Search results for: artificial food

Authors: Mohammad Heidari

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In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

Procedia PDF Downloads 403

Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

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Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

Procedia PDF Downloads 64

Authors: Godwin A. Otogo, Sansanee Wangvoralak, Graham J. Pierce, Lee C. Hastie, Beth Scott

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The squid Loligo forbesii is suspected to be an important species in marine food webs, as it can strongly impact its prey and be impacted upon by predation, competition, fishing and/or climate variability. To quantify these impacts in the food web, the measurement of its trophic position and ecological role within well-studied ecosystems is essential. An Ecopath model was balanced and run for the Moray Firth ecosystem and was used to investigate the significance of this squid’s trophic roles. The network analysis routine included in Ecopath with Ecosim (EwE) was used to estimate trophic interaction, system indicators (health condition and developmental stage) and food web features. Results indicated that within the Moray Firth squid occupy a top trophic position in the food web and also a major prey item for many other species. Results from Omnivory Index (OI) showed that squid is a generalized feeder transferring energy across wide trophic levels and is more important as a predator than that as a prey in the Moray Firth ecosystem. The results highlight the importance of taking squid into account in the management of Europe’s living marine resources.

Keywords: Squid, Loligo forbesii, Ecopath, Moray Firth, Trophic level

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Authors: Hsien-Tsen Wang

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Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

Procedia PDF Downloads 84

Authors: Saira Naeem, Rana Muhammad Ayyub

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The main objective of this study is to empirically study the antecedents of perceptions of non-Muslim consumers towards Halal foods. The questionnaire survey was conducted through surveymonkey.com from non-Muslims (n=222) of USA. The validated scales of knowledge about Halal foods, animal welfare concerns, acculturation and perception about Halal foods were adopted after necessary adaptation as measures. The structural equation modelling (SEM) approach was used to study the structural model. It was found that Knowledge about Halal foods and ongoing acculturation among non-Muslims has a positive effect on perception about Halal food whereas; animal welfare concerns have negative effect on it. Furthermore, the acculturation has moderating effects but it was found non-significant. It is recommended that Halal food marketers should increase their efforts to educate customers by updating their knowledge about it. Furthermore, it is recommended that the non-Muslim consumers must be apprised of the fact that their animal welfare concerns are adequately addressed while Halal food production and supply chain. Online data collection is the only limitation of this study. This study will guide the Halal marketers of western countries about how to market the Halal food products and services to serve the non-Muslim customers.

Keywords: non-Muslims, consumer perceptions, animal welfare concerns, acculturation, knowledge about Halal

Procedia PDF Downloads 103

Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Hamed Sadeghi, Pouya A. Panahi, Hamed Nasiri, Mohammad Sadeghi

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Collapsible soils like loess comprise an important category of problematic soils for construction purposes and sustainable development. As a result, research on both geological and geotechnical aspects of this type of soil have been in progress for decades. However, considerable natural variability in physical properties of in-situ loess strata even in a single block sample challenges the fundamental laboratory investigations. The reason behind this is that it is somehow impossible to remove the effect of a specific factor like void ratio from fair comparisons to come with a reliable conclusion. In order to cope with this limitation, two types of artificially made dispersive and calcareous loess are introduced which can be easily reproduced in any soil mechanics laboratory provided that all its compositions are known and controlled. The collapse potential is explored for a variety of soil water salinity and lime content and comparisons are made against the natural soil behavior. Trends are reported for the influence of pore water salinity on collapse potential under different osmotic flow conditions. The most important advantage of artificial loess is the ease of controlling cementing agent content like calcite or dispersive potential for studying their influence on mechanical soil behavior.

Keywords: artificial loess, unsaturated soils, collapse potential, dispersive clays, laboratory tests

Procedia PDF Downloads 178

Authors: Waleed Basuliman

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Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

Procedia PDF Downloads 477

Authors: M. Unis, S. Turky, A. Elalem, A. Meshrghi

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The Esterification kinetics of acetic acid with isopropnol in the presence of sulfuric acid as a homogenous catalyst was studied with isothermal batch experiments at 60,70 and 80°C and at a different molar ratio of isopropnol to acetic acid. Investigation of kinetics of the reaction indicated that the low of molar ratio is favored for esterification reaction, this is due to the reaction is catalyzed by acid. The maximum conversion, approximately 60.6% was obtained at 80°C for molar ratio of 1:3 acid : alcohol. It was found that increasing temperature of the reaction, increases the rate constant and conversion at a certain mole ratio, that is due to the esterification is exothermic. The homogenous reaction has been described with simple power-law model. The chemical equilibrium combustion calculated from the kinetic model in agreement with the measured chemical equilibrium.

Keywords: artificial flavors, esterification, chemical equilibria, isothermal

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Authors: Sameh A. S. Thabit Alariqi

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Food is widely packaged with plastic materials to prevent microbial contamination and spoilage. Ionizing radiation is widely used to sterilize the food-packaging materials. Sterilization by γ-radiation causes degradation for the plastic packaging materials such as embrittlement, stiffening, softening, discoloration, odour generation, and decrease in molecular weight. Many antioxidants can prevent γ-degradation but most of them are toxic. The migration of antioxidants to its environment gives rise to major concerns in case of food packaging plastics. In this attempt, we have aimed to utilize synergistic mixtures of stabilizers which are approved for food-contact applications. Ethylene-propylene-diene terpolymer (EPDM) have been melt-mixed with hindered amine stabilizers (HAS), phenolic antioxidants and organo-phosphites (hydroperoxide decomposer). Results were discussed by comparing the stabilizing efficiency of mixtures with and without phenol system. Among phenol containing systems where we mostly observed discoloration due to the oxidation of hindered phenol, the combination of secondary HAS, tertiary HAS, organo-phosphite and hindered phenol exhibited improved stabilization efficiency than single or binary additive systems. The mixture of secondary HAS and tertiary HAS, has shown antagonistic effect of stabilization. However, the combination of organo-phosphite with secondary HAS, tertiary HAS and phenol antioxidants have been found to give synergistic even at higher doses of -sterilization. The effects have been explained through the interaction between the stabilizers. After γ-irradiation, the consumption of oligomeric stabilizer significantly depends on the components of stabilization mixture. The effect of the organo-phosphite antioxidant on the overall stability has been discussed.

Keywords: ethylene-propylene-diene terpolymer, synergistic mixtures, gamma sterilization, gamma stabilization

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Authors: Xiaochen Mu

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Whether in common law countries that adhere to the "commercial copyright theory" or in civil law countries that center around "author's rights," the standards for judging originality have undergone continuous adjustments in response to the development of information technology. The adherence to originality standards does not arbitrarily dictate that all types of works be judged according to a single standard of originality, nor does it rigidly ignore the changes in creative methods and dissemination models brought about by technology. Adjustments and interpretations should be allowed based on the different forms of expression of works. Appropriate adjustments and interpretations are our response to technological advancements. However, what should be upheld are the principles and bottom lines of these adjustments and interpretations, namely the legislative intent and purpose of copyright law, which are to encourage the creation and dissemination of outstanding cultural works and to promote the flourishing of culture.

Keywords: generative artificial intelligence, originality, works, copyright

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Authors: Ke Yang, QiHan, Bauke de Veirs

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This study addresses the need for coordinated management of natural resources in urban agglomeration. Using ecosystem services theory, The study explore the relationship between land use in the Beijing-Tianjin-Hebei (B-T-H) region and the Food-Water-Energy (F-W-E) nexus from 2000 to 2030. We assess ecosystem services using the InVEST: Habitat Quality (HQ), Water Yield (WY), Carbon Sequestration (CS), Soil Retention (SDR), and Food Production (FP). The study find an annual expansion of construction land alongside a significant decline in cultivated land. Additionally, HQ, CS, and per capita FP decline annually until 2020 and are expected to persist through 2030. In contrast, WY and SDR grow annually but may decline by 2030. Spearman coefficient analysis reveals synergies between HQ and CS, SDR and CS, and SDR and HQ, with trade-offs between CS and WY and HQ and WY. Utilizing the K-means clustering analysis method, we introduce county-based spatial planning for the F-W-E system, offering valuable insights and recommendations for sustainable resource management.

Keywords: food-water-energy (F-W-E), ecosystem services, trade-offs and synergies, ecosystem service bundle, county-based

Procedia PDF Downloads 51

Authors: M.Younus, M. Athar Khan, Asif Adrees

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The present research endeavour was made to investigate the Public Health impact of Salmonellosis through consuming the meat and eggs of the carrier’s birds and to see the prevalence of Salmonella enteritidis and Salmonella typhimurium from poultry feed, poultry meat, and poultry eggs and their role in the chain of transmission of salmonellae to human beings and causing food poisoning. The ultimate objective was to generate data to improve the quality of poultry products and human health awareness. Salmonellosis is one of the most wide spread food borne zoonoses in all the continents of the world. The etiological agents Salmonella enteritidis and Salmonella typhimurium not only produce the disease but during the convalescent phase (after the recovery of disease) remain carriers for indefinite period of time. The carrier state was not only the source of spread of disease with in the poultry but also caused typhoid fever in humans. The chain of transmission started from poultry feed to poultry meat and ultimately to humans as dead end hosts. In this experiment a total number of 200 samples of human stool and blood were collected randomly (100 samples of human stool and 100 samples of human blood) of 100 patients suspected from food poisoning patients from different hospitals of Lahore area for the identification of Salmonella enteritidis and Salmonella typhimurium through PCR method in order to see the public health impact of Salmonellosis through consuming the meat and eggs of the carrier birds. On the average 14 and 10 stool samples were found positive against Salmonella enteritidis and Salmonella typhimurium from each of the 25 patients from each hospital respectively in case of suspected food poisoning patients. Similarly on an average 5% and 6% blood samples were found positive from 25 patients of each hospital respectively. There was a significant difference (P< 0.05) in the sero positivity of stool and blood samples of suspected food poisoning patients as far as Salmonella enteritidis and Salmonella typhimurium was concerned. However there was no significant difference (P<0.05) between the hospitals.

Keywords: salmonella, zoonosis, food, transmission, eggs

Procedia PDF Downloads 652

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

Procedia PDF Downloads 144

Authors: Moshe Davidian, Shlomo Mark, Yotam Lurie

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With the rapid development of technology and the concomitant growth in the capability of Artificial Intelligence (AI) systems and their power, the ethical challenges involved in these systems are also evolving and increasing. In recent years, various organizations, including governments, international institutions, professional societies, civic organizations, and commercial companies, have been choosing to address these various challenges by publishing ethical codes for AI systems. However, despite the apparent agreement that AI should be “ethical,” there is debate about the definition of “ethical artificial intelligence.” This study investigates the various AI ethical codes and their key ethical values. From the vast collection of codes that exist, it analyzes and compares 25 ethical codes that were found to be representative of different types of organizations. In addition, as part of its literature review, the study overviews data collected in three recent reviews of AI codes. The results of the analyses demonstrate a convergence around seven key ethical values. However, the key finding is that the different AI ethical codes eventually reflect the type of organization that designed the code; i.e., the organizations’ role as regulator, user, or developer affects the view of what ethical AI is. The results show a relationship between the organization’s role and the dominant values in its code. The main contribution of this study is the development of a list of the key values for all AI systems and specific values that need to impact the development and design of AI systems, but also allowing for differences according to the organization for which the system is being developed. This will allow an analysis of AI values in relation to stakeholders.

Keywords: artificial intelligence, ethical codes, principles, values

Procedia PDF Downloads 91

Authors: Isma Alfia Novita

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Indonesia is one country with the largest agricultural producer in the world but still can not meet the needs of the national rice. In addition, Indonesia was ranked the second-largest rice importer after the Philippines. Indonesia's rice consumption reached 102 kg per capita, or almost twice the average global rice consumption is only 60 kg per capita per year. One of the government's efforts in developing national food consumption is to invite people to improve diversification and food security. This is done considering the diet of Indonesia is still high consumption of rice. Therefore, this program made innovations Rice Moringa namely imitation rice with the addition of Moringa (Moringa oleifera). Moringa is a plant that is widely grown and easily found. In addition, Moringa has many benefits because it contains vitamin A, vitamin B, vitamin C, calcium, protein, and potassium. Based on the analysis of the nutrient content, it is known that the Moringa leaves have good potential to maintain the balance of nutrients in the body

Keywords: imitation rice, Moringa oliefera, Moringa, AFTA

Procedia PDF Downloads 113

Authors: Pil Kyoo Jo, Youngmee Lee, Jee Young Kim, Yu Jin Oh, Sohyun Park, Young Ha Joo, Hye Suk Kim, Semi Kang

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A growing number of people are living alone and eating alone. People might have different dietary behaviors between eating alone and eating with others, it can influence their weight and health. The purpose of this study was to investigate the dietary behavior of eating alone in middle-aged populations in South Korea. We used the nationally representative data from the 5th Korea National Health and Nutrition Examination Survey (KNHANES), 2010-2012 and a cross-sectional survey on the eating behaviors among adults (N=1318, 530 men, 788 women) aged from 20 to 54 years. Results showed that ‘underweight’ group ate more amount of food when eating with others compared to eating alone and ‘overweight’ and ‘obesity’ groups had opposite respondent (p<0.05). When having a meal alone, ‘underweight’ group ate food until didn’t feel hungry and ‘overweight’ and ‘obesity’ groups ate leftover food even they felt full (p<0.01). The ‘overweight’ and ‘obesity’ groups usually ate alone than ‘underweight’ group did (p<0.05). All groups had faster meal time when eating alone than eating with others and usually ate processed foods for convenience when eating alone. Younger people, aged 10-30, ate more processed food than older people did. South Koreans spend nearly 45% of their total food consumption from processed foods. This research was supported by the National Research Foundation of Korea for 2011 Korea-Japan Basic Scientific Cooperation Program (NRF-2011B00003). This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2015S1A5B6037369).

Keywords: BMI, dietary behavior, eating alone, middle-aged populations

Procedia PDF Downloads 258

Authors: Talaat Ahmed, Amna Babssail

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Mangroves are evergreen trees and grow along the coastal areas of Qatar. The largest and oldest area of mangroves can be found around Al-Thakhira and Al-Khor. Other mangrove areas originate from fairly recent plantings by the government, although unfortunately the picturesque mangrove lake in Al-Wakra has now been uprooted. Avicinnia marina is the predominant mangrove species found in the region. Mangroves protect and stabilize low lying coastal land, and provide protection and food sources for estuarine and coastal fishery food chains. They also serve as feeding, breeding and nursery grounds for a variety of fish, crustaceans, reptiles, birds and other wildlife. A total of 21 individuals of A. marina, representing seven diverse Natural and artificial populations, were sampled throughout its range in Qatar. Leaves from 2-3 randomly selected trees at each location were collected. The locations are as follows: Al-Rawis, Ras-Madpak, Fuwairt, Summaseima, Al-khour, AL-Mafjar and Zekreet. Total genomic DNA was extracted using commercial DNeasy Plant System (Qiagen, Inc., Valencia, CA) kit to be used for genetic diversity analysis. Total of 12 (Inter-Simple Sequence Repeat) ISSR primers were used to amplify DNA fragments using genomic DNA. The 12 ISSR primers amplified polymorphic bands among mangrove samples in different areas as well as within each area indicating the existing of variation within each area and among the different areas of mangrove in Qatar. The results could characterize Avicinnia marina populations exist in different areas of Qatar and establish DNA fingerprint documentations for mangrove population to be used in further studies. Moreover, existing of genetic variation within and among Avicinnia marina populations is a strong indication for the ability of such populations to adapt different environmental conditions in Qatar. This study could be a warning to save mangrove in Qatar and save the environment as well.

Keywords: DNA fingerprint, Avicinnia marina, genetic analysis, Qatar

Procedia PDF Downloads 382

Authors: P. Ghosh, S. B. Sharma

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The growing problem of food waste is causing unacceptable economic, environmental and social impacts across the globe. In Australia, food waste is estimated at about AU$8 billion per year; however, information on the extent of wastage at different stages of the food value chain from farm to fork is very limited. This study aims to identify causes for and extent of food waste at wholesaler stage of the food value chain in the state of Western Australia. It also explores approaches applied to reduce and utilize food waste by the wholesalers. The study was carried out at Perth city market in Caning Vale, the main wholesale distribution centre for fruits and vegetables in Western Australia. A survey questionnaire was prepared and shared with 51 wholesalers and their responses to 10 targeted questions on quantity of produce (fruits and vegetables) delivery received and further supplied, reasons for waste generation and innovations applied or being considered to reduce and utilize food waste. Data were computed using the Statistical Package for the Social Sciences (SPSS version 21). Among the wholesalers 52% were primary wholesalers (buy produce directly from growers) and 48% were secondary wholesalers (buy produce in bulk from major wholesalers and supply to the local retail market, caterers, and customers with specific requirements). Average fruit and vegetable waste was 180 Kilogram per week per primary wholesaler and 30 Kilogram per secondary wholesaler. Based on this survey, the fruit and vegetable waste at wholesaler stage was estimated at about 286 tonnes per year. The secondary wholesalers distributed pre-ordered commodities, which minimized the potential to cause waste. Non-parametric test (Mann Whitney test) was carried out to assess contributions of wholesalers to waste generation. Over 56% of secondary wholesalers generally had nothing to bin as waste. Pearson’s correlation coefficient analysis showed positive correlation (r = 0.425; P=0.01) between the quantity of produce received and waste generated. Low market demand was the predominant reason identified by the wholesalers for waste generation. About a third of the wholesalers suggested that high cosmetic standards for fruits and vegetables - appearance, shape, and size - should be relaxed to reduce waste. Donation of unutilized fruits and vegetables to charity was overwhelmingly (95%) considered as one of the best options for utilization of discarded produce. The extent of waste at other stages of fruit and vegetable supply chain is currently being studied.

Keywords: food waste, fruits and vegetables, supply chain, waste generation

Procedia PDF Downloads 301

Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

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Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: Antwi Kwaku Dei, Lyford Conrad Power

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This paper investigates the outcome of participating in the government of Ghana block farm program on rural households’ farm productivity, income, food security and nutritional status in Northern Ghana using cross-sectional data. Data analysis was done using the Instrumental Variable and the Heckman Selection Bias procedures. Our analysis indicates that participation in the block farm program significantly increased directly the productivity of maize, rice, and soybean by 21.3 percent, 15.8 percent, and 12.3 percent respectively. Also, the program participation was found to increase households’ farm income by 20 percent in northern Ghana. Furthermore, program participation was found to improve household food security and nutrition by 19 percent and 14 percent respectively through income effect. Based on the benefit-cost ratio of 1.59 the results from the study recommends that the program is expanded to other communities in the northern region. Further analysis indicates that rural households’ decision to participate in food security intervention programs is significantly influenced by factors including the gender of the household head, the age of the household head, and household size. Results of the study further show that gender of household head, household size, household monthly income, household assets, women educational status, the age of women, marital status of women, are significant determinants of food security and nutrition status in Northern Ghana.

Keywords: block farm program, farm productivity, , household food security, Northern Ghana

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Authors: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

Procedia PDF Downloads 365

Authors: Andres Piña, Amy Meléndez, Pablo Cano, Tomas Cahuich

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The purpose of this project is to propose a quick and environmentally friendly alternative to measure the quality of oils used in food industry. There is evidence that repeated and indiscriminate use of oils in food processing cause physicochemical changes with formation of potentially toxic compounds that can affect the health of consumers and cause organoleptic changes. In order to assess the quality of oils, non-destructive optical techniques such as Interferometry offer a rapid alternative to the use of reagents, using only the interaction of light on the oil. Through this project, we used interferograms of samples of oil placed under different heating conditions to establish the changes in their quality. These interferograms were obtained by means of a Mach-Zehnder Interferometer using a beam of light from a HeNe laser of 10mW at 632.8nm. Each interferogram was captured, analyzed and measured full width at half-maximum (FWHM) using the software from Amcap and ImageJ. The total of FWHMs was organized in three groups. It was observed that the average obtained from each of the FWHMs of group A shows a behavior that is almost linear, therefore it is probable that the exposure time is not relevant when the oil is kept under constant temperature. Group B exhibits a slight exponential model when temperature raises between 373 K and 393 K. Results of the t-Student show a probability of 95% (0.05) of the existence of variation in the molecular composition of both samples. Furthermore, we found a correlation between the Iodine Indexes (Physicochemical Analysis) and the Interferograms (Optical Analysis) of group C. Based on these results, this project highlights the importance of the quality of the oils used in food industry and shows how Interferometry can be a useful tool for this purpose.

Keywords: food industry, interferometric, oils, quality control

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Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq

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Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.

Keywords: Cox regression, neural networks, survival, cancer.

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Authors: Chandanee Wasana Kalansooriya

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Dietary behaviour is a crucial factor affecting diabetes control. With increasing rates of diabetes prevalence in Asian countries, examining their dietary patterns, which are largely based on rice, is timely required. It has been identified that higher consumption of some rice varieties is associated with increased risk of type 2 diabetes. Although diabetes patients are advised to consume healthier rice varieties, which contains low glycemic, several conditions, one of which food insecurity, make them difficult to preserve those healthy dietary guidelines. Hence this study tries to investigate how food security affects on making right decisions of rice consumption within diabetes affected households using a sample from Sri Lanka, a country which rice considered as the staple food and records the highest diabetes prevalence rate in South Asia. The study uses data from the Household Income and Expenditure Survey 2016, a nationally representative sample conducted by the Department of Census and Statistics, Sri Lanka. The survey used a two-stage stratified sampling method to cover different sectors and districts of the country and collected micro-data on demographics, health, income and expenditures of different categories. The study uses data from 2547 households which consist of one or more diabetes patients, based on the self-recorded health status. The Household Dietary Diversity Score (HDDS), which constructed based on twelve food groups, is used to measure the level of food security. Rice is categorized into three groups according to their Glycemic Index (GI), high GI, medium GI and low GI, and the likelihood and impact made by food security on each rice consumption categories are estimated using a Two-part Model. The shares of each rice categories out of total rice consumption is considered as the dependent variable to exclude the endogeneity issue between rice consumption and the HDDS. The results indicate that the consumption of medium GI rice is likely to increase with the increasing household food security, but low GI varieties are not. Households in rural and estate sectors are less likely and Tamil ethnic group is more likely to consume low GI rice varieties. Further, an increase in food security significantly decreases the consumption share of low GI rice, while it increases the share of medium GI varieties. The consumption share of low GI rice is largely affected by the ethnic variability. The effects of food security on the likelihood of consuming high GI rice varieties and changing its shares are statistically insignificant. Accordingly, the study concludes that a higher level of food security does not ensure diabetes patients are consuming healthy rice varieties or reducing consumption of unhealthy varieties. Hence policy attention must be directed towards educating people for making healthy dietary choices. Further, the study provides a room for further studies as it reveals considerable ethnic and sectorial differences in making healthy dietary decisions.

Keywords: diabetes, food security, glycemic index, rice consumption

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Authors: Hans Schumann, Colin Domnauer, Louis Rosenberg

Abstract:

In this study, machine learning techniques were deployed on real-time human swarm data to forecast the likelihood of outcomes for English Premier League matches in the 2020/21 season. These techniques included ensemble models in combination with neural networks and were tested against an industry standard of Vegas Oddsmakers. Predictions made from the collective intelligence of human swarm participants managed to achieve a positive return on investment over a full season on matches, empirically proving the usefulness of a new artificial intelligence valuing human instinct and intelligence.

Keywords: artificial intelligence, data science, English Premier League, human swarming, machine learning, sports betting, swarm intelligence

Procedia PDF Downloads 195

Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

Abstract:

Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

Procedia PDF Downloads 346

Authors: Mohammed Sabbah, Asmaa Al-Asmar, Doaa Abu-Hani, Fuad Al-Rimawi

Abstract:

Plant extracts are an increasingly popular natural product with a wide range of potential applications in food, industrial, and health care industries. They are rich in polyphenolic compounds and flavonoids, which have been demonstrated to possess a variety of beneficial properties, including antimicrobial and antioxidant activity. Plant extracts have been found to possess antimicrobial activity against a variety of foodborne pathogens and can be used as a natural preservative to extend the shelf life of food products. They have also strong antioxidant activity, which can reduce the formation of free radicals and oxidation of food components. Recently there is an increase interest in bio-based polymers to be used as innovative “bioplastics” for industrial exploitation e.g. packaging materials for food products. Additionally, incorporation of active compounds (e.g. antioxidants and antimicrobials) in bio-polymer materials is of particular interest since such active polymers can be used as active packaging materials (with antimicrobial and antioxidant activity). In this work, different plant extracts have been characterized for their phenolic compounds, flavonoids content, antioxidant activity (both as free radical scavenging ability and reducing ability), and antimicrobial activity against gram positive and negative bacteria (Escherichia coli; Staphylococcus aureus, and Pseudomonas aeruginosa) as well as antifungal activities (against yeast, mold and Botrytis cinera/a plant pathogen). Results showed that many extracts are rich with polyphenolic compounds and flavonoids and have strong antioxidant activities, and rich with phytochemicals (e.g. rutin, quercetin, oleuropein, tyrosol and hydroxytyrosol). Some extracts showed antibacterial activity against both gram positive and negative bacteria as well as antifungal activities and can work, therefore, as preservatives for food or pharmaceutical industries. As an application, two extracts were used as additive to pectin-based packaging film, and results showed that the addition of these extracts significantly improve their functionality as antimicrobial and antioxidant activity. These biomaterials, therefore can be used in food packaging materials to extend the shelf life of food products.

Keywords: plant extracts, antioxidants, flavonoids, bioplastic, edible biofilm, packaging materials

Procedia PDF Downloads 61

Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

Abstract:

Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

Procedia PDF Downloads 135