality of the assessment procedure. The same is true for questionnaires administered to parents and self-reports completed by bilingual students who, more often than not, are assessed in a language that is not their primary one or are compared to monolinguals not dealing with the same challenges or the same skills. Results show that students, when offered to work in a bilingual fashion, chooses to do so in a significant proportion. Recommendations will be offered to support educators aiming at expanding their skills when confronted with multilingual students in an assessment context.

Keywords: psychoeducational assessment, bilingualism, multiculturalism, intelligence, achievement

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Authors: Pavel E. Mikriukov

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The demand for natural gas (NG) is increasing every year around the world, so it is necessary to produce and transport NG in large quantities. To solve this problem, liquefied natural gas (LNG) plants are used, using different equipment and different technologies to achieve the required LNG quality. To determine the best efficiency of the LNG liquefaction plant, it is necessary to analyze the equipment used in this process and identify other technological solutions for LNG production using more productive and energy-efficient equipment. Based on this, mathematical models of the technological process of the LNG plant were created, which are based on a two-circuit system of heat exchange equipment and a nitrogen isolated cycle for NG cooling. The final liquefaction of natural gas is performed on the construction of the basic principle of the Joule-Thompson effect. The pressure and temperature drop are considered on different types of equipment such as throttle valve, which was used in the basic scheme; turbo expander and supersonic separator, which act as new equipment, to be compared with the efficiency of the basic scheme of the unit. New configurations of LNG plants are suggested, which can be used in almost all LNG facilities. As a result of the analysis, it turned out that the turbo expander and the supersonic separator have comparatively equal potential in comparison with the baseline scheme execution on the throttle valve. A more rational method of selecting the technology and the equipment used for natural gas liquefaction can improve the efficiency of low-tonnage plants and reduce the cost of gas for own needs.

Keywords: gas liquefaction, gas, Joule-Thompson effect, LNG, low-tonnage LNG, supersonic separator, Throttle valve, turbo expander

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Varinder Kaur, Amanjit Kaur, Simran Kaur, Samriti Vaid

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Coating of fabrics with anti-microbial dyes is an adaptable technique of protection from various diseases. Natural dyes, which are known to possess antibacterial properties, can be used for antibacterial finishing of fibers like cotton, wool, bamboo and so many. Dyeing of fabrics with natural dyes normally requires the use of mordants so that dyes can stay on the fabric as well as into interstices of the fabric during multiple washings. In this study, the mordants used are alum and chitosan for ensuring a reasonable color fastness to light and washing. Chitosan is a natural polysaccharide having significant biological and chemical properties such as biodegradability, biocompatibility, bioactivity, microbial activity and polycationicity. The metal ion of alum mordant can act as electron acceptor for electron donor to form coordination bond with the dye molecule, making them insoluble in water. The dyeing of bamboo fabric using a natural dye extracted from turmeric has been studied using conventional dyeing method. Natural dye was extracted using water as solvent by Soxhlet extraction method. The extracted color was characterized by spectroscopic studies like UV/visible and further tested for antimicrobial activity. The effect of mordants on the dyeing outcome in terms of colour depth as well as fastness properties of the dyeing was investigated. It has been found that employing the conventional dyeing technique at 100 oC, the mordanted samples were deeper in depth than their unmordanted counterparts. The results of fastness properties of the dyed fabrics were fair to good. Turmeric extract was found to enhance microbial resistance of bamboo as well as was itself as a good cause of coloration. These textiles dyed with the turmeric as natural dye can be very useful in developing clothing for infants, elderly and infirm people to protect them against common infections. The outcome of this study will provide a new feature to the interface of dyeing and pharmaceutical industry.

Keywords: antimicrobial activity, bamboo fabric, natural dye, turmeric

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Authors: I. Sterbova, E. Oberhofnerova, M. Panek, M. Pavelek

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With growing popularity, wood of European larch (Larix decidua, Mill.) is being more often applied into the exterior, usually as facade elements, also without surface treatment. The aim of this work was to compare two laboratory tests of artificial accelerated weathering of wood with two ways of natural weathering in the exterior. To assess changes in selected surface characteristics of larch wood, accelerated weathering methods in the Xenotest and UV chamber were used, both in combination with temperature cycling, for 6 weeks. They were compared with natural weathering results at exposition under 45° and 90° in the exterior for 12 months. The changes of colour, gloss, contact angle of water and also changes in visual characteristics were evaluated. The results of wood surfaces changes after 6 weeks of accelerated weathering in Xenotest are closer to 12 months of natural weathering in the exterior at an angle of 90° compared to the UV chamber testing. The results, especially the colour changes, of the samples exposed at an angle of 45° in the exterior were significantly different. Testing in Xenotest more closely simulates the weathering of façade elements in the exterior compared to the UV chamber testing.

Keywords: larch wood, wooden facade, wood accelerated weathering, weathering methods

Procedia PDF Downloads 139

Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

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In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

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Authors: Koryukaeva Ksenia, Jinfeng Sun

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Europe has been a traditional importer of Russian natural gas for more than 50 years. In 2021, Russian state-owned company Gazprom supplied about a third of all gas consumed in Europe. The Russia-Europe mutual dependence in terms of natural gas supplies has been causing many concerns about the energy security of the two sides for a long period of time. These days the issue has become more urgent than ever considering recent Russian invasion in Ukraine followed by increased large-scale geopolitical conflicts, making the future of Russian natural gas supplies and global gas markets as well highly uncertain. Hence, the main purpose of this study is to get insight into the possible futures of Russian pipeline natural gas exports by a scenario planning method based on Monte-Carlo simulation within LUSS model framework, and propose Russian pipeline natural gas export strategies based on the obtained scenario planning results. The scenario analysis revealed that recent geopolitical disputes disturbed the traditional, longstanding model of Russian pipeline gas exports, and, as a result, the prospects and the pathways for Russian pipeline gas on the world markets will differ significantly from those before 2022. Specifically, our main findings show, that (i) the events of 2022 generated many uncertainties for the long-term future of Russian pipeline gas export perspectives on both western and eastern supply directions, including geopolitical, regulatory, economic, infrastructure and other uncertainties; (ii) according to scenario modelling results, Russian pipeline exports will face many challenges in the future, both on western and eastern directions. A decrease in pipeline gas exports will inevitably affect country’s natural gas production and significantly reduce fossil fuel export revenues, jeopardizing the energy security of the country; (iii) according to proposed strategies, in order to ensure the long-term stable export supplies in the changing environment, Russia may need to adjust its traditional export strategy by performing export flows and product diversification, entering new markets, adapting its contracting mechanism, increasing competitiveness and gaining a reputation of a reliable gas supplier.

Keywords: Russian natural gas, Pipeline natural gas, Uncertainty, Scenario simulation, Export strategy

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Authors: Maria Neagu

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This paper presents the heat and mass driven natural convection succession in a Darcy thermally stratified porous medium that embeds a vertical semi-infinite impermeable wall of constant heat flux and concentration. The scale analysis of the system determines the two possible maps of the heat and mass driven natural convection sequence along the wall as a function of the process parameters. These results are verified using the finite differences method applied to the conservation equations.

Keywords: finite difference method, natural convection, porous medium, scale analysis, thermal stratification

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Authors: Fulya Ozbey, Ecehan Ozmehmet

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Health and living in a healthy environment are important for all the living creatures. Healthy buildings are the part of the healthy environment and the ones that people and sometimes the animals spend most of their times in it. Therefore, healthy buildings are important subject for everybody. There are many elements of the healthy buildings from material choice to the thermal comfort including indoor air quality. The aim of this study is, to simulate two natural ventilation strategies which are used as a cooling method in Mediterranean climate, by applying to a residential building and compare the results for Asian climate. Fulltime natural and night-time ventilation strategies are simulated for three days during the summertime in Mediterranean climate. The results show that one of the chosen passive cooling strategies worked on both climates good enough without using additional shading element and cooling device, however, the other ventilation strategy did not provide comfortable indoor temperature enough. Finally, both of the ventilation strategies worked better on the Asian climate than the Mediterranean in terms of the total overheating hours during the chosen period of year.

Keywords: Asian climate, indoor air quality, Mediterranean climate, natural ventilation simulation, thermal comfort

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Authors: Fatma Faheem, K. Abduraheem

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Museums are custodians of natural and cultural heritage. Objects like tribal dresses, headgears, weapons, musical instruments, manuscripts and other ethnocultural materials housed in museums are prized possessions of intellectual and cultural property of people. Tropical countries like India have a favorable climatic condition for biodeterioration. Organic materials such as leather and parchment objects which form a substantial part of natural history collections of museums across the world are promptly infested by insects like dermestid beetles, tenebrionides, silver fishes, cockroaches and other micro-organisms. The environmental problems caused due to the overuse of pesticides and other non-degradable chemicals have been the matter of serious concern for both the scientists and public in recent years. Synthetic pesticides are very expensive and also highly toxic for humans and its environment. Due to its high health risk factor government has taken severe initiatives on policy of banning it. In order to overcome the problems of biodeterioration, natural biocides should be applied. In this paper, comparative study has been done to investigate the toxic efficacy of Myristica fragrans and Syzygium aromaticum oil in variation with contact and stomach toxicity against larvae of Anthrenus verbasci.

Keywords: biodeterioration, contact toxicity, cultural heritage, natural biocides, natural heritage, stomach toxicity

Procedia PDF Downloads 245

Authors: Ralf Gliniorz, Carolin Petzoldt, Andreas Ehrlich, Sandra Gelbrich, Lothar Kroll

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The building envelope is integral part of buildings, and renewable resources have a key role in energy consumption. So our aim was the development and implementation of a free forming facade system, consisting of fibre-reinforced polymer, which is built up of commercial biobased resin systems and natural fibre reinforcement. The field of application is aimed in modern architecture, like the office block 'Fachagentur Nachwachsende Rohstoffe e.V.' with its oak wood recyclate facade. The build-up of our elements is a classically sandwich-structured composite: face sheets as fibre-reinforced composite using polymer matrix, here a biobased epoxy, and natural fibres. The biobased core consists of stuck cardboard structure (BC-flute). Each element is manufactured from two shells in a counterpart, via hand lay-up laminate. These natural fibre skins and cardboard core have adhered 'wet-on-wet'. As a result, you get the effect of translucent face sheets with matrix illumination. Each created pixel can be controlled in RGB-colours and form together a screen at buildings. A 10 x 5 m² area 'NFP-BIO' with 25 elements is planned as a reference object in Chemnitz. The resolution is about 100 x 50 pixels. Specials are also the efficient technology of production and the possibility to extensively 3D-formed elements for buildings, replacing customary facade systems, which can give out information or advertising.

Keywords: biobased facade, cardboard core, natural fibre skins, sandwich element

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Authors: Brittany Duboz-Quinville

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Emotional Intelligence (EI) is a growing field, and many studies are examining how it pertains to the workplace. In the context of crisis management several studies have postulated that EI could play a role in individuals’ ability to execute crisis plans. However, research evaluating the EI of leaders who have actually managed a crisis is still lacking. The COVID-19 pandemic forced many businesses into a crisis situation beginning in March and April of 2020. This study sought to measure both EI and effective crisis management (CM) during the COVID-19 pandemic to determine if they were positively correlated. A quantitative survey was distributed via the internet that comprised of 15 EI statements, and 15 CM statements with Likert scale responses, and 6 demographic questions with discrete responses. The hypothesis of the study was: it is believed that EI correlates positively with effective crisis management. The results of the study did not support the studies hypothesis as the correlation between EI and CM was not statistically significant. An additional correlation was tested, comparing employees’ perception of their superiors’ EI (Perception) to employees’ opinion of how their superiors managed the crisis (Opinion). This Opinion and Perception correlation was statistically significant. Furthermore, by examining this correlation through demographic divisions there are additional significant results, notably that French speaking employees have a stronger Opinion/Perception correlation than English speaking employees. Implications for cultural differences in EI and CM are discussed as well as possible differences across job sectors. Finally, it is hoped that this study will serve to convince more companies, particularly in France, to embrace EI training for staff and especially managers.

Keywords: crisis management, emotional intelligence, empathy, management training

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Authors: Dionisios Panagiotaras, Ioannis P. Kokkoris, Dionysios Koulougliotis, Dimitra Lekka, Alexandra Skalioti

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In the summer of 2021, Greece was affected by devastating forest fires in various regions of the country, resulting in human losses, destruction or degradation of the natural environment, infrastructure, livestock and cultivations. The present study concerns a pilot assessment of natural vegetation regeneration in the second, in terms of area, fire-affected region for 2021, at Ancient Olympia area, located in West Peloponnisos (Ilia Prefecture), Greece. A standardised field sampling protocol for assessing natural regeneration was implemented at selected sites where the forest fire had occurred previously (in 2007), and the vegetation (Pinus halepensis forest) had regenerated naturally. The results of the study indicate the loss of the established natural regeneration of Pinus halepensis forest, as well as of the tree-layer in total. Post-fire succession species are recorded to the shrub and the herb layer, with a varying cover. Present findings correspond to the results of field work and analysis one year after the fire, which will form the basis for further research and conclusions on taking action for restoration schemes in areas that have been affected by fire more than once within a 20-year period.

Keywords: forest, pinus halepensis, ancient olympia, post fire vegetation

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Authors: Justin Bin

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Artificial intelligence (AI) has been rapidly rising in usage recently, already active in the daily lives of millions, from distinguished AIs like the popular ChatGPT or Siri to more obscure, inconspicuous AIs like those used in social media or internet search engines. As upcoming generations grow immersed in emerging technology, AI will play a vital role in their development. Namely, the education sector, an influential portion of a person’s early life as a student, faces a vast ocean of possibilities concerning the implementation of AI. The main purpose of this study is to analyze the effect that AI will have on the future of the educational field. More particularly, this study delves deeper into the following three categories: school admissions, the productivity of students, and ethical concerns (role of human teachers, purpose of schooling itself, and significance of diplomas). This study synthesizes research and data on the current effects of AI on education from various published literature sources and journals, as well as estimates on further AI potential, in order to determine the main, overarching effects it will have on the future of education. For this study, a systematic organization of data in terms of type (quantitative vs. qualitative), the magnitude of effect implicated, and other similar factors were implemented within each area of significance. The results of the study suggest that AI stands to change all the beforementioned subgroups. However, its specific effects vary in magnitude and favorability (beneficial or harmful) and will be further discussed. The results discussed will reveal to those affiliated with the education field, such as teachers, counselors, or even parents of students, valuable information on not just the projected possibilities of AI in education but the effects of those changes moving forward.

Keywords: artificial intelligence, education, schools, teachers

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Authors: Shen Xiaoyun

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The AI-generated works must intersect with the right holder’s work, thus having a certain impact on the rights and interests of the right holder’s work. The law needs to explore and improve the regulation of the fair use of AI creations and build a compensation system to adapt to the development of the times. The development of AI technology has brought about problems such as the unclear relationship between fair use and infringement of copyright, the unclear general terms and conditions of application, and the incomplete criteria for judging at different stages. Through different theoretical methods, the legitimacy of the rational use of the system can be demonstrated. The compensation standard for fair use of copyright in AI creation can refer to the market pricing of the right holder's work, and the compensation can construct a formula for the amount of damages for AI copyright infringement, and construct the compensation standard based on the main factors affecting the market value of the work, so as to provide a reference for the construction of a compensation system for fair use of works generated by AI.

Keywords: artificial intelligence, creative acts, fair use of copyright, copyright compensation system

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Authors: Mohammed Talib Alkiyumi

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The Sultanate of Oman is characterized by a huge musical heritage that remains mostly preserved. 142 different traditional musical genres and styles (funun) have been registered in the Sultanate. This large number is a unique phenomenon that is worthy of attention and study. These genres and styles are different from others in their origins, rhythms, melodies, poetry, dance movements, etc. Certainly, Oman is exposed to other cultures and there is a variety of ethnicities in the Sultanate; however, this musical diversity is mostly an Omani product. This paper investigates the psychological motives behind Omani musical creativity. This qualitative study is based on relevant documents, as well as an analysis of Omani performance in those genres through documentary films and direct observations. Musical genres are performed in social events such as weddings and celebrations; however, research has shown psychological motives that motivated Omani people to create these various genres, such as provocation of enthusiasm, meditation, religious motivations, poetic competition, and emotional motivation. For each motive, musical genres have been presented.

Keywords: traditional musical, creativity, musical intelligence, Sultanate of Oman

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Authors: H. Bhowmik, A. Faisal, Ahmed Al Yaarubi, Nabil Al Alawi

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Experiments are conducted to analyze the steady-state and the power-on transient natural convection heat transfer from a horizontal cylinder mounted in a vertical up flow circular duct. The heat flux ranges from 177 W/m² to 2426 W/m² and the Rayleigh number ranges from 1×10⁴ to 4.35×10⁴. For natural air flow and constant heat flux condition, the effects of heat transfer around the cylinder under steady-state condition are investigated. The steady-state results compare favorably with that of the available data. The effects of transient heat transfer data on different angular position of the thermocouple (0^o, 90^o, 180^o) are also reported. It is observed that the transient heat transfer around the cylinder is strongly affected by the position of thermocouples. In the transient region, the rate of heat transfer obtained at 90^o and 180^o are higher than that of stagnation point (0^o). Finally, the dependence of the average Nusselt number on Rayleigh number for steady and transient natural convection heat transfer are analyzed, and a correlation equation is presented.

Keywords: Fourier number, Nusselt number, Rayleigh number, steady state, transient

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Authors: Katarina Živković, Ivana Joksimović

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Many different chemicals may occur in drinking water and cause significant human health risks after prolonged periods of exposure. In particular concern are contaminants that have cumulative toxic properties, such as heavy metals. This investigation was done to clarify concerns about chemical quality and safety of drinking tap water in Podgorica. For comparison, all available natural bottled water on Montenegrin market were bought. All samples (bottled water and tap water from Podgorica) were analyzed using ICP –OES on contents of Al, Cd, Pb, Cu, Zn,Cr, Fe, As and Mn. All results compared with the maximum concentration levels allowed by international standards and World Health Organization (WHO) guidelines. The results of analysis showed that all trace of heavy metals were very low and in same time below MCL according to WHO and International standard.

Keywords: inductively coupled plasma - optical emission spectrometry (ICP-OES), Montenegro (Podgorica), natural bottled water, tap water , trace of heavy metal

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Authors: Chih Chin Yang, Chung Shan Sun

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In this paper, the relationships between professional competences and school curricula in IC design industry are explored. The semi-structured questionnaire survey and focus group interview is the research method. Study participants are graduates of microelectronics engineering professional departments who are currently employed in the IC industry. The IC industries are defined as the electronic component manufacturing industry and optical-electronic component manufacturing industry in the semiconductor industry and optical-electronic material devices, respectively. Study participants selected from IC design industry include IC engineering and electronic & semiconductor engineering. The human training with IC design professional competence in microelectronics engineering professional departments is explored in this research. IC professional competences of human resources in the IC design industry include general intelligence and professional intelligence.

Keywords: IC design, curricula, competence, task, duty

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Authors: Belaynesh Chekol, Numan Çelebi

Abstract:

The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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Authors: Sakchai Satienperakul, Manoch Thanomwat, Jutiporn Seedasama

Abstract:

A paper based analytical devices (PADs) for the analysis of Fe (III) ion in natural water samples is developed, using reagent from guava leaf extract. The extraction is simply performed in deionized water pH 7, where tannin extract is obtained and used as an alternative natural reagent. The PADs are fabricated by ink-jet printing using alkenyl ketene dimer (AKD) wax. The quantitation of Fe (III) is carried out using reagent from guava leaf extract prepared in acetate buffer at the ratio of 1:1. A color change to gray-purple is observed by naked eye when dropping sample contained Fe (III) ion on PADs channel. The reflective absorption measurement is performed for creating a standard curve. The linear calibration range is observed over the concentration range of 2-10 mg L-1. Detection limited of Fe (III) is observed at 2 mg L-1. In its optimum form, the PADs is stable for up to 30 days under oxygen free conditions. The small dimensions, low volume requirement and alternative natural reagent make the proposed PADs attractive for on-site environmental monitoring and analysis.

Keywords: green chemical analysis, guava leaf extract, lab on a chip, paper based analytical device

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Authors: Ozge Celik, Elvan Ender

Abstract:

With rapidly increasing population growth and industrial revolution in the 1950s, in Turkey migration began to the cities from the countryside. Along the rapid growth of urban population has started to bring many problems. Depending on the uncontrolled urban development, concerns about the protection of natural values has increased day by day. As a result of disturbance on the natural environment, human health has started to be under threat. After all, much urban planning approaches outspread that protecting natural resources by respect to human health and troubleshooting problems emerging with anthropogenic effects. Smart growth concept is one of the chosen methods to resolve the problems in Turkey. In this paper, smart growth concept idea and its criteria will be explained while ecological planning and urban planning problems will be mentioned in Turkey according to the need of concept. Studies, consisting of practical and theoretical smart growth ideas, shows that ecological landscape planning is not included in the urban development process in Turkey. The main idea is to initiate urban development plans considering social and cultural structures of cultural assets and also natural values.

Keywords: ecological landscape planning, smart growth, Turkey, urban development

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Authors: Payal Maheshwari, Bansari Shah

Abstract:

The research aimed to study the level of emotional intelligence (EI) and organizational role stress (ORS) of fire-fighters and the relationship between the two variables. Hundred and twenty fire-fighters were selected from different fire stations of Mumbai by purposive sampling. The firefighters who had the basic training, a minimum experience of 2 years and had been on the field during a crisis situation were selected for the study. The firefighters selected ranged from 23-58 years of age, and the number of years of experience ranged from 2 to 33 years. The findings of the study revealed that majority of the firefighters perceived themselves to be at an above average (57) and high (58) level of EI (M=429.35, SD=38.712). Domain-wise analysis disclosed that compared to self-awareness (92) and relationship management (93), more number of participants perceived themselves in the high category in the domains of self-management (108) and social management (106). Further, examination of the subdomain scores conveyed that a large number of participants rated themselves in the average level of these skills of accurate self-assessment (50), emotional self-control (50), adaptability (56) initiative (41), influence (66), change catalyst (53), and conflict management (50). With relation to the stress variable, it was found that almost half the number of the participants (59) rated themselves as having an average level of stress (M=137.44, SD=28.800). In most of the domains, majority of the participants perceived themselves as having an average level of stress, while in the domain of role isolation, self-role distance, and role ambiguity, majority of the firefighters rated themselves as having a low level of stress. A strong negative correlation (r=-.360**, p=.000) was found between EI and ORS. This study is a contribution to the literature and has implications for fire-fighters at the personal level, for the policymakers, and the fire department.

Keywords: emotional intelligence, organizational role stress, firefighters, relationship

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Authors: Palash Bandyopadhyay

Abstract:

Background and significance of the study: Crude oil and natural gas is of crucial importance due to its increasing demand in India. The demand has been increased because of change of lifestyle overtime. Since India has poor utilization of oil production capacity, constantly the import of it has been increased progressively day by day. This ultimately hit the foreign exchange reserves of India, however it negatively affect the Indian economy as well. The financial performance of crude oil and natural gas companies in India has been trimmed down year after year because of underutilization of production capacity, enhancement of demand, change in life style, and change in import bill and outflows of foreign currencies. In this background, the current study seeks to measure the financial performance of crude oil and natural gas companies of India in the post liberalization period. Keeping in view of this, this study assesses the financial performance in terms of liquidity management, solvency, efficiency, financial stability, and profitability of the companies under study. Methodology: This research work is encircled on yearly ratio data collected from Centre for Monitoring Indian Economy (CMIE) Prowess database for the periods between 1993-94 and 2012-13 with 20 observations using liquidity, solvency and efficiency indicators, profitability indicators and financial stability indicators of all the major crude oil and natural gas companies in India. In the course of analysis, descriptive statistics, correlation statistics, and linear regression test have been utilized. Major findings: Descriptive statistics indicate that liquidity position is satisfactory in case of three crude oil and natural gas companies (Oil and Natural Gas Companies Videsh Limited, Oil India Limited and Selan exploration and transportation Limited) out of selected companies under study but solvency position is satisfactory only for one company (Oil and Natural Gas Companies Videsh Limited). However, efficiency analysis points out that Oil and Natural Gas Companies Videsh Limited performs effectively the management of inventory, receivables, and payables, but the overall liquidity management is not well. Profitability position is very much satisfactory in case of all the companies except Tata Petrodyne Limited, but profitability management is not satisfactory for all the companies under study. Financial stability analysis shows that all the companies are more dependent on debt capital, which bears a financial risk. Correlation and regression test results illustrates that profitability is positively and negatively associated with liquidity, solvency, efficiency, and financial stability indicators. Concluding statement: Management of liquidity and profitability of crude oil and natural gas companies in India should have been improved through controlling unnecessary imports in spite of the heavy demand of crude oil and natural gas in India and proper utilization of domestic oil reserves. At the same time, Indian government has to concern about rupee depreciation and interest rates.

Keywords: financial performance, crude oil and natural gas companies, India, linear regression

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