Search results for: natural intelligence

Authors: M. Hosseinnezhad, K. Gharanjig

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Natural dyes, extracted from black carrot and bramble, were utilized as photosensitizers to prepare dye-sensitized solar cells (DSSCs). Spectrophotometric studies of the natural dyes in solution and on a titanium dioxide substrate were carried out in order to assess changes in the status of the dyes. The results show that the bathochromic shift is seen on the photo-electrode substrate. The chemical binding of the natural dyes at the surface photo-electrode were increased by the chelating effect of the Ti(IV) ions. The cyclic voltammetry results showed that all extracts are suitable to be performed in DSSCs. Finally, photochemical performance and stability of DSSCs based on natural dyes were studied. The DSSCs sensitized by black carrot extract have been reported to achieve up to Jsc=1.17 mAcm^-2, Voc= 0.55 V, FF= 0.52, η=0.34%, whereas Bramble extract can obtain up to Jsc=2.24 mAcm^-2, Voc= 0.54 V, FF= 0.57, η=0.71%. The power conversion efficiency was obtained from the mixed dyes in DSSCs. The power conversion efficiency of dye-sensitized solar cells using mixed Black carrot and Bramble dye is the average of the their efficiency in single DSSCs.

Keywords: anthocyanin, dye-sensitized solar cells, green energy, optical materials

Procedia PDF Downloads 245

Authors: Luis Rodrigo Valencia Perez, Francisco Flores Aguero, Gibran Aguilar Rangel

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Artificial Intelligence (AI) is rapidly transforming diverse sectors, and higher education in Latin America is no exception. This article explores the impact of AI on higher education institutions in the region, highlighting the imperative need for well-trained teachers in emerging technologies and a cultural shift towards the adoption and efficient use of these tools. AI offers significant opportunities to improve learning personalization, optimize administrative processes, and promote more inclusive and accessible education. However, the effectiveness of its implementation depends largely on the preparation and willingness of teachers to integrate these technologies into their pedagogical practices. Furthermore, it is essential that Latin American countries develop and implement public policies that encourage the adoption of AI in the education sector, thus ensuring that institutions can compete globally. Policies should focus on the continuous training of educators, investment in technological infrastructure, and the creation of regulatory frameworks that promote innovation and the ethical use of AI. Only through a comprehensive and collaborative approach will it be possible to fully harness the potential of AI to transform higher education in Latin America, thereby boosting the region's development and competitiveness on the global stage.

Keywords: artificial intelligence (AI), higher education, teacher training, public policies, latin america, global competitiveness

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Authors: Nada Alqadri, Omaima Nasir

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Natural compounds are an important source of potential inhibitors; they have a lot of pharma potential with less adverse effects. The effective antiviral activities of natural products have been proved in different studies. The outbreak of COVID-19 in Wuhan, Hubei, in December 2019, coronavirus has had a significant impact on people's health and lives. Based on previous studies, natural products can be introduced as preventive and therapeutic agents in the fight against COVID-19; considering that no food or supplement has been authorized to prevent COVID-19, individuals continue to search for and consume specific herbs, foods, and commercial supplements for this purpose. This study will be aimed to estimate the uses of herbal and natural products during the COVID-19 infection to determine their usage reasons and evaluate their potential side effects. An online cross-sectional survey of different participants will be conducted and will be a focus on respondents’ chronic disease histories, socio-dmographic characteristics, and frequency and trends of using these products. Descriptive and univariate analyses will be performed to determine prevalence and associations between various products used and respondents’ socio-demographic data. Relationships will be tested using Pearson’s chi-square test or an exact probability test. Our main findings will give evidence of beneficial uses of natural products and herbal medicine as prophylactic and will be a vigorous approach to stop or at least slow down COVID-19 infection and transmission. This will be of great interest of public health, and the results of our study will lend health officials better control on the current pandemic.

Keywords: COVID-19, herbs, natural products, saudi arabia

Procedia PDF Downloads 218

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 478

Authors: Laura Seppälä, Ana Nuutinen

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Environmental concerns are increasing the interest in the potential uses of natural dyes. Natural dyes are more safe and environmentally friendly option than synthetic dyes. However, one must be also cautious with natural dyes, because, for example, some dyestuff such as plants or mushrooms, as well as some mordants are poisonous. By natural dyes we mean dyes that are derived from plants, fungi, bark, lichens, algae, insects, and minerals. Different plant parts, such as stems, leaves, flowers, roots, bark, berries, fruits, and cones, can be utilized for textile dyeing and printing, pigment manufacture, and other processes depending on the season. They may be utilized to produce distinctive colour tones that are challenging to do with synthetic dyes. This adds value to textiles and makes them stand out. Synthetic dyes quickly replaced natural dyes, after being developed in the middle of the 19th century, but natural dyes have remained the dyeing method of crafters until recently. This research examines the commercial solutions for natural dyes in many parts of the world, such as Europe, the United States, South America, Africa, Asia, New Zealand, and Australia. This study aims to determine the commercial status of natural dyes. Each continent has its own traditions and specific dyestuffs. The availability of natural dyes can vary depending on several aspects, including plant species, temperature, and harvesting techniques, which poses a challenge to the work of designers and crafters. While certain plants may only provide dyes during specific seasons, others may do so continuously. To find the ideal time to collect natural dyes, it is critical to research various plant species and their harvesting techniques. Furthermore, to guarantee the quality and colour of the dye, plant material must be handled and processed properly. This research was conducted via an internet search, and results were searched systematically for commercial stakeholders in the field. The research question looked at commercial players in the field of natural dyes. This qualitative case study interpreted the data using thematic analysis. Each webpage was screenshotted and analyzed in reflection on to research question. Online content analysis means systematically coding and analyzing qualitative data. The most evident result was that the natural dyes interest in different parts of the World. There are clothing collections dyed with natural dyes, dyestuff stores, and courses for natural dyeing. This article presents the designers who work with natural dyes and actors who are involved with the natural dye industry. Several websites emphasized the safety and environmental benefits of natural dyes. Many of them included eye-catching images of textiles dyed naturally, and the colours of such dyes are thought to be attractive since they are beautiful and natural hues. The search did not find big-scale industrial solutions for natural dyes, but there were several instances of dyeing with natural dyes. Understanding the players, designers, and stakeholders in the natural dye business is the purpose of this article. The comprehension of the current state of the art illustrates the direction that the natural dye business is currently taking.

Keywords: commercial solutions, environmental issues, key stakeholders, natural dyes, sustainability, textile dyeing

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Authors: Onyimonyi Anselm Ego, Obi-Keguna Christy, Dim Emmanuel Chinonso, Ugwuanyi Evelyn, Uzochukwu Ifeanyi Emmanuel

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A total of 144 Shaver Brown Layers in their sixteenth week of lay were used in a twelve weeks study to evaluate the egg yolk and serum cholesterol of the birds when fed varying dietary combinations of garlic and natural cocoa powder. The birds were randomly assigned into nine dietary treatments with 16 birds per treatment. Each bird was housed separately in a cage measuring 45 cm x 35 cm in an open sided battery cage house typical of the tropics. A standard poultry mash diet with 16.5% CP and 2800 KcalME/kg was formulated as the basal ration which also served as the control diet. Garlic and natural cocoa powder were incorporated in varying combinations (50 g or 100 g/100 kg of feed) in the remaining eight treatments. Weekly data of egg weight, egg length, egg diameter, yolk weight, albumen weight and hen day egg production were kept. Egg yolk and serum cholesterol levels were determined using a Randox kit. Results showed that birds receiving garlic and natural cocoa powder had significantly (P<0.05) reduced egg and albumen weight as compared to control birds. Hen day production of the birds was also significantly higher than control birds. Egg yolk and serum cholesterol of birds receiving the garlic and natural cocoa powder were significantly (P<0.05) lower than the control. Serum cholesterol levels showed decline in the birds receiving garlic and natural cocoa powder. The least yolk cholesterol level of 160 mg/dl was observed in birds receiving 50g garlic and 50 g natural cocoa powder (Treatment 5). Control birds had an egg cholesterol level of 245.45 mg/dl. It was concluded that incorporating garlic and natural cocoa powder in the diets of laying hens can result in a significant reduction in the egg and serum cholesterol levels.

Keywords: egg, serum, cholesterol, garlic

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Authors: Archna Mall, Neelam Agrawal, Hari O. Saxena, Bhavana Sharma

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Butea monosperma occurs widely throughout central Indian states. Eco-friendly natural dyes were isolated in aqueous medium from leaves, bark and flowers of this plant. These dyes were used for dyeing on cotton fabric using various chemical (potassium aluminium sulphate, potassium dichromate, ferrous sulphate, stannous chloride & tannic acid) and natural mordants (rinds of Terminallia bellerica & Terminalia chebula fruits and shells of Prunus dulcis & Juglans regia nuts). Dyeing was carried out using the pre-mordanting technique. Large range of beautiful shades in terms of hue and darkness were recorded because of varying mordant concentrations and combinations. More importantly dyed fabrics registered varying the degree of colour fastness properties to washing (1-3, colour change and 4-5, colour staining), light (2-4), rubbing (4-5, dry and 3-5, wet) and perspiration (1-4, colour change and 4-5, colour staining). Thus, along with flowers which are traditionally known for natural dyes, the leaves and bark may also find their place in textile industries.

Keywords: Butea monosperma, cotton, mordants, natural dyes

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Authors: Genady Grabarnik, Serge Yaskolko

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Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: Hellal Abdelkader, Chafaa Salah, Boudjemaa Fouzia

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A new, convenient, and high yielding procedure for the preparation of diethyl α-aminophosphonates in water via Kabachnik-Fields reaction by one-pot reaction of aromatic aldehydes, ortho-aminophenols, and dialkylphosphites in the presence of a low catalytic amount of citric, malic, tartaric, and oxalic acids as a natural, bi-functional, and highly stable catalyst is described, the obtained products were characterized by elemental analyses, molar conductance, magnetic susceptibility, FTIR, Uv-Vis spectral data, NMR-C, NMR-H, and NMR-P analyses.

Keywords: α-aminophosphonates, aminophenols, natural acids, aqueous media, Kabachnik-Fields reaction

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Authors: Fausto Morais

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Artificial intelligence has been widely used in law. Programs are able to classify suits, to identify decision-making patterns, to predict outcomes, and to formalize legal arguments as well. In Brazil, the artificial intelligence victor has been classifying cases to supreme court’s standards. When those programs act doing those tasks, they simulate some kind of legal decision and legal arguments, raising doubts about how artificial intelligence can be integrated into legal reasoning. Taking this into account, the following three issues are identified; the problem of hypernormatization, the argument of legal anthropocentrism, and the artificial legal principles. Hypernormatization can be seen in the Brazilian legal context in the Supreme Court’s usage of the Victor program. This program generated efficiency and consistency. On the other hand, there is a feasible risk of over standardizing factual and normative legal features. Then legal clerks and programmers should work together to develop an adequate way to model legal language into computational code. If this is possible, intelligent programs may enact legal decisions in easy cases automatically cases, and, in this picture, the legal anthropocentrism argument takes place. Such an argument argues that just humans beings should enact legal decisions. This is so because human beings have a conscience, free will, and self unity. In spite of that, it is possible to argue against the anthropocentrism argument and to show how intelligent programs may work overcoming human beings' problems like misleading cognition, emotions, and lack of memory. In this way, intelligent machines could be able to pass legal decisions automatically by classification, as Victor in Brazil does, because they are binding by legal patterns and should not deviate from them. Notwithstanding, artificial intelligent programs can be helpful beyond easy cases. In hard cases, they are able to identify legal standards and legal arguments by using machine learning. For that, a dataset of legal decisions regarding a particular matter must be available, which is a reality in Brazilian Judiciary. Doing such procedure, artificial intelligent programs can support a human decision in hard cases, providing legal standards and arguments based on empirical evidence. Those legal features claim an argumentative weight in legal reasoning and should serve as references for judges when they must decide to maintain or overcome a legal standard.

Keywords: artificial intelligence, artificial legal principles, hypernormatization, legal anthropocentrism argument, legal reasoning

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Authors: Kwame Amoah

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Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

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Authors: Mitchell Gohnert

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This paper reviews some fundamental concepts of structural optimization, which is focused on the shape of the structure. Bending stresses produce high peak stresses at each face of the member, and therefore, substantially more material is required to resist bending. The shape of the structure has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape to accommodate natural stress flow. The main objective of structural optimization is to direct the thrust line along the axis of the member. Optimal shapes include the catenary arch or dome, triangular shapes, and columns. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined. Structures, however, must resist multiple load patterns. An optimal shape is still possible by ensuring that the thrust lines fall within the middle third of the member.

Keywords: optimization, natural structures, shells, catenary, domes, arches

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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: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Zhiwen Yang, Jingyuan Li, Zhenkai Xie, Jian Ling, Jiguang Wang, Mengliang Li

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To reflect the effects of different emission control strategies, such as retrofitting after-treatment system and replacing with natural gas-fueled vehicles, on particle number (PN), particle mass (PM) and nitrogen oxides (NOx) emissions emitted by urban bus, a portable emission measurement system (PEMS) was employed herein to conduct real-world driving emission measurements on a diesel oxidation catalytic converter (DOC) and catalyzed diesel particulate filter (CDPF) retrofitting China IV diesel bus, a China IV diesel bus, and a China V natural gas bus. The results show that both tested diesel buses possess markedly advantages in NOx emission control when compared to the lean-burn natural gas bus equipped without any NOx after-treatment system. As to PN and PM, only the DOC+CDPF retrofitting diesel bus exhibits enormous benefits on emission control relate to the natural gas bus, especially the normal diesel bus. Meanwhile, the differences in PM and PN emissions between retrofitted and normal diesel buses generally increase with the increase in vehicle-specific power (VSP). Furthermore, the differences in PM emissions, especially those in the higher VSP ranges, are more significant than those in PN. In addition, the maximum peak PN particle size (32 nm) of the retrofitted diesel bus was significantly lower than that of the normal diesel bus (100 nm). These phenomena indicate that the CDPF retrofitting can effectively reduce diesel bus exhaust particle emissions, especially those with large particle sizes.

Keywords: CDPF, diesel, natural gas, real-world emissions

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Yuichi Miyamoto

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In regards to the energy sector in the modern period, two points were raised. First is a vast and growing energy demand, and second is an environmental impact associated with it. The enormous consumption of fossil fuel to the mobile unit is leading to its rapid depletion. Nuclear power is not the only problem. A modal shift that utilizes personal transporters and independent power, in order to realize a sustainable society, is very effective. The paper proposes that the world will continue to work on this. Energy of the future society, innovation in battery technology and the use of natural energy is a big key. And it is also necessary in order to save on energy consumption.

Keywords: natural energy, modal shift, personal transportation, battery

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Authors: M. E. Joret, F. Germeys, P. Van de Craen

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Background: Previous studies have shown that ‘full’ bilingualism seems to enhance the executive functions in children, young adults and elderly people. Executive functions refer to a complex cognitive system responsible for self-controlled and planned behavior and seem to predict academic achievement. The present study aimed at investigating whether similar effects could be found in children learning their second language at school in immersion education programs. Methods: In this study, 44 children involved in immersion education for 4 to 5 years were compared to 48 children in traditional schools. All children were between 9 and 11 years old. To assess executive functions, the Simon task was used, a neuropsychological measure assessing executive functions with reaction times and accuracy on congruent and incongruent trials. To control for background measures, all children underwent the Raven’s coloured progressive matrices, to measure non-verbal intelligence and the Echelle de Vocabulaire en Images Peabody (EVIP), assessing verbal intelligence. In addition, a questionnaire was given to the parents to control for other confounding variables, such as socio-economic status (SES), home language, developmental disorders, etc. Results: There were no differences between groups concerning non-verbal intelligence and verbal intelligence. Furthermore, the immersion learners showed overall faster reaction times on both congruent and incongruent trials compared to the traditional learners, but only after 5 years of training, not before. Conclusion: These results show that the cognitive benefits found in ‘full’ bilinguals also appear in children involved in immersion education, but only after a sufficient exposure to the second language. Our results suggest that the amount of second language training needs to be sufficient before these cognitive effects may emerge.

Keywords: bilingualism, executive functions, immersion education, Simon task

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Authors: Mirza Popovac

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This paper investigates the application of the vortex tubes towards increasing the efficiency of high temperature heat pumps based on natural refrigerants, by recovering a part of the expansion work within the refrigerant cycle. To this purpose the 3D Navier-Stokes solver is used to perform a set of numerical simulations, investigating the vortex tube performance. Firstly, the fluid flow and heat transfer characteristics are analyzed for standard configurations of vortex tubes, and the obtained results are validated against the experimental and numerical data available in literature. Subsequently, different geometry specifications are analyzed, as well as the interplay between relevant heat pump operating conditions and the properties of natural refrigerants. Finally, the characteristic curve of performance will be derived for investigated vortex tubes specifications when used within high temperature heat pumps.

Keywords: heat pump, vortex tube, CFD, natural refrigerant

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Authors: Phillip Garrad, Saritha Unnikrishnan

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The recent popularity of connected and autonomous vehicles (CAV) corresponds with an increase in the risk of cyber-attacks. These cyber-attacks have been instigated by both researchers or white-coat hackers and cyber-criminals. As Connected Vehicles move towards full autonomy, the impact of these cyber-attacks also grows. The current research details challenges faced in cybersecurity testing of CAV, including access and cost of the representative test setup. Other challenges faced are lack of experts in the field. Possible solutions to how these challenges can be overcome are reviewed and discussed. From these findings, a software simulated CAV network is established as a cost-effective representative testbed. Penetration tests are then performed on this simulation, demonstrating a cyber-attack in CAV. Studies have shown Artificial Intelligence (AI) to improve runtime, increase efficiency and comprehensively cover all the typical test aspects in penetration testing in other industries. There is an attempt to introduce similar AI models to the software simulation. The expectation from this implementation is to see similar improvements in runtime and efficiency for the CAV model. If proven to be an effective means of penetration test for CAV, this methodology may be used on a full CAV test network.

Keywords: cybersecurity, connected vehicles, software simulation, artificial intelligence, penetration testing

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Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

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Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

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Authors: Ploysai Ohama, Nuttawadee Hanchengchai, Thiva Saksri

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Natural dye extracted from Pterocarpus indicus was applied to a cotton fabric and silk yarn by dyeing processing different eco-friendly mordants. Analytical studies such as UV–VIS spectrophotometry and gravimetric analysis were performed on the extracts. The color of each dyed material was investigated in terms of the CIELAB (L*, a* and b*) and K/S values. Cotton fabric dyed without mordants had a shade of greenish-brown, while those post-mordanted with selected eco-friendly mordants such as alum, lemon juice and limewater result in a variety of brown and darker color shade of fabric.

Keywords: natural dyes, plant materials, dyeing, mordant

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Authors: Prakash Singh

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Being a collegial leader would require such a person to promote an organizational passion that identifies and acknowledges the contribution of every employee. Collegiality is about sharing responsibilities and being accountable for one’s actions. Leaders must therefore be equipped with the knowledge, skills, abilities, beliefs, and dispositions that will allow them to succeed in their organizations. These abilities should not only dwell on cognition alone, but also, equally, on the development of their emotional intelligence (EQ). It is therefore a myth that leaders are entrusted with absolute power to manage all the resources of their organizations. Workers feel confident with leaders who are adaptable, flexible and supportive when it comes to shared decision-making and the devolution of power within the organization. Research strongly supports the notion that a leader requires a high level of EQ in addition to IQ (cognitive intelligence) to achieve the goals of the organization. On the other hand, traditional managers require cognitive abilities and technical skills to get the work done by their employees. This does not imply that management is not important in organizations. However, the approach of managers becomes highly critical when the focus is purely task orientated. Enabling or empowering employees, therefore, is an important aspect in establishing emotionally intelligent collaboration, as the willing and satisfied participation of the employees can be the result of leaders’ commitment to establishing a collegial working environment as demonstrated by their behaviours. This paper therefore analyses why it matters for ideal leaders to be imbued with the traits of EQ and collegiality.

Keywords: collegiality, emotional intelligence, empowering employees, traditional managers

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Authors: Jarbas Lopes Cardoso Jr., Frederic Andres, Alexandre Guitton, Asanee Kawtrakul, Silvio E. Barbin

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The important objective of the CyberBrain Mass Agriculture Alarm Acquisition and Analysis (CBMa4) project is to minimize the impacts of diseases and disasters on rice cultivation. For example, early detection of insects will reduce the volume of insecticides that is applied to the rice fields through the use of CBMa4 platform. In order to reach this goal, two major factors need to be considered: (1) the social network of smart farmers; and (2) the warning data alarm acquisition and analysis component. This paper outlines the process for collecting the warning and improving the decision-making result to the warning. It involves two sub-processes: the warning collection and the understanding enrichment. Human sensors combine basic suitable data processing techniques in order to extract warning related semantic according to collective intelligence. We identify each warning by a semantic content called 'warncons' with multimedia metaphors and metadata related to these metaphors. It is important to describe the metric to measuring the relation among warncons. With this knowledge, a collective intelligence-based decision-making approach determines the action(s) to be launched regarding one or a set of warncons.

Keywords: agricultural engineering, warning systems, social network services, context awareness

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Authors: Seyed Sobhan Alvani, Mohammad Gohari

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By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.

Keywords: traffic index, population growth rate, cities wideness, artificial neural network

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Authors: Uma Shanker, Vidhisha Jassal

Abstract:

A novel green route was used to synthesize few metal hexacyanoferrates (FeHCF, NiHCF, CoHCF and CuHCF) nanoparticles using Sapindus mukorossias a natural surfactant and water as a solvent. The synthesized nanoparticles were characterized by Powder X-ray diffraction (PXRD), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Fourier Transform Infrared Spectroscopy (FTIR) and Thermo gravimetric techniques. Trasmission electron microscopic images showed that synthesized MHCF nanoparticles exhibited cubic and spherical shapes with exceptionally small sizes ranging from 3nm - 186 nm.

Keywords: metal hexacyanoferrates, natural surfactant, Sapindus mukorossias, nanoparticles

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Authors: Thiago Fabrizio Gavilano Farje, Marcelo Patricio Herrera Malpartida

Abstract:

This study examines the influence of artificial intelligence (AI) on the work efficiency of administrative employees in the financial sector of Metropolitan Lima, Peru, during the year 2024. Focusing on the relationship between AI implementation and work efficiency, it addresses specific variables such as decision-making, motivation, and employee productivity. To accomplish the analysis between AI and work efficiency within the financial sector of Metropolitan Lima, it is necessary to evaluate how AI optimizes time in administrative tasks, examine how AI impacts the agility of the process of making decisions, and investigate the influence of AI on the satisfaction and motivation of employees. The research adopts a correlational and explanatory approach, designed to establish and understand the connections between AI and work efficiency. A survey design adapted from an OECD study is used, applying questionnaires to a representative sample of administrative workers in the financial sector who incorporate AI into their functions. The target population includes administrative workers in the financial sector of Metropolitan Lima, estimated at 73,097 employees based on data from the Censo Nacional de Empresas y Establecimientos and studies by the BCRP. The sample, selected through simple random sampling, comprises 246 workers.

Keywords: business management, artificial intelligence, decision making, labor efficiency, financial sector

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Authors: Eman Alzahrani, Hala M. Abo-Dief, Ashraf T. Mohamed

Abstract:

The present work is aimed at examining carbon steel oil pipelines corrosion using three natural extracts (Eruca Sativa, Rosell and Mango peels) that are used as inhibitors of different concentrations ranging from 0.05-0.1wt. %. Two sulphur compounds are used as corrosion mediums. Weight loss method was used for measuring the corrosion rate of the carbon steel specimens immersed in technical white oil at 100ºC at various time intervals in absence and presence of the two sulphur compounds. The corroded specimens are examined using the chemical wear test, scratch test and hardness test. The scratch test is carried out using scratch loads from 0.5 Kg to 2.0 Kg. The scratch width is obtained at various scratch load and test conditions. The Brinell hardness test is carried out and investigated for both corroded and inhibited specimens. The results showed that three natural extracts can be used as environmentally friendly corrosion inhibitors.

Keywords: inhibition, natural extract, oil pipelines corrosion, sulphur compounds

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Authors: Baltazar Ndakidemi

Abstract:

The resource-constrained farmers, especially those in sub-Saharan Africa, encounter significant challenges related to agriculture, notably diseases and pests. The sustainable means of pest management are not well known to farmers. As a result, some farmers use synthetic pesticides whose environmental impacts, ill health, and other negative impacts of synthetic pesticides on natural enemies have posed a great need for more sustainable means of pest management. Pesticidal plant resources can replace synthetic pesticides because their secondary metabolites can exhibit insecticidal activities such as deterrence, repellence, and pests' mortality. Additionally, the volatiles from these plants can have positive effects of attracting populations of natural enemies. Pesticidal plants can be grown as field margin plants or in strips for supporting natural enemies' populations. However, this is practically undetermined. Hence, there is a need to investigate the roles played by pesticidal plants in supporting natural enemies of pests and their applications in different cropping systems such as legumes. This study investigates different pesticidal plants with a high potential for pest control in agricultural fields. The information sheds light on potential plants that can be used for different crop pests.

Keywords: natural enemies, biological control, synthetic pesticides, pesticidal plants, predators, parasitoids

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Authors: Khiari Nor El Houda, Hiouani Amira Sarra

Abstract:

Many EFL students with high capacities are hidden because they suffer from speaking anxiety (SA). Most of them find public speaking much demanding. They feel unable to communicate, they fear to make mistakes and they fear negative evaluation or being called on. With the growing number of the learners who suffer from foreign language speaking anxiety (FLSA), it is becoming increasingly difficult to ignore its harmful outcomes on their performance and success, especially during their first contact with the pupils, as they will be teaching in the near future. Different researchers suggested different ways to minimize the negative effects of FLSA. The present study sheds light on emotional intelligence skills training as an effective strategy not only to influence public speaking success but also to help pre-service EFL teachers lessen their speaking anxiety and eventually to prepare them for their professional career. A quasi-experiment was used in order to examine the research hypothesis. We worked with two groups of third-year EFL students at Oum El Bouaghi University. The Foreign Language Classroom Anxiety Scale (FLCAS) and the Emotional Quotient Inventory (EQ-i) were used to collect data about the participants’ FLSA and EI levels. The analysis of the data has yielded that the assumption that there is a negative correlation between EI and FLSA was statistically validated by the Pearson Correlation Test, concluding that, the more emotionally intelligent the individual is the less anxious s/he will be. In addition, the lack of amelioration in the results of the control group and the noteworthy improvement in the experimental group results led us to conclude that EI skills training was an effective strategy in minimizing the FLSA level and therefore, we confirmed our research hypothesis.

Keywords: emotional intelligence, emotional intelligence skills training, EQ-I, FLCAS, foreign language speaking anxiety, pre-service EFL teachers

Procedia PDF Downloads 140